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Psychological distress and associated factors among asthmatic patients in Southern, Ethiopia, 2021

There is an increased prevalence of psychological distress in adults with asthma. Psychological distress describes unpleasant feelings or emotions that impact the level of functioning. It is a significant exac...

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Retrospective assessment of a collaborative digital asthma program for Medicaid-enrolled children in southwest Detroit: reductions in short-acting beta-agonist (SABA) medication use

Real-world evidence for digitally-supported asthma programs among Medicaid-enrolled children remains limited. Using data from a collaborative quality improvement program, we evaluated the impact of a digital i...

Nonadherence to antiasthmatic medications and its predictors among asthmatic patients in public hospitals of Bahir Dar City, North West Ethiopia: using ASK-12 tool

Globally, adequate asthma control is not yet achieved. The main cause of uncontrollability is nonadherence to prescribed medications.

The hen and the egg question in atopic dermatitis: allergy or eczema comes first

Atopic dermatitis (AD) as a chronic inflammatory systemic condition is far more than skin deep. Co-morbidities such as asthma and allergic rhinitis as well as the psychological impact influence seriously the q...

Medication regimen complexity and its impact on medication adherence and asthma control among patients with asthma in Ethiopian referral hospitals

Various studies have found that medication adherence is generally low among patients with asthma, and that the complexity of the regimen may be a potential factor. However, there is no information on the compl...

Monoclonal antibodies targeting small airways: a new perspective for biological therapies in severe asthma

Small airway dysfunction (SAD) in asthma is characterized by the inflammation and narrowing of airways with less of 2 mm in diameter between generations 8 and 23 of the bronchial tree. It is now widely accepte...

Level of asthma control and its determinants among adults living with asthma attending selected public hospitals in northwestern, Ethiopia: using an ordinal logistic regression model

Asthma is a major public health challenge and is characterized by recurrent attacks of breathlessness and wheezing that vary in severity and frequency from person to person. Asthma control is an important meas...

Static lung volumes and diffusion capacity in adults 30 years after being diagnosed with asthma

Long-term follow-up studies of adults with well-characterized asthma are sparse. We aimed to explore static lung volumes and diffusion capacity after 30 + years with asthma.

Over-prescription of short-acting β 2 -agonists and asthma management in the Gulf region: a multicountry observational study

The overuse of short-acting β 2 -agonists (SABA) is associated with poor asthma control. However, data on SABA use in the Gulf region are limited. Herein, we describe SABA prescription practices and clinical outcom...

A serological biomarker of type I collagen degradation is related to a more severe, high neutrophilic, obese asthma subtype

Asthma is a heterogeneous disease; therefore, biomarkers that can assist in the identification of subtypes and direct therapy are highly desirable. Asthma is a chronic inflammatory disease that leads to change...

Adherence to inhalers and associated factors among adult asthma patients: an outpatient-based study in a tertiary hospital of Rajshahi, Bangladesh

Adherence to inhaler medication is an important contributor to optimum asthma control along with adequate pharmacotherapy. The objective of the present study was to assess self-reported adherence levels and to...

The link between atopic dermatitis and asthma- immunological imbalance and beyond

Atopic diseases are multifactorial chronic disturbances which may evolve one into another and have overlapping pathogenetic mechanisms. Atopic dermatitis is in most cases the first step towards the development...

The effects of nebulized ketamine and intravenous magnesium sulfate on corticosteroid resistant asthma exacerbation; a randomized clinical trial

Asthma exacerbation is defined as an acute attack of shortness of breath with more than 25% decrease in morning peak flow compared to the baseline on 2 consecutive days, which requires immediate standard thera...

Determinants of asthma in Ethiopia: age and sex matched case control study with special reference to household fuel exposure and housing characteristics

Asthma is a chronic inflammatory disorder characterized by airway obstruction and hyper-responsiveness. Studies suggest that household fuel exposure and housing characteristics are associated with air way rela...

Feasibility and acceptability of monitoring personal air pollution exposure with sensors for asthma self-management

Exposure to fine particulate matter (PM 2.5 ) increases the risk of asthma exacerbations, and thus, monitoring personal exposure to PM 2.5 may aid in disease self-management. Low-cost, portable air pollution sensors...

Biological therapy for severe asthma

Around 5–10% of the total asthmatic population suffer from severe or uncontrolled asthma, which is associated with increased mortality and hospitalization, increased health care burden and worse quality of lif...

Treatment outcome clustering patterns correspond to discrete asthma phenotypes in children

Despite widely and regularly used therapy asthma in children is not fully controlled. Recognizing the complexity of asthma phenotypes and endotypes imposed the concept of precision medicine in asthma treatment...

Positive change in asthma control using therapeutic patient education in severe uncontrolled asthma: a one-year prospective study

Severe asthma is difficult to control. Therapeutic patient education enables patients to better understand their disease and cope with treatment, but the effect of therapeutic patient education in severe uncon...

Asthma and COVID-19: a dangerous liaison?

The coronavirus disease 2019 (COVID-19) pandemic, caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), provoked the most striking international public health crisis of our time. COVI...

Knowledge, attitude, and practice towards COVID-19 among chronic disease patients at Aksum Hospital, Northern Ethiopia, 2020: a cross-sectional study

The Coronavirus disease 2019 outbreak is the first reported case in Wuhan, China in December 2019 and suddenly became a major global health concern. Currently, there is no vaccine and treatment have been repor...

Self-reported vs. objectively assessed adherence to inhaled corticosteroids in asthma

Adherence to inhaled corticosteroids (ICS) in asthma is vital for disease control. However, obtaining reliable and clinically useful measures of adherence remains a major challenge. We investigated the associa...

Association between prevalence of obstructive lung disease and obesity: results from The Vermont Diabetes Information System

The association of obesity with the development of obstructive lung disease, namely asthma and/or chronic obstructive pulmonary disease, has been found to be significant in general population studies, and weig...

Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study

Breathing pattern disorders are frequently reported in uncontrolled asthma. At present, this is primarily assessed by questionnaires, which are subjective. Objective measures of breathing pattern components ma...

The role of leukotriene modifying agent treatment in neuropsychiatric events of elderly asthma patients: a nested case control study

In March 2020, the US Food and Drug Administration decided that the dangers related to neuropsychiatric events (NPEs) of montelukast, one of the leukotriene modifying agents (LTMAs), should be communicated thr...

Asthma and stroke: a narrative review

Asthma is a heterogeneous disease, usually characterized by chronic airway inflammation, bronchial reversible obstruction and hyperresponsiveness to direct or indirect stimuli. It is a severe disease causing a...

Comparison of dental caries (DMFT and DMFS indices) between asthmatic patients and control group in Iran: a meta-analysis

The association between caries index, which is diagnosed by Decayed, Missing, and Filled Teeth (DMFT), and asthma has been assessed in several studies, which yielded contradictory results. Meta-analysis is the...

ICS/formoterol in the management of asthma in the clinical practice of pulmonologists: an international survey on GINA strategy

The treatment with short-acting beta-2 agonists (SABA) alone is no longer recommended due to safety issues. Instead, the current Global Initiative for Asthma (GINA) Report recommends the use of the combination...

Sustainability of residential environmental interventions and health outcomes in the elderly

Research has documented that housing conditions can negatively impact the health of residents. Asthma has many known indoor environmental triggers including dust, pests, smoke and mold, as evidenced by the 25 ...

Non-adherence to inhaled medications among adult asthmatic patients in Ethiopia: a systematic review and meta-analysis

Medication non-adherence is one of a common problem in asthma management and it is the main factor for uncontrolled asthma. It can result in poor asthma control, which leads to decreased quality of life, incre...

The outcome of COVID-19 among the geriatric age group in African countries: protocol for a systematic review and meta-analysis

According to the World Health Organization (WHO), the outbreak of coronavirus disease in 2019 (COVID-19) has been declared as a pandemic and public health emergency that infected more than 5 million people wor...

Correction to: A comparison of biologicals in the treatment of adults with severe asthma – real-life experiences

An amendment to this paper has been published and can be accessed via the original article.

The original article was published in Asthma Research and Practice 2020 6 :2

Disease control in patients with asthma and respiratory symptoms (wheezing, cough) during sleep

The Global Initiative for Asthma ( GINA)-defined criteria for asthma control include questions about daytime symptoms, limitation of activity, nocturnal symptoms, need for reliever treatment and patients’ satisfac...

The burden, admission, and outcomes of COVID-19 among asthmatic patients in Africa: protocol for a systematic review and meta-analysis

Coronavirus disease 2019 outbreak is the first reported case in Wuhan, China in December 2019 and suddenly became a major global health concern. According to the European Centre for Disease Prevention and Cont...

The healthcare seeking behaviour of adult patients with asthma at Chitungwiza Central Hospital, Zimbabwe

Although asthma is a serious public health concern in Zimbabwe, there is lack of information regarding the decision to seek for healthcare services among patients. This study aimed to determine the health care...

Continuous versus intermittent short-acting β2-agonists nebulization as first-line therapy in hospitalized children with severe asthma exacerbation: a propensity score matching analysis

Short-acting β2-agonist (SABA) nebulization is commonly prescribed for children hospitalized with severe asthma exacerbation. Either intermittent or continuous delivery has been considered safe and efficient. ...

Patient perceived barriers to exercise and their clinical associations in difficult asthma

Exercise is recommended in guidelines for asthma management and has beneficial effects on symptom control, inflammation and lung function in patients with sub-optimally controlled asthma. Despite this, physica...

Asthma management with breath-triggered inhalers: innovation through design

Asthma affects the lives of hundred million people around the World. Despite notable progresses in disease management, asthma control remains largely insufficient worldwide, influencing patients’ wellbeing and...

A nationwide study of asthma correlates among adolescents in Saudi Arabia

Asthma is a chronic airway inflammation disease that is frequently found in children and adolescents with an increasing prevalence. Several studies are linking its presence to many lifestyle and health correla...

A comparison of biologicals in the treatment of adults with severe asthma – real-life experiences

Anti-IgE (omalizumab) and anti-IL5/IL5R (reslizumab, mepolizumab and benralizumab) treatments are available for severe allergic and eosinophilic asthma. In these patients, studies have shown beneficial effects...

The Correction to this article has been published in Asthma Research and Practice 2020 6 :10

Determinants of Acute Asthma Attack among adult asthmatic patients visiting hospitals of Tigray, Ethiopia, 2019: case control study

Acute asthma attack is one of the most common causes of visits to hospital emergency departments in all age groups of the population and accounts for the greater part of healthcare burden from the disease. Des...

Determinants of non-adherence to inhaled steroids in adult asthmatic patients on follow up in referral hospital, Ethiopia: cross-sectional study

Asthma is one of the major non-communicable diseases worldwide. The prevalence of asthma has continuously increased over the last five decades, resulting in 235 million people suffering from it. One of the mai...

Development of a framework for increasing asthma awareness in Chitungwiza, Zimbabwe

Asthma accounts for significant global morbidity and health-care costs. It is still poorly understood among health professionals and the general population. Consequently, there are significant morbidity and mo...

Epidemiology and utilization of primary health care services in Qatar by asthmatic children 5–12 years old: secondary data analysis 2016–2017

Childhood asthma is a growing clinical problem and a burden on the health care system due to repetitive visits to children’s emergency departments and frequent hospital admissions where it is poorly controlled...

Is asthma in the elderly different? Functional and clinical characteristics of asthma in individuals aged 65 years and older

The prevalence of chronic diseases in the elderly (> 65 years), including asthma, is growing, yet information available on asthma in this population is scarce.

Factors associated with exacerbations among adults with asthma according to electronic health record data

Asthma is a chronic inflammatory lung disease that affects 18.7 million U.S. adults. Electronic health records (EHRs) are a unique source of information that can be leveraged to understand factors associated w...

What is safe enough - asthma in pregnancy - a review of current literature and recommendations

Although asthma is one of the most serious diseases causing complications during pregnancy, half of the women discontinue therapy thus diminishing the control of the disease, mostly due to the inadequate educa...

Biomarkers in asthma: state of the art

Asthma is a heterogenous disease characterized by multiple phenotypes driven by different mechanisms. The implementation of precision medicine in the management of asthma requires the identification of phenoty...

Exhaled biomarkers in childhood asthma: old and new approaches

Asthma is a chronic condition usually characterized by underlying inflammation. The study of asthmatic inflammation is of the utmost importance for both diagnostic and monitoring purposes. The gold standard fo...

Assessment of predictors for acute asthma attack in asthmatic patients visiting an Ethiopian hospital: are the potential factors still a threat?

Recurrent exacerbations in patients with moderate or severe asthma are the major causes of morbidity, mortality and medical expenditure. Identifying predictors of frequent asthma attack might offer the fertile...

Effect of adjusting the combination of budesonide/formoterol on the alleviation of asthma symptoms

The combination of budesonide + formoterol (BFC) offers the advantages of dose adjustment in a single inhaler according to asthma symptoms. We analyzed the relationship between asthma symptoms in terms of peak...

Asthma Research and Practice

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Asthma: a case study, review of pathophysiology, and management strategies

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1 Medical College of Georgia, School of Nursing, Augusta, GA, USA.
PMID: 12426803
DOI: 10.1111/j.1745-7599.2002.tb00076.x

Purpose: To review the pathophysiology of asthma, present a case study, and provide management strategies for treating this common, yet complex disorder in children and adults.

Data sources: Selected clinical guidelines, clinical articles, and research studies.

Conclusions: Asthma is a chronic inflammatory airway disorder with acute exacerbations that currently affects approximately 14 million-15 million children and adults in the United States. Costs for asthma are staggering and nurse practitioners (NPs) are frequently presented with management decisions for the acute treatment and chronic management of this disorder. Disparities exist with the occurrence of asthma between race and gender. Additionally, there is an increased incidence in acute exacerbations resulting from poor long-term control and follow-up care among the socioeconomically disadvantaged.

Implications for practice: Standards of care, along with new and emerging treatment strategies, guide NPs in providing the most comprehensive care to those affected with this chronic disorder. Knowledge about the pathophysiology of asthma and correlated to the case presentation enhances understanding treatment strategies for NPs who are often faced with providing care for patients with this chronic disorder that may sometimes present in an acute exacerbation.

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Artificial intelligence techniques in asthma: a systematic review and critical appraisal of the existing literature

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Artificial intelligence (AI) when coupled with large amounts of well characterised data can yield models that are expected to facilitate clinical practice and contribute to the delivery of better care, especially in chronic diseases such as asthma.

The purpose of this paper is to review the utilisation of AI techniques in all aspects of asthma research, i.e. from asthma screening and diagnosis, to patient classification and the overall asthma management and treatment, in order to identify trends, draw conclusions and discover potential gaps in the literature.

We conducted a systematic review of the literature using PubMed and DBLP from 1988 up to 2019, yielding 425 articles; after removing duplicate and irrelevant articles, 98 were further selected for detailed review.

The resulting articles were organised in four categories, and subsequently compared based on a set of qualitative and quantitative factors. Overall, we observed an increasing adoption of AI techniques for asthma research, especially within the last decade.

AI is a scientific field that is in the spotlight, especially the last decade. In asthma there are already numerous studies; however, there are certain unmet needs that need to be further elucidated.

Artificial intelligence algorithms are able to analyse large amounts of complex data and extract meaningful patterns that can be utilised in clinical practice and contribute to the provision of better care, especially in chronic diseases such as asthma https://bit.ly/2SC6c3q

Introduction

Asthma is a common disease affecting an estimated 300 million individuals worldwide; in Europe, about 30 million children and adults less than 45 years old have asthma [ 1 ]. It is a major global health problem that imposes a substantial burden on patients, their families and the community. Asthma poses certain challenges that remain largely unmet despite the effort and the research in the respective fields, specifically the following. i) There is no unanimous and widely applicable diagnostic test for asthma, leading to significant underdiagnosis and overdiagnosis [ 2 ]. ii) The pathogenesis of asthma is based on the process of gene–environment interaction, yet its specifics remain elusive; this field is currently in the spotlight in view of the new biologic treatments for asthma. iii) Asthma phenotypes remain a controversial subject, due to the discordance in symptomatology, spirometry and response to treatment of individual patients. iv) Asthma exacerbations play a crucial role in the course and management of the disease, incurring significant increase in direct and indirect costs [ 3 ].

As in other parts of medicine, there is an increasing interest in artificial intelligence (AI) methodologies to elucidate the aforementioned unmet needs of asthma. AI refers to the software that is able to make a machine intelligent such that it performs human tasks, i.e. process, learn and respond to information gained from data. The term is often used in combination with the term “machine learning” that refers to the process followed in order to make a machine learn how to perform a specific task, and in a similar manner as a human to perform better as the experience increases. Both AI and machine learning are data-driven processes whereby the computer or the algorithm is presented with input data and the desired output and “learns” the inherent relations that lead from the input to the output. Similarly, with AI and machine learning, data mining involves the computational and programming steps in order to “mine” large amounts of complex data for meaningful patterns and consequently knowledge. Figure 1 depicts the steps of the data mining process. There are two basic phases within the data mining process: the training and the predicting phase. During the training phase, the machine learning algorithm is fed with input data based on which a model is trained that captures the relations and patterns within the data. During the training phase, the raw input data are subject to a series of preprocessing steps aiming to increase the quality of the data, identify the set of more informative features and omit potentially redundant or irrelevant information. Inherent to the training phase is the process of model evaluation where the parameters of the trained model are further fine tuned in order to procure a well-trained model. In the predicting phase new instances of unknown data are fed as input to the previously trained model and the respective labels are predicted.

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Flowchart of the data mining process.

AI/machine learning in medicine

Even though AI and machine learning exist as computer science domains for several years, they are two terms that have become radically and widely popular the last few years in a broad and non-specialised audience. This can be attributed to several reasons: their utilisation in daily digital tasks especially pertaining to smartphones ( e.g. mobile assistant, fingerprint scanner, personalised playlists, etc .), the availability of AI and machine learning models to a wider audience with more user-friendly software, the need to discover new knowledge and analyse more effectively large and complex sources of data originating from various domains.

As described previously AI and machine learning models are largely dependent on the available data, and the healthcare domain is producing vast amounts of data that need to be mined for underlying knowledge. Such large and complex datasets incorporating various sources of data, ( e.g. clinical, imaging, genomic, proteomic, etc. ) can be effectively analysed with the available AI/machine learning techniques. In the supplementary material, we provide a brief primer on AI/machine learning techniques in order to further facilitate reading of the manuscript. Imaging modalities, such as computed tomography and magnetic resonance imaging scans, used in clinical practice can be effectively analysed by machine learning algorithms [ 4 – 7 ]. Genomic data is another source of enormous and complex information that is being used increasingly in the healthcare domain. Most of these data ( e.g. single nucleotide polymorphisms, gene expression, etc .) produce large amounts of data that are impossible to comprehend; yet the systematic analysis of such data with machine learning techniques has brought about clinically meaningful knowledge for the benefit of patients [ 8 , 9 ]. The relatively recent boom of high-quality wearable sensors is also producing huge amounts of time-series data that need to be mined efficiently in order to provide clinically relevant information [ 10 , 11 ].

The distribution of data types analysed with AI algorithms in the literature has been explored in a recent review article [ 12 ] suggesting that diagnostic imaging is the most widely employed data source in healthcare-oriented applications of AI, while genomic data and electrodiagnosis constitute emerging data types that are equally appealing for analysis with AI. The authors further explored the leading diseases for which AI algorithms have been employed in the literature, with cancer research being the top field in which AI applications have been developed, followed by diseases of the nervous system as well as cardiovascular diseases [ 13 ]. In this analysis, respiratory diseases are way below, with only mediocre adoption of AI techniques.

In the present manuscript, we have systematically searched the literature for articles that employ AI or machine learning techniques in asthma, in an attempt to map the existing literature and identify gaps and areas of interest for future research. First, in the literature review section, we describe the methodological steps in order to acquire all relevant literature. Next, in the machine learning and asthma section, we present our findings from the literature review, and the articles are organised into four major categories to facilitate the critical appraisal of the existing evidence.

Literature review

We systematically searched the literature until May 18, 2019, for articles using AI or machine learning techniques in asthma research. First, we searched DBLP, which is a computer science bibliography website, using the term “asthma”. We maintained only journal articles posing no restriction regarding the year of publication. Next, we searched PubMed using the following terms: “artificial intelligence” AND asthma, “machine learning” AND asthma, “data mining” AND asthma, “decision trees” AND asthma, “neural network” AND asthma, “random forests” AND asthma, “support vector machine” AND asthma. The articles from both repositories were then merged and duplicates were removed. All articles were subsequently examined by the authors in order to exclude irrelevant ones; we also omitted articles not written in English. The aforementioned steps are shown in figure 2 , resulting eventually in 98 articles. Each of the 98 articles was then assigned to at least one out of the following four categories based on its content and purpose: 1) asthma screening and diagnosis, 2) patient classification, 3) asthma management and monitoring, and 4) asthma treatment.

Flowchart of the literature search.

In figure 3 , we present the distribution of studies using AI/machine learning techniques for asthma research, over the course of approximately 30 years, from 1988 up to 2018. As expected during the first and second decade there is minimal use of such techniques for asthma, while from 2010 we observe a considerable and progressive increase.

Distribution of articles published per year that employed artificial intelligence/machine learning techniques for asthma research.

Artificial intelligence and asthma

In the sections that follow we present the articles retrieved in an organised manner, divided into four categories based on their content and purpose. Specifically, we have split the articles into the following four major contextual categories. 1) Asthma screening and diagnosis. 2) Patient classification. 3) Asthma management and monitoring. 4) Asthma treatment.

The articles from each category are summarised in a separate table where the respective studies can be compared by a set of qualitative and quantitative criteria or characteristics. These tables (tables S3, S4 and S5) are available in the supplementary material of the article. In the sections that follow we provide an overview of the articles comprising each category. Moreover, we have selected some of the most important studies from each category and provide more information. Our aim is to capture the most representative works, focussing on the ones that have been published within the last 5 years, as this is an emerging and developing field with rapid evolution.

In order to facilitate reading of the following sections, we hereby mention some terms that are commonly used in AI/machine learning. Specifically, artificial neural network (ANN), random forest, decision tree, support vector machine (SVM), logistic regression, Bayes network, naïve Bayes, k-nearest neighbours (k-NN), self-organising maps (SOM) and hidden Markov model (HMM) constitute classification algorithms; sensitivity, specificity, accuracy), receiver operating characteristic (ROC) and area under ROC curve (AUC) are performance metrics used for the assessment of AI/machine learning algorithms. Cross validation, or its subtype called leave one out CV (LOOCV) are techniques used for AI/machine learning model validation. These terms are summarised in table 1 below. In the supplementary material we provide an exhaustive list of the abbreviations used throughout the manuscript, as well as a primer on AI/machine learning techniques.

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List of the most commonly used abbreviations in the manuscript

Asthma screening and diagnosis

This category is the most populated one and contains 48 articles aiming for the screening or diagnosis of asthma. These studies are summarised in table S3 of the supplementary material. We observe that, in terms of machine learning algorithms, the majority of the studies (20 studies) employ ANNs or variations of ANNs, especially the earlier ones. Support vector machines are used in eight studies, decision trees or random forests are utilised in 11 studies, logistic regression is used in three studies and k-nearest neighbours in two studies. The remaining studies employ other machine learning algorithms, such as HMM, fuzzy logic or naïve Bayes. Overall, we observe that a limited number of machine learning algorithms are employed in the studies contained in the category “Asthma screening and diagnosis”, i.e. ANNs, support vector machines, random forests and decision trees. It should be noted that these machine learning algorithms are described in the accompanying supplementary material, as well as some information regarding the evaluation of the reported results. Based on column “sample size”, most of the studies employ tens or hundreds of patients and there are only a few studies that have enrolled larger patient cohorts (only four studies have enrolled >1000 patients).

As expected for the purpose of asthma diagnosis and screening, primarily clinical data have been employed; specifically, these data contain information from the medical history, pattern of symptoms, pulmonary function tests, lung sounds from auscultation, etc . Clinical data are employed in 37 studies, out of which 12 explore features pertaining to lung or breath sounds. Similarly, there are studies in this category that exploit questionnaires as well as other clinical and epidemiological features in order to screen certain populations for asthma or identify patients that have a high probability of asthma. Some of the most recently published works employ genetic data (nine studies) in search of predisposing genetic traits for asthma. As for the evaluation methods, 23 studies used variations of cross-validation techniques, of which seven used LOOCV, nine studies performed a train-test split and nine studies used an independent test set. We have selected a few representative studies published within the last 5 years from the category “Asthma screening and diagnosis” that we present briefly hereafter.

O letic and B ilas [ 14 ] used a wearable sensor that recorded signals of respiratory sounds which were subsequently transferred to a smartphone. After certain signal manipulations, an HMM was utilised for respiratory sound classification, aiming primarily to detect wheezing. The resulting model yielded accuracy=94.91%, sensitivity=89.34% and specificity=96.28%. This study shows an emerging trend of smartphone employment in computationally intensive tasks such as the induction of machine learning algorithms in asthma.

A maral et al. [ 15 ] explored the contribution of forced oscillation technique (FOT) for the detection of airway obstruction, focussing specifically on patients with asthma. FOT is an oscillation-based technique that captures respiratory mechanics that can assess bronchial hyperresponsiveness in adults and children, and has been shown to be as sensitive as spirometry in detecting impairments to lung function due to smoking or exposure to occupational hazards [ 16 ]. It should be noted that FOT is a non-invasive technique that also has the advantage over conventional lung function tests that it does not require the performance of respiratory manoeuvres [ 16 ]. However, FOT should be used cautiously and as a complement to spirometry, since its interpretation and reference values remain controversial [ 17 ]. In their work A maral et al. [ 15 ] employed a series of machine learning algorithms using the FOT parameters as input in order to detect airway obstruction. The best performance was achieved by a k-NN classifier that reached AUC=0.91.

In a methodologically different approach K aur et al. [ 18 ] utilised a natural language processing (NLP) approach in order to mine health records and identify asthma diagnosis. The resulting algorithm was validated in a cohort of 427 patients and predicted asthma status with sensitivity=86%, specificity=98%, PPV=88% and NPV=98%. Several approaches exist in the literature aiming to screen for asthma based on either the health record or the patient's prescriptions.

S ingh et al. [ 19 ] measure CO 2 waveforms from capnography in order to discriminate asthmatic and non-asthmatic patients. They extracted a series of features from the capnography signals from 30 non-asthmatic and 43 asthmatic patients; after applying feature selection, the remaining features were fed to a support vector machine which performed very well for the discrimination of the two classes (accuracy=94.52%, sensitivity=97.67% and specificity=90%). Capnography refers to the non-invasive measurement of the partial pressure of CO 2 in exhaled breath expressed as the CO 2 concentration over time. Changes in the CO 2 waveform (capnogram) or the end-tidal CO 2 have been employed for disease diagnosis [ 20 ], assessment of disease severity as well as treatment response [ 21 ]. Based on the aforementioned results, the authors suggest that capnography may be a promising technique for diagnosing asthma, either alone or coupled with other features. The small dataset used in this study does not allow for proper evaluation of the proposed modality and further analyses in larger datasets are mandatory.

Another interesting work was recently published by S pathis and V lamos [ 22 ] who developed a decision support system for the diagnosis of asthma and chronic obstructive pulmonary disease (COPD). They used as input a set of clinical characteristics ( e.g. age, sex, sputum production, chest pain, smoking, etc .) as well as spirometry in order to detect asthma and COPD; the best performing algorithm in both cases was a random forest classifier that resulted in Precision of 97.7% and 80.3% for the diagnosis of COPD and asthma, respectively. It should be noted that, especially for COPD, the results are quite encouraging given the fact that the employed input features are readily available during a regular pulmonology visit, yet the small number of patients does not allow for firm conclusions.

For a similar purpose as the previous work, T opalovic et al. [ 23 ] employed spirometry and features from the patients’ clinical profile in order to classify patients in 10 different conditions or states (healthy, asthma, COPD, other obstructive, hyperventilation, interstitial lung disease, neuromuscular disorder, pulmonary vascular disorders and upper airway obstruction). Compared with the evaluation by pulmonologists that resulted in correct diagnosis in approximately 38% of the subjects, the proposed machine learning algorithm that utilised a decision tree classifier achieved 68% accuracy. The proposed algorithm performed better in the identification of spirometric patterns (obstructive, restrictive, mixed or normal) and in the most common conditions, such as COPD and asthma.

P andey et al. [ 24 ] acquired nasal brushing samples from 190 patients with asthma and healthy controls and extracted RNA; the expression of 90 genes was recorded and fed to a logistic regression classifier which achieved an impressive AUC of 0.994. Studies employing genomic data have recently emerged in the study of asthma but are gradually being used more widely, and can contribute to the pathogenesis of asthma at the molecular level. In a similar manner, F ang et al. [ 25 ] analysed gene expression data and came down to 62 genes that could serve as asthma biomarkers. Nasal brushing samples or gene expression data can often be acquired in a minimally invasive manner, nevertheless RNA extraction remains a costly technique.

Finally, the metabolome is another source of biomarkers that has recently been employed in a multitude of fields in medical research. S inha et al. [ 26 ] explored the exhaled breath condensate (EBC) from 89 asthmatic subjects and 20 healthy controls and built a random forest classifier in order to differentiate between the two groups. The resulting classifier yielded 80% sensitivity and 75% specificity. Same as before, EBC may be another promising field in the search for non-invasive asthma biomarkers; however, this method needs further standardisation prior to wider clinical application [ 27 ].

Patient classification

This category contains 31 studies that aim to classify patients into subgroups based on a series of characteristics. These subgroups refer to asthma severity, asthma phenotypes/endotypes or other classifications of patients. Table S4 of the supplementary material shows a qualitative and quantitative comparison of these studies. In this category, nine studies employed decision trees or random forests, seven studies used ANNs, three studies utilised support vector machines, four studies used logistic regression and the remaining ones employed other machine learning techniques such as k-NN, Bayes network, naïve Bayes, etc.

The sample size, as expected, varies significantly among the studies. In terms of input data, 26 studies employ clinical data as input, whereas genomic data either alone or in combination with clinical information are used in six studies, especially in the most recent publications. Variations of the cross-validation technique are primarily used (17 studies) for evaluating the proposed classifications schemes, out of which 10 studies use 10-fold cross validation and three studies employ the LOOCV method; five studies performed evaluation with an independent test set and three studies used the training–testing method.

It is noteworthy that this category “Patient classification” is not the most populated one; however, it is the category that has significant overlap with the other categories. As noted before, every study based on its content could belong in more than one of the available categories. Studies in the category “Patient classification” often belong to other categories as well. Specifically, the task of classifying patients into certain groups is often an important step in the studies even if there are other aims in the respective study.

Identifying subcategories within the broad category of “Patient classification” is not easy. Roughly, the studies in this category could be assigned into the following subcategories: i) asthma severity and ii) asthma phenotypes. Studies in the former subcategory feature a variety of inputs, such as breath/respiratory sounds, asthma control and hospitalisation frequency. Other studies explore the exacerbation severity and classify the patients according to the course of exacerbations or a set of clinical outcomes. Below we present a couple of the most recent and representative studies from the “asthma severity” subcategory.

V an V ilet et al. [ 28 ] explored the relationship between asthma control and exhaled biomarkers in a paediatric population. Specifically the authors explored the discriminatory ability of fractional nitric oxide ( F eNO ), volatile organic compounds (VOCs) and cytokines/chemokines towards identifying children with persistently controlled and uncontrolled asthma. A cohort of 96 asthmatic children was followed up for a year and different features sets were fed as input to a random forest aiming to discriminate between the two patient groups. Using solely a set of VOCs resulted in an AUC of 0.86; whereas the addition of the other two inputs did not lead to a more accurate classification.

N abi et al. [ 29 ] analysed wheeze sounds from 55 asthmatic patients in order to classify them into three severity classes: i.e. mild, moderate and severe. An ensemble classifier yielded the highest PPV of 95%, pinpointing that tracheal-related wheeze sounds were most sensitive and specific predictors of asthma severity levels.

Next, we focus on the second subcategory of the “Patient classification” category, i.e. “asthma phenotypes”. The studies in this subcategory either explore different patient classes based on a set of input features either genomic and/or clinical; therefore, the patients are clustered based on their inherent characteristics. In the same subcategory, there are studies that classify the employed patients based on their response to treatment. In the next few paragraphs, we present some of the most important and recent studies from this subcategory.

K rautenbacher et al. [ 30 ] combined a wide range of heterogeneous data, namely questionnaire, diagnostic, genotype, microarray, RT-qPCR, flow cytometry and cytokine data in order to differentiate between three patient phenotypes. The phenotypes under consideration are healthy, mild-to-moderate allergic and nonallergic. The study focussed on a paediatric population of 260 children. The most important variables for classifying childhood asthma phenotypes comprised novel identified genes, namely protein kinase N2 (PKN2), protein tyrosine kinase 2 (PTK2), and alkaline phosphatase, placental (ALPP). Similarly, F ontanella et al. [ 31 ] explored the relationship between allergic sensitisation and asthma propensity; even though the study primarily aims to serve as a diagnostic tool for asthma, pairwise interactions between immunoglobulin (Ig)E components are used to predict clinical phenotypes.

W illiams- D e V ane et al. [ 32 ] utilised a completely data driven approach in order to identify asthma subtypes. The authors employed gene expression data, clinical covariates as well as certain disease indicators and devised a multi-step decision tree aiming to identify asthma endotypes aiming to facilitate the discovery of new mechanisms underlying asthma.

W u et al. [ 33 ] explored asthma phenotypes based on patients’ response to corticosteroids, using an unsupervised multiview learning approach. The proposed work explored the contribution of 100 clinical, physiological, inflammatory and demographic variables and was validated in a set of 346 adult asthmatic patients. The authors reported that patients with late-onset asthma, low lung function and high baseline eosinophilia showed the best corticosteroid responsiveness, whereas the poorest responsiveness was reported in young, obese females with severe airflow limitation and little eosinophilic inflammation. A similar approach is presented in the paper by R oss et al. [ 34 ], in which the authors proposed an machine learning algorithm in order to identify paediatric asthma phenotypes based on the patients’ response to controller medication. Bronchodilator response and serum eosinophils were found to be the most predictive features of asthma control in the paediatric population under consideration.

Asthma management and monitoring

This category is also quite populated, featuring 40 studies that primarily deal with asthma exacerbations of asthma flare-ups. Table S5 provides an overview of these studies. Regarding machine learning algorithms, 12 studies employed decision trees, random forests or variations of these algorithms; 11 studies utilised ANNs, four studies used support vector machines, three studies employed Bayes network/naïve Bayes algorithms and three used logistic regression.

Interestingly, in this category there are 11 studies employing more than 1000 records, five of which analyse environmental data ( e.g. air pollution). There are only three studies incorporating genomic data in this category, consequently the majority of the studies encompass either clinical data or environmental/meteorological data or their combination (seven studies). Cross validation was also the main method used for evaluation as reported in 21 studies, of which two used LOOCV; training–testing split was used in eight studies and only four studies performed evaluation on an independent testing set. In this category, we can identify two broad subcategories, namely asthma exacerbation prediction and asthma exacerbation management. The former category refers to models aiming to early identify an exacerbation while the latter contains models that predict the course of the exacerbation and the subsequent management.

K hasha et al. [ 35 ] utilised expert knowledge in an ensemble classifier in order to detect asthma control level yielding an overall 91.66% accuracy. The algorithm was developed with data collected from 96 asthmatic patients followed-up for a 9-month period. According to the authors, the aim of the proposed model is to serve as a real-time preventive system for asthma control.

In a similar manner, H osseini et al. [ 36 ] proposed a platform for real-time assessment of asthma attack risk, based on a set of sensors capturing physiological and environmental data. The collected data are pipelined through a smartphone for analysis to an random forest classifier which identified asthma attacks with an overall accuracy of 80.1%. In another work by H uffaker et al. [ 37 ], nocturnal recordings of physiological data were obtained from a contactless bed sensor and fed to a random forest model which yielded 87.4% accuracy, 47.2% sensitivity and 96.3% specificity, towards detecting asthma exacerbations. Similarly, for the prediction of asthma exacerbations, F inkelstein et al. [ 38 ] utilised telemonitoring data which were analysed by an adaptive Bayesian network resulting in perfect classification ( i.e. 100% accuracy, 100% sensitivity and 100% specificity).

In a methodologically different approach, R am et al. [ 39 ] mined a multitude of data coming from Google search interests, Twitter data and environmental data in order to early predict asthma-related emergency department visits; the resulting model yielded 70% precision. Such systems could potentially serve as a means of public health surveillance in order to enhance proactiveness and efficiency of the emergency department. For the same purpose, K hatri et al. [ 40 ] developed an ANN model in order to predict peak demand days at the emergency department for chronic respiratory diseases.

Another important issue regarding an asthma exacerbation is the decision whether hospitalisation is needed or not. P atel et al. [ 41 ] proposed an algorithm based on gradient-boosting machines that quantifies the overall risk, and consequently the need for hospitalisation is decided. The algorithm yielded an AUC of 0.84 and the following features were found to be more informative: vital signs, acuity, age, weight, socioeconomic status and weather-related features.

Asthma treatment

The last category contains studies utilising machine learning algorithms for the overall asthma treatment. It is notable that this category contains only one article by R oss et al. [ 34 ] which has also been mentioned in previous categories. The authors aimed to identify asthma phenotypes based on their response to treatment and, thus, fine tune their patients’ treatment. We have intentionally included this hardly populated category in order to highlight the gap in literature in terms of machine learning algorithms used for asthma treatment.

Asthma research is gradually picking up on AI/machine learning techniques, following the overall trend of AI/machine learning adoption in healthcare-related studies. Specifically, in figure 3 (Introduction section) we presented the distribution of studies using AI/machine learning techniques for asthma research, over the course of 30 years, i.e. from 1988 to 2018. During the first and second decade, there is minimal employment of such techniques for asthma, while from 2010, we observe a considerable and progressive increase. A similar trend has been observed regarding the utilisation of AI/machine learning techniques in other healthcare domains, e.g. cancer research [ 13 ], whereas in the latter case the number of articles published in each year is almost ten times bigger.

In the “Asthma screening and diagnosis” category we observe that the vast majority of studies have utilised relatively small numbers of patients. Only studies employing questionnaires contain richer patient sets. This observation poses an important question regarding the validity and robustness of the reported results.

As for the “Patient classification” section, the studies employ relatively larger patient cohorts; nevertheless, the reported evaluation metrics are encouraging but not quite perfect yet. Therefore, more data and further analyses are needed in order to obtain more definite answers.

The “Asthma management and monitoring” category is quite heterogeneous in terms of the employed population sizes and the accuracy of the reported results. Specifically, we observe from the respective table S5 that the number of patients or records used in the studies vary significantly from just a couple up to thousands. This has to do with several factors: the type and cost of employed data (genomic, metabolomic, clinical, etc. ), the focus on specific populations and the scarcity of patients in each patient set, the quality and completeness of gathered information.

It is noteworthy that the last category “Asthma treatment” contains one study, denoting the lack of research currently in this prospect with the employment of machine learning techniques. This can be attributed to the fact that treatment is primarily directed by published guidelines. However, it should be noted that in the field of asthma treatment there is considerable activity in the literature, especially with respect to biologics. According to our literature research, there are currently no studies that exploit machine learning algorithms focussed on the exploration of biologic treatments of asthma. Nevertheless, as the number of approved biologics increases, as also the number of eligible patients, such studies are expected to emerge. The profiles of super-responders to specific biologics currently remain largely elusive, and AI/machine learning could facilitate the discovery of such complex profiles. There is also an increasing interest in the reviewed literature towards severe asthma encompassing machine learning techniques, following the overall trend in asthma research.

Only a small fraction of the studies in the current review utilise large patient cohorts, and even fewer analyse complex data, where AI could be more useful; therefore, AI in asthma research still remains underused, or at least not exploited to its full potential. Furthermore, we observe that in terms of the quantitative and qualitative features we have compared the included studies, there are some similar patterns among them. Specifically, there is considerable utilisation of ANNs and decision trees; whereas, in the most recent studies, random forests are being increasingly used. This trend is to be expected, since ANNs were widely employed in several medical fields due to their superior results. Decision trees are also quite common in health-related studies because they provide reasoning which is often regarded as cornerstone. It should be noted that there is a significant number of studies ( i.e. 21) focussing on paediatric populations; whereas, the rest include adults, denoting the burden based on age.

It should be highlighted that AI/machine learning techniques are particularly useful for the analysis of large complex datasets, encompassing heterogeneous sources of information. Asthma poses an ideal target for AI/machine learning utilisation, as it is a chronic disease with patients being followed-up for several years and its perturbations can be detected from the cellular level, to the organ level and up to the organism level as a whole. Moreover, environmental factors play a key role in asthma pathogenesis and natural history; therefore, large scale environmental and meteorological data need to be analysed in a complementary manner. Ideally, a theoretical asthma study should capture genomic, metabolomic, clinical and environmental data, in several consecutive time-slices from large and diverse patient cohorts, thus framing all potential asthma effects ranging in scale and time. The resulting highly complex and heterogeneous dataset should be mined with AI techniques aiming to gain new knowledge regarding asthma diagnosis, classification and treatment.

Conclusions

AI/machine learning is undeniably a scientific field that is in the spotlight, especially in the last decade; its utilisation in medical applications is on the rise, and subsequently there is growing interest in the respiratory field and asthma research, as denoted by the literature review conducted in the current work. Further progress is to be expected in respiratory research as more advanced machine learning techniques are gradually used, e.g. deep learning. Another issue that affects the combined research of asthma with AI/machine learning techniques is the fruitful communication between computer scientists and clinicians for the identification of the appropriate research questions. In order to deal with those questions more effectively large amounts of high quality and well characterised populations are needed. Finally, there is an unmet need in the identification of treatment responders to different therapeutic approaches, including the selection of an appropriate biologic treatment in severe asthma by predicting a patient's response based on phenotypic and endotypic characteristics. Artificial intelligence is here to stay in medicine; however, there are certain open issues in asthma that need to be further elucidated.

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Conflict of interest: K.P. Exarchos has nothing to disclose.

Conflict of interest: M. Beltsiou has nothing to disclose.

Conflict of interest: C-A. Votti has nothing to disclose.

Conflict of interest: K. Kostikas reports grants, personal fees and non-financial support from AstraZeneca, Boehringer Ingelheim, Chiesi, ELPEN, GSK, Menarini and Novartis, grants from NuvoAir, personal fees from Sanofi, outside the submitted work; and was an employee and shareholder of Novartis Pharma AG until October 2018.

Received March 2, 2020.
Accepted April 29, 2020.
Copyright ©ERS 2020
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Published Date: 4 September 2023

Sputum Neurturin Levels in Adult Asthmatic Subjects

Sato S, Suzuki Y, Kikuchi M, Rikimaru M, Saito J, Shibata Y

Journal of Asthma and Allergy 2023 , 16:889-901

Published Date: 31 August 2023

Effect of Biologic Therapies on Airway Hyperresponsiveness and Allergic Response: A Systematic Literature Review

Spahn JD, Brightling CE, O’Byrne PM, Simpson LJ, Molfino NA, Ambrose CS, Martin N, Hallstrand TS

Journal of Asthma and Allergy 2023 , 16:755-774

Published Date: 21 July 2023

Validation of the Arabic Version of the European Community Respiratory Health Survey Screening Questionnaire

AlShareef SM

Journal of Asthma and Allergy 2023 , 16:735-742

Published Date: 20 July 2023

Budget Impact Analysis of Single-Inhaler Fluticasone Furoate/Umeclidinium/Vilanterol in Patients with Asthma in the Dubai Academic Healthcare Corporation

Hamouda M, Farghaly M, Al Dallal S

ClinicoEconomics and Outcomes Research 2023 , 15:549-558

Published Date: 13 July 2023

Percent Recovery Index Predicts Poor Asthma Control and Exacerbation in Adults

Kuang L, Ren C, Liao X, Zhang X, Zhou X

Journal of Asthma and Allergy 2023 , 16:711-722

Exploration and Validation of Potential Biomarkers and Therapeutic Targets in Ferroptosis of Asthma

Xing Y, Feng L, Dong Y, Li Y, Zhang L, Wu Q, Huo R, Dong Y, Tian X, Tian X

Journal of Asthma and Allergy 2023 , 16:689-710

Published Date: 12 July 2023

Can Pharmacists’ Counseling Improve the Use of Inhalers and Quality of Life? A Prospective “Pre” and “Post” Education Analysis in Mardan, Pakistan

Gul S, Rehman IU, Goh KW, Ali Z, Rahman AU, Khalil A, Shah I, Khan TM, Ming LC

Journal of Asthma and Allergy 2023 , 16:679-687

Published Date: 6 July 2023

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Asthma Essay With Conclusions

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173 Asthma Essay Topic Ideas & Examples

🏆 best asthma topic ideas & essay examples, 💡 interesting topics to write about asthma, 📑 good research topics about asthma, 📌 simple & easy asthma essay titles, 👍 good essay topics on asthma, ❓ research questions about asthma.

SOAP Note for an Asthmatic Patient Today, asthma is known as one of the most common respiratory diseases in the United States, as well as in the whole world.
Application: Asthma The features of the air passage include the bronchi, alveoli and the bronchioles. The pathophysiology of chronic and acute asthma exacerbation describes the process and stages that lead to airway obstruction.
Asthma Treatment Algorithm for Patients Complete the blanks in the following table to create an algorithm for asthma care using your textbook as well as GINA guidelines.
Asthma Exacerbation in Pregnancy The patient has a history of childhood asthma diagnosis, and she is presently exhibiting typical asthma symptoms like wheezing and a nonproductive cough.
Asthma: Epidemiological Analysis and Care Plan Asthma has a variety of symptoms and pathogenesis, including acute, subacute, or chronic inflammation of the airways, intermittent blockage of airflow, and hyperresponsiveness of the bronchi.
Asthma Diagnosis in Pregnant Women It may be essential to modify the type and dose of medication to compensate for the alterations in the female’s metabolism and the severity of her health condition.
Healthy Lifestyle Interventions in Comorbid Asthma and Diabetes In most research, the weight loss in cases of comorbid asthma and obesity is reached through a combination of dietary interventions and physical exercise programs.
Clinical Case of Asthma in African American Boy By combining the use of corticosteroids and exercises into the treatment plan, as well as educating the patient and his parents about the prevention and management of asthma attacks, a healthcare practitioner will be able […]
Asthma From a Clinic Perspective And the prevalence of asthma in the European Union is 9. In UK and Ireland experience some of the greatest rates of asthma in the globe.
Corticosteroids and Inhalants in Asthma As well as the causes of fatigue and physiological events during an asthma attack, and how the body compensates for an increase in CO2, with a focus on the effects of hypercapnia on the central […]
The Treatment Modalities of Asthma However, in order to limit susceptibility to the triggers, the patient is advised to take long-term asthma medications on a daily basis.
Asthma Diagnostics and Treatment According to the Asthma and Allergy Foundation of America, some of the most common symptoms of asthma include cough, wheezing, shortness of breath, chest tightness, and fainting.
Asthma: Pathophysiology, Symptoms, and Manifestations The primary organ affected by asthma is the lungs, as the disease is caused by airway narrowing and the inability to breathe.
Asthma: Description, Diagnosis and Treatment First of all, before discussing measures to prevent an increase in the case of the disease, it is necessary to understand the nature of the disease.
Inflammation’s Role in Asthma Development This work is written in order to study the role of inflammation plays in the development of asthma on the basis of research papers.
The Use of Tezspire: The Management of Asthma The brochure describes the use of Tezspire, which is a drug used for the management of asthma. The brochure’s target audience is patients with a long history of asthma and their family and caregivers.
Asthma Treatment in Pediatric Patients: Spacer vs. Conventional Inhaler Computers and the Internet connection have become available to a considerable portion of the population, which equally serves as a facilitator of the new solution implementation.
Physical Assessment Report for an 18-Years-Old Asthma Patient The boy and his family suspect that he is suffering frequent asthma attacks due to allergies to cold and dust, however none of his members of the family suffer from asthma.
Asthma: Pathophysiology, Etiology, Diagnosis, and Complications The pathobiology of asthma remains greatly indeterminate, and its pathophysiology involves abnormalities of the respiratory system organs, including the lungs and the bronchial tree.
Use of Scientific Method in Asthma and Allergic Reactions Study As in the case of asthma and allergic reactions investigations, descriptive studies can be used to describe the nature of the relationship between asthma and asthma attack, therefore explaining the cause and effect.
COVID-19 Susceptibility in Bronchial Asthma by Green et al. The research reflected in the article aims to trace the susceptibility of patients with bronchial asthma to coronavirus disease. It is noted that the receptors that respond to those occurring in the environment are the […]
Exercise-Induced Asthma in Children The onset of an EIA attack follows a constriction of the airways of the patient after physical exercise. When water shifts from the cells of the epithelium to the airway surface, it causes a release […]
Child Asthma Emergency Department Visits: Plan for the Reduction The population of Central Harlem will be the target of this intervention that aims to decrease the rate of children’s asthma-related ED visits.
The Child Asthma Emergency Department Visits The program makes it easy for medical caregivers to carry accurate assessments to pediatric patients. The program is easily scalable, and it is also sustainable, making 5A’s the best solution to Child Asthma Emergency Department […]
Asthma Among Children of Color in New York City On the other hand, the conditioning of the matter to a particular scope hinders the determination of a rational scientific solution to the core issue.
Asthma in Relation to Inability to Breathe: A Case Study The shortness of breath is known to be a primary cause of Asthma, whereas the asthmatic state of an individual also has the capabilities of influencing shortness of breath as a result of the lung […]
Asthma Treatment Options, Long-Term Control, and Complications Speaking of the patient profile, the first aspects that should be mentioned are the peculiarities of asthma disease history and other health conditions that might affect the treatment pattern.
Occupational Asthma: Case Discussion The primary diagnosis is occupational asthma; the causative agents of the indicated type of the disease are located directly at the person’s workplace.
The Relationship Between Vitamin D Deficiency and Asthma Disease in Children The reaction of the host on the respiratory infections is closely correlated with the deficiency of the vitamin D [1]. This is because of the suggestion that providing vitamin D supplements to patients with low […]
Asthma: Culture and Disease Analysis The cause of this condition is thought to be the narrowing of the person’s airways. This, as the experts explain, is a result of the inflammation of the airways in the lungs.
Relationship Between Asthma and the Body Mass Index The optimal design of the study is the use of questionnaires, since the nature of the research requires the consent of individual respondents in form of writing.
The Connection Between Asthma and Dust Emissions This is attributed to an increased rise of annual sandstorms and continued constructions that create a huge amount of dust in the air.
Prevalence of Asthma Due to Climatic Conditions Newhouse and Levetin also conducted a study to find the correlation between the airborne fungal spores, the concentration of pollen, meteorological factors and other pollutants, and the occurrence of rhinitis and asthma.
Helping African American Children Self-Manage Asthma The purpose of this critique is to analyze the weaknesses of the study. The title of the report Helping African American Children Self-Manage Asthma: The Importance of Self-Efficacy adequately identified the population of interest, namely […]
Asthma Among the Japanese Population In a report by Nakazawa in which the author sought to determine the trend of asthma mortality among the Japanese population, emotional stress and fatigue emerged as the leading factors for the causation of asthma.
Informed Consent – Ellen Roche, Asthma Study People interested in taking part in research trials have the right to know risks, benefits, procedures, the aim of the study, and protection of identity. This violation of subjects’ right led to the formation of […]
Asthma Prevalence: Sampling and Confidence Intervals In the study which was carried out in United States in 2009 amongst the children and adults to show the prevalence of Asthma, a sample of 38,815 and confidence interval of 95% was used.
Osteopathic Manipulation in Patients With Chronic Asthma This article seeks to criticise the application of osteopathic manipulation in the treatment of asthma patients. The focus is on the intervention of osteopathic manipulation therapy in restoring normal functioning and compliance to the thoracic […]
5-Year-Old With Asthma: Developmental Milestones & Care According to his mother, he also regularly grinds his teeth at night.G.J.was delivered normally and the mother had no complications. He could listen to instructions and get whatever he is being asked by his mother.
Asthma Respiratory Disorder Treatment Asthma etiology is the classification of various risk factors responsible for causing asthma in children and adults. Asthma etiology is the scientific classification of risk factors that cause Asthma in children and adult.
Childhood Bronchial Asthma: Process & Outcome Measures The evidence that is used to support the adoption of this measure is the guideline on clinical practice, as well as the procedure of formal consensus.
Biological Basis of Asthma and Allergic Disease The immunological response in asthmatic people fails in the regulation of the production of the Th2 cells and the anti-inflammatory cells.
Asthma and Medications: The Ethical Dilemma in Treating Children One of the major causes of dilemma, however, is the inability to manage and treat the condition in children under the age of 7 years due to ethical dilemma.
Understanding Asthma in the Elderly: Triggers, Treatment, and Challenges The main objective of the given paper is to analyze the reasons of emergence of asthma among the elderly population, as well as research peculiarities of this group’s reaction to this condition as compared to […]
Exercise-Related Asthma in the 21st Century The study has also reported that almost 48 % of parents recognize the fact that children suffering from asthma have higher probability of the emergence of the typical symptoms of IEB.
The Nature and Control of Non-Communicable Disease – Asthma Asthma is caused due to the inflammation of the airways which in turn induces cough, wheezing, breathlessness and a feeling of tightness in the chest.
Asthma in School Going Youth: Effects and Management The control and prevention of adverse effects of asthma are goals of managing asthma as stated in the National Asthma Education and Preventive Program asthma treatment guidelines.
Asthma in the African American Community The paper will also highlight the effects that the treatment options used by African Americans have on the prevalence of the disease.
Asthma Definition and Its Diagnostics The geographical area plays a major role in the distribution of the prevalence of asthma and its predisposing factors. There is scientific evidence that the presence of a history of asthma in parents is a […]
Foot Orthosis, Asthma & Benign Tumor It is a chronic inflammatory disorder of the airways, associated with the following symptoms: variable airflow obstruction and enhanced bronchial responsiveness to a variety of irritants.
Asthma in School Children in Saudi Arabia The purpose of this paper is to review the current literature on asthmatic disease in Saudi Arabia to accurately determine the epidemiology nature of the condition through community assessment for purposes of compiling a health […]
Usefulness of Acupuncture in Asthma Treatment The case for the effectiveness of acupuncture in the treatment of asthma is to be further supported by more research studies, since current and past research has been affected by a number of limitations or […]
Hypertension, Asthma and Glaucoma The assignment of duties is also a difficult task since the victim is forgetful and disoriented, which in this case may lead to delays or failures within the working system.
The Management of Asthma According to the Australian Bureau of Statistics, the country has the highest prevalence of Asthma in the world. Quick-relief medications are used to manage symptoms that come with acute attacks of asthma-like coughing, tightening of […]
Treatment of Asthma in Australia The rapid-acting treatments are taken to quicken the process of reversing acute asthmatic attacks by causing the relaxation of the smooth muscles of the bronchial system. These preventers reduce the sensitivity of airways hence swelling […]
The Asthma and Emphysema Analysis According to Kinsella and others, etiology of emphysema is often associated with smocking, and this led to the hypothesis that emphysema develops with age whereas asthma is mostly prevalent in children.
Asthma: Causes and Treatment Effects of asthma are more pronounced mostly at night and early in the morning and this results in lack of sleep.
Acute Asthma: Home and Community-Based Care For Patients It refers to the continuum of care extended to patients from the health facility to the community and homes. An asthma attack is fatal and patients should be encouraged to perform self-administration of medication.
How Emotions Spark Asthma Attack Although stress and emotions are known to start in a patient’s mind, asthma in itself is a physical disease that affects the patient’s lungs, and stress can create strong physiological reactions which may lead to […]
Asthma Is a Chronic Inflammatory Disorder Hence the main purpose of the study is to investigate the association of smoking and secondhand smoke with level of asthma control, severity, and quality of life among adult asthmatics.
Asthma: Leading Chronic Illness Among Children in the US Ample communication was to be provided to the family, Head Start personnel and the Child’s physician in relation to the asthma. A great reduction was seen in the asthma symptoms and emergency.
Dealing With Asthma: Controversial Methods Because of the enormous speed of the illness spread, dealing with asthma is becoming a burning issue of the modern medicine. This is due to the fact that the muscles of the broche lack the […]
Social Determinants of Health: Asthma Among Old People in Ballarat On the other hand, Melbourne is the capital city of the State of Victoria with a population of 4 million people, making it the second most populated city in Australia. This is a great challenge […]
Asthma Investigation: Symptoms and Treatment In patients with asthma, the condition causes the inflammation of air passages that is followed by the significant narrowing of airways.
Severe Asthma: The Alair Bronchial Thermoplasty System The article focuses on asthma and the treatment that could alleviate the condition. Most of asthma patients are used to having an inhaler with them and this way, there is not much new technology, except […]
Asthma in Pediatric and Occupational Therapy Treatment The flow peak is more than 80% of the child’s personal best, and less than 30% variability in the day-to-day flow of the peak measurements.
Public & Community Health: Asthma in Staten Island There is borough of Bronx, which is considered to be the poorest, and the case with it has been stated here that asthma is the fate of the residents.
Clinical Guidelines: Report on Asthma Guideline The guideline illustrates diagnostic procedures for assessment of severity and control of asthma based on presence of airway hypersensitiveness, reversibility of airflow, detailed medical history, respiratory tract, skin and chest examinations, spirometry to assess obstruction, […]
Clinical Management of Complex Cases in Dentistry: Case of Hypertension With Asthma Understanding the role of various drug interactions and the effect of various drugs on the medical conditions of the patients is of valuable assistance.
Health, Culture, and Identity as Asthma Treatment Factors She is the guardian of Lanesha and, despite raising another grandson and caring for her elderly mother, she is responsible for the health of the girl.
The Anti-Inflammatory Role of IL-26 in Uncontrolled Asthma Research findings suggest that the suppression of IL-26 secretion in the lungs would alleviate the anti-inflammatory response associated with uncontrolled asthma.
Nursing Informatics. Asthma: Health Literacy In the United States of America, bronchial asthma is one of the most common chronic diseases in children with the prevalence rate ranging from 6% to 9%.
Asthma Pathophysiology and Genetic Predisposition The pathophysiology of this disorder involves one’s response to an antigen and a subsequent reaction of the body in the form of inflammation, bronchospasm, and airway obstruction.
Asthma: Pathopharmacological Foundations for Advanced Nursing Practice Because of the high prevalence of asthma in the USA, mortality and morbidity rates in the country are also excessive. Asthma is one of the most common diseases in the USA, with high prevalence and […]
Asthma as Community Health Issue in the Bronx The rate of people, especially children, with asthma in this area is among the highest ones in the city. The issue of asthma in New York and the Bronx, in particular, is connected to multiple […]
Environmental Factors of Asthma in Abu Dhabi City A countrywide evaluation of the demises related to environmental pollution that takes a significant role in the rising cases of asthma shows UAE as the most affected nations since the discovery of oil in 1958 […]
Occupational Asthma: Michelle’s Case The first test is not prohibitively expensive, and the patient should be able to afford it if she can pay for the medications.
Asthma Patient’s Examination and Care Plan HPI: Being discharged from the facility ten weeks ago, the patient reports having shortness of breath, severe wheezing, and coughing. To control symptoms, the patient takes HTCZ and Enalapril.
Obstructive Pulmonary Disease-Asthma Overlap The purpose of the research was to expand the current knowledge of the overlap syndrome in order to determine its prevalence and risk factors.
Chronic Asthma and Acute Asthma Exacerbation The consequences of the smooth muscles’ tightening can be aggravated by the thickening of the bronchial wall due to acute edema, cellular infiltration, and remodeling of the airways chronic hyperplasia of smooth muscles, vessels, and […]
Asthma and Stepwise Management The stepwise approach to asthma treatment and management is a six-step approach, according to which the number and the dose of medications and frequency of management are increased as necessary when symptoms persist and then […]
Asthma, Its Diagnostics, Treatment and Prevention Hippocrates was the one who labeled the disease as asthma, a Greek word that was used to denote the idea of “wind or to blow”, perhaps an attempt to describe the wheezing sound produced by […]
Asthma: Evidence-Based Pharmacological Treatment For instance, in children under 6, the development of the disease is typically preceded by the asthma-like symptoms that manifest themselves roughly at the age of three.
The Evaluation of Evidence Linking Asthma With Occupation Overall, the results of this study supported the initial argument of the authors in regard to the need for frequent updates and modifications of JEMs in order for them to reflect the most relevant and […]
Pregnant Woman’s Asthma Case The case mentions the decreased effectiveness of the fluticasone MDI that she uses which can also be a clue to her condition. Her patterns of MDI use in the last two months and the bronchospasm […]
Asthma: Causes and Mechanisms The enlargement of the dense oesinophilic line near the bronchus/airways causes the individual to wheeze and gasp for air. The drugs are mainly used in the rapid opening of the bronchus to enable airflow into […]
Healthcare: Childhood Asthma and the Risk Factors in Australia From the findings presented above, it is evident that childhood asthma remains a considerable burden in Australia due to socioeconomic, geographic, and health-related issues such as deprived neighbourhoods, decreasing sun exposure and increasing latitude, and […]
Intubation and Mechanical Ventilation of the Asthmatic Patient in Respiratory The title of the article gives a clear idea of the research question to be investigated. The authors have detailed the processes of intubation and mechanical ventilation in patients with acute asthma.
Asthma Environmental Causes This essay discusses the measures that can be taken to mitigate environmental causes of asthma. In the US, the government has developed a comprehensive strategy to mitigate environmental causes of asthmatic conditions in children.
Asthma’s Diagnosis and Treatment The complete occlusion of the airway can lead to growth of a distal at the atelectasis in the lung parenchyma. The level of AHR is connected to the signs of asthma and the urgency of […]
The Effects Of Asthma On Pregnant African Americans
Urban Children and Asthma Care Barriers
Asthma: Asthma and Nocturnal Asthma
The Health Problem of Asthma in the United States of America
Asthma: Chronic Inflamatory Obstructive Lung Disease
Asthma and Food-Allergy Reactions
Asthma And Exercise Asthmatic Asthmatics Breathing
Automobile Emissions, Co And Asthma
Asthma Control and Treatment in Racial and Ethnic Minorities
Asthma Is The Most Common Chronic Disease Of The Airways
Inflammatory Mediators Of Asthma And Histamines Biology
The Impact of Asthma on the Respiratory System, Its Causes, and Treatment
How Asthma Affects The Airway And Lungs
Diet and Nutrition for Asthma in a Child
Urban Asthma And The Neighborhood Environment
Asthma And Its Pathophysiological Structure
The Effects of Medication on the Increased Performance of Asthma Patients
What Parents Need To Know About Asthma
Employment Behaviors of Mothers Who have a Child with Asthma
The Genetic and Environmental Components of Asthma
The Influence of Asthma on the Lives of Students
Children’s Elevated Risk of Asthma in Unmarried Families: Underlying Structural and Behavioral Mechanisms
The Effects Of Environmental Tobacco Smoke Among Children With Asthma
The Effects Of Air Pollution On Children ‘s Asthma Emergency
Is Improper Use Of The Inhaler Related To Poor Asthma Control
Asthma Symptoms, Diagnosis, Management & Treatment
Limitations From Suffering Chronic Asthma
Causes And Effect Of Allergies And Asthma
Describe The Main Limitations Suffered By Those With Chronic Asthma
The Symptoms, Causes and Diagnosis of Asthma
Negligent: Asthma and Nursing Interventions
The Signs, Causes and What Triggers Asthma
The Routine Care for Patients with Coronary Heart Disease, Asthma, Stroke, Irritable Bowel Syndrome, Urinary Tract Infections, Diabetes, and Cervical Cancer
The Role Of Nurse Management Asthma And School Health Program
The Scope of Asthma in the General Population and on the Health Care System
The Most Effective Treatment for an Asthma Exacerbation
Pathophysiology Of Chronic Asthma And Acute Asthma
The Use Of Vitamin D Asthmatic Children Effectiveness Of Vitamin Supplements In Childhood Asthma
The Ways in Which the Symptoms of Asthma Can Be Reduced
Measures to Minimize Environmental Causes of Asthma
Inner City Adult Asthma Patients and Risk Factors
Raising Awareness to Prevent the Rise of Asthma
Planning and Intervention in the Disease Process of Childhood Asthma
The Anatomy And Physiology Of Respiratory System And The Diagnosis Of Asthma
The Causes and Effects of Asthma Sufferers
The Application of Corticosteroids in the Management of Bronchial Asthma
Salbutamol: History of Development in Asthma Drug Compounds
Sensitization To Plant Food Allergens In Patients With Asthma
The Diagnosis and Treatment of Otitis Media and Asthma
The Discrepancy between Asthma Cases in Minority and White Communities
The Chronic Illness in Children Known as Asthma
Does Childhood Asthma Improve With Age?
What Are the First Warning Signs of Asthma?
Which Child Is at Greatest Risk for Asthma?
What Is the Genetic Predisposition of Asthma?
Can Occupational Therapy Help With Asthma?
How to Ventilate Obstructive and Asthmatic Patients?
What Is a Risk Factor Associated With Childhood Asthma?
What Type of Approach Is Used in Asthma Management?
What Is the Difference Between Asthma and Acute Asthma?
What Are the Pharmacological Treatment of Asthma?
How Is Asthma Diagnosed?
Can Asthma During Pregnancy Affect Baby?
What Are the Three Mechanisms Involved in Asthma?
How Does Genetics and Environment Affect Asthma?
How Long Does It Take To Recover From Asthma Exacerbation?
What Factors Influence the Development of Asthma?
What Is the Physiological Cause of Asthma?
What Are the Statistics on Asthma in Australia?
What Is the Most Serious Type of Asthma?
What Ethnic Group Is Especially Likely to Have Childhood Asthma?
What Is a Nursing Care Plan of an Asthmatic Patient?
Does Asthma Cause Smooth Muscle Hypertrophy?
Should People With Asthma Use a Humidifier?
What Is Mechanical Ventilation Asthma?
What Is the Most Common Allergen to Trigger Asthma?
What Is the Main Physiological Cause of Asthma?
What Percent of Asthma Is Caused by Smoking?
How Long Does the Average Person With Asthma Live?
Which Drug Is Safe for Asthma in Pregnancy?
How Many People With Asthma Still Smoke?
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Published: 17 June 2020

Improving primary care management of asthma: do we know what really works?

Monica J. Fletcher 1 ,
Ioanna Tsiligianni 2 ,
Janwillem W. H. Kocks ORCID: orcid.org/0000-0002-2760-0693 3 , 4 , 5 ,
Andrew Cave 6 ,
Chi Chunhua 7 ,
Jaime Correia de Sousa ORCID: orcid.org/0000-0001-6459-7908 8 , 9 ,
Miguel Román-Rodríguez 10 ,
Mike Thomas ORCID: orcid.org/0000-0001-5939-1155 11 ,
Peter Kardos ORCID: orcid.org/0000-0002-4725-4820 12 ,
Carol Stonham 13 ,
Ee Ming Khoo ORCID: orcid.org/0000-0003-3191-1264 14 ,
David Leather 15 &
Thys van der Molen 16

npj Primary Care Respiratory Medicine volume 30 , Article number: 29 ( 2020 ) Cite this article

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Health policy

Asthma imposes a substantial burden on individuals and societies. Patients with asthma need high-quality primary care management; however, evidence suggests the quality of this care can be highly variable. Here we identify and report factors contributing to high-quality management. Twelve primary care global asthma experts, representing nine countries, identified key factors. A literature review (past 10 years) was performed to validate or refute the expert viewpoint. Key driving factors identified were: policy, clinical guidelines, rewards for performance, practice organisation and workforce. Further analysis established the relevant factor components. Review evidence supported the validity of each driver; however, impact on patient outcomes was uncertain. Single interventions (e.g. healthcare practitioner education) showed little effect; interventions driven by national policy (e.g. incentive schemes and teamworking) were more effective. The panel’s opinion, supported by literature review, concluded that multiple primary care interventions offer greater benefit than any single intervention in asthma management.

Implementation of a primary care asthma management quality improvement programme across 68 general practice sites

Bringing asthma care into the twenty-first century

A multinational observational study identifying primary care patients at risk of overestimation of asthma control

Introduction.

Asthma is a common chronic condition that is estimated to affect 339 million people worldwide 1 , 2 . Despite major advances in asthma treatment and the availability of both global 2 and national guidance, asthma continues to cause a substantial burden in terms of both direct and indirect costs 1 . In 2016, estimated worldwide asthma deaths were 420,000 1 and although there have been falls in some countries over the last decade, significant numbers of avoidable deaths still occur 3 . Mortality rates vary widely, with low- and middle-income countries faring worse 4 . For example, Uganda’s reported mortality rate is almost 50% higher 5 than that reported globally (0.19/100,000) 6 , although inter-country comparisons using different data sources and epidemiological methodologies have limitations. The World Health Organisation (WHO) has a global ambition for universal healthcare coverage by 2030 as millions of people worldwide do not have accessible affordable medical care 7 . The WHO moreover recognises that health systems with strong primary care have the utmost potential to deliver improved health outcomes, greater efficiency and high-quality care 7 . Perversely the availability of good quality primary and social care tends to vary inversely, those having the greatest needs being least likely to receive it 8 .

In addition to the issues of access and the quality of care, both under- and over-diagnosis of asthma is common in all healthcare settings, but the issue is of particular concern in primary care, where most initial diagnoses are made 9 , 10 .

For people with asthma, high-quality, local and accessible primary care could be a solution to poor control 11 . Our aim was to identify the factors that experts believe enable the delivery of high-quality asthma care and to review the evidence that confirms that these factors do indeed have positive outcomes in primary care.

Key drivers and their underpinning components

The expert panel identified five key drivers for the delivery of quality respiratory care in primary care and a number of components underpinning each of these drivers. These are summarised in Table 1 .

Of the 50 articles selected from the review, there were comparatively smaller numbers of publications relating to the impact of National Health Policy and Guidelines. However, there was more substantial evidence relating to the other three key drivers, which is summarised in tabular format (Tables 2 – 4 ).

National Health Policy

The expert panel reached an agreement that the political will to prioritise asthma and to support both primary care and respiratory disease were fundamental elements for the achievement of a sustainable change. In their opinion this required national and local programmes supporting the improvements. There was however little evidence published to support this opinion with respect to patient outcome as it is not the area of research that is commonly undertaken. A review of seven national European asthma programmes to support strategies to reduce asthma mortality and morbidity concluded that national/regional asthma programmes are more effective than conventional treatment guidelines 12 . One of the most well-known and successful national programmes in Europe, which has resulted in reduced morbidity and mortality and decreased costs, is the Finnish National Asthma Programme 13 . Programmes outside of Europe have also demonstrated the impact that prioritisation of primary care can have on respiratory outcomes. Changing structures and policies in South Africa and in Brazil may start to impact on primary care 13 , 14 .

Few studies have explored the extent of adherence to guidelines for asthma management based on data provided directly by GPs. One study aimed to evaluate adherence to GINA guidelines and its relationship with disease control in real life. According to GINA guideline asthma classification, the results indicated overtreatment of intermittent and mild persistent asthma, as well as a general poor adherence to GINA treatment recommendations, despite its confirmed role in achieving a good asthma control 15 . In the US, nationally representative data showed that agreement with and adherence to asthma guidelines was higher for specialists than for primary care clinicians, but was low in both groups for several key recommendations 16 .

Reward for performance

Pay-for-performance (P4p) schemes are those that remunerate physicians for achieving pre-defined clinical targets and quality measures—so based on value—that contrasts to schemes that are simply a fee-for-service payment, which pay for volume of activity (Data from Review Table 2 ). In the UK, primary care has moved towards group practices with P4p compensation in which performance is measured using several defined quality indicators 17 , 18 . A systematic review of 94 studies showed increased practice activity but only limited evidence of improvements in the quality of primary care or cost-effectiveness, despite modest reductions in mortality and hospital admissions in some domains 18 . In another review of seven studies from the US and UK, the effects of financial incentive schemes were found to improve patient’s well-being, whilst the effects on the quality of primary healthcare were found to be modest and variable 19 .

An evaluation of three primary care incentive models, namely a traditional fee-for-service model, a blended fee-for-service model and a blended capitation model, demonstrated that the quality of asthma care improved over time within each of the primary care models 20 . The model that combined blended fee-for-service with capitation appears to provide better quality care compared to the traditional fee-for-service model in terms of outcome indicators such as a lower rate of emergency department visits.

A P4p programme in the Netherlands containing indicators for chronic care, prevention, practice management and patient experience was designed by target users 21 . A study of 65 practices that implemented the programme showed a significant improvement in the mean asthma score after 1 year. It showed that a bottom-up developed P4p programme might lead to improvements in both clinical care and patient experience.

Practice resources and organisation

Optimal patient care requires targeted and tailored management (Data from Review Table 3 ). The experts felt that the organisation of both the GP practice and the local healthcare system had an influence on the provision of high-quality care. Registered patient lists and fully integrated computer systems were its foundation. An approach called SIMPLES—developed in the UK, incorporated into a desktop reference tool by the International Primary Care Respiratory Group and adapted for use in the Netherlands 22 , 23 —identifies patients who have uncontrolled symptoms or difficult-to-manage disease and addresses preventable or treatable factors to guide their management. Electronic alerts in patient records have also been used to identify those at increased risk of an exacerbation, in order to modify care and treatment 24 , 25 , 26 .

A systematic review of the effectiveness of computerised clinical decision systems (CCDS) in the care of patients with asthma demonstrated improvements in healthcare process measures and patient outcomes 27 . Conversely another systematic review focussing on their implementation in practice concluded that the limiting factors were the lack of their regular use by healthcare practitioners (HCPs) and adherence to the advice offered 28 . These reviews both concluded that CCDS have the potential to improve patient outcomes, practice efficiency and produce cost-saving benefits if implemented 27 , 28 .

Computerised systems linked with internet programmes to monitor asthma control can also afford benefits for patients. One study identified that the use of both weekly internet-based self-monitoring using the Asthma Control Questionnaire (ACQ) and treatment adjustment using an online management tool resulted in significant improvements in ACQ 29 .

Clinical prediction models could theoretically aid the diagnosis of asthma in primary care but supportive evidence is currently lacking 30 . However, there is strong evidence that service models aimed at supporting primary care practitioners with the diagnosis or ongoing monitoring of patients result in improved accuracy and patient outcomes 31 , 32 , 33 .

The expert panel felt that having access to dedicated and appropriately trained personnel preferably as part of multidisciplinary teams was essential (Data from Review Table 4 ). This need was accentuated because of increasing GP workloads and a shortage of primary care physicians in many countries.

There was extensive evidence 34 , 35 , 36 , 37 , 38 , 39 , 40 that a variety of models involving a range of healthcare practitioners within both the core primary healthcare team and extended community teams improve patient outcomes and healthcare process measures—such as an increased use of asthma action plans, improved medication adherence 36 , 39 —and reduces the use of emergency care 34 , 38 .

One approach in Canada is based on using primary care networks, in which additional non-physician healthcare providers are funded to help provide coordinated healthcare 34 . In these networks patients were shown to be less likely to visit the ED than patients in practices that were not part of the network.

Evidence from a range of countries supports the beneficial role of pharmacists, working alone or in teams 36 , 37 , 38 . In a study utilising community pharmacists to review patients with either poorly controlled asthma or no recent asthma review, there were benefits in terms of asthma control, inhaler technique, action plan ownership, asthma-related QOL and medication adherence 36 . The pharmacists were able to recruit patients and incorporate this as part of daily practice. Availability of referral to a physician was an important component of the service.

Evidence also indicates that education delivered by a variety of methods enhances the quality of care delivered and improves patient outcomes 41 , 42 , 43 , 44 , 45 . Approaches integrating education with other interventions, such as the Colorado Asthma Toolkit Programme (CATP) that combines education with decision support tools, electronic patient records and other online support materials, have been shown to have positive outcomes 41 , 42 . Another team-based approach that combined an educational intervention with the integration of an electronic clinical quality management system with a reminder system found that the number of action plans increased significantly 39 .

Patient education is an important factor for the improvement of self-management and asthma control. An educational programme from Australia demonstrated that patients who received person-centred education had improved asthma outcomes compared to those receiving a brochure only 46 . One review paper 47 about patient enablement concluded that HCPs need to develop their understanding of this concept to integrate this into practice as the level of this is linked to better patient outcomes.

Primary care is pivotal to any health system; however, there is no universal definition of what we mean by primary care and certainly not one standardised model of care. Without focussing on a single model, we have attempted to bring together expert opinion and the most recent evidence on strategies that improve outcomes in asthma patients in primary care. To our knowledge the methodology used in this project has not been used before. The panel of experts who identified the key drivers were knowledgeable of asthma in primary care at a national level in their respective countries and globally. A literature search to investigate the individual key drivers and their underpinning components was undertaken using a keyword search. This identified many publications but very few measured the effect on patient outcome and those that did reported conflicting results. Furthermore, we found a paucity of research relating to the components relating to national healthcare policy and guidelines.

The evidence suggests that health systems that have primary care as a cornerstone and place asthma as a healthcare priority improve asthma care and improve outcome on patient level. The highly regarded Finnish asthma initiative carried out more than 25 years ago not only identified asthma as a national priority, but also placed primary care at the centre of the programme, recognising the key role of General Practitioners and nurses and greatly reduced asthma mortality and morbidity 48 . After the successful implementation of the Finnish asthma plan, many other countries and regions have attempted to implement similar initiatives 13 , 14 . For example, in Poland and Brazil, asthma burden was reduced utilising such a strategy 49 .

Poor health outcomes in asthma patients have been attributed in primary care to gaps between evidence-based recommendations and practice 50 , 51 . Studies show that adherence to clinical guidelines is poor, whatever the clinical setting, with the main barriers being time pressures and limited resources 52 , reflecting that it is not the guidelines per se that improve care, but it is the implementation of the recommendations.

Most guidelines are complex, lengthy and generally biased towards a secondary care perspective. The Global Initiative for Asthma (GINA) committee acknowledges the difficulty of implementing their recommendations in primary care, but they are almost exclusively developed by tertiary care physicians 2 . In the Netherlands, the Dutch Royal Society of General Practitioners writes its own guidelines, which are all presented in the same recognisable brief format. Their asthma guidelines were first published in 1986 with revisions every 4 years and are relatively well followed 53 . However, there are now 194 different clinical guidelines in the Netherlands, illustrating just how difficult it is for General Practitioners to adopt all the recommendations of each clinical guideline and its update.

A survival analysis of guidelines has concluded that 86% are still up to date 3 years after their publication and yet the median lifespan of a clinical guideline is about 60 months 54 . New evidence is continually emerging and this implies that regular updates of clinical guidelines are necessary 55 , 56 . It is therefore important that all guidelines have a process for regular scrutiny 57 and are updated for contemporary applicability. Indeed, asthma and COPD guidelines published by the Association of Scientific Medical Societies in Germany and the Asthma Guidelines of the German Respiratory Society are regularly updated, at least every 5 years (more frequently as necessary); if not they are deleted from the website.

The proliferation of guidelines and their asynchronicity can result in conflicting recommendations. For example, in the UK, four asthma guidelines could be followed (the GINA Report, British Thoracic Society and Scottish Intercollegiate Guidelines (BTS) and the NICE recommendations next to local guidelines) 2 , 58 , 59 , none of which are fully aligned. A review of three contemporaneous international guidelines updated in 2012 (The Canadian Thoracic Society (CTS), BTS and GINA) also revealed significant inconsistency arising from varying approaches to evidence interpretation and recommendation formulation 60 .

Globally, there is a move away from pure fee-for-service payments towards primary care payment schemes linked to performance, which recognise and reward good practice to improve quality and reduce costs 61 . These schemes combine quality standards and targets but still tend to be process driven, not outcome based. The evidence for the effectiveness of such schemes in general on improving quality of care is both inconclusive and inconsistent 62 .

The UK quality and outcomes framework (QOF), which includes asthma, is the world’s largest primary care payment for performance (P4p) scheme 63 . Evidence however shows that improved patient outcomes may not be sustained, cost reduction is unproven 18 and leads to increased GP activity, but this does not necessarily correlate with improved individual patient benefit 64 , 65 . Furthermore, in Portugal, the recording of asthma and COPD prevalence as performance indicators in pay-for-performance contracts showed a modest but steady increase over time in physician’s diagnosis and ICPC-2 coding of these two conditions, but no direct patient benefits 66 .

Disease-specific schemes are usually aligned to clinical guidelines and some focus on prescribing. In Norway, under such a scheme, combination asthma medications were only reimbursed for patients diagnosed with asthma. As a result, asthma diagnosis significantly increased 67 .

The effect on health inequalities has also been studied. The results from UK QOF have shown that the gap between achievements from practices in the most deprived and least deprived areas narrowed 68 . Nevertheless, inequalities in morbidity and premature mortality persisted 69 , 70 . Additionally incentives can increase inequalities because those conditions that are ‘incentivised’ are afforded greater priority and resource allocation, to the detriment of those that are not 71 .

It would appear that simplistic fee-for-service schemes based purely on an activity—such as performing spirometry tests—which are not part of reimbursement of a more comprehensive assessment, have the potential to inadvertently lead to an increase in unnecessary tests. Pay-for-performance schemes have the potential to improve asthma care, but will be reliant on the specifics of the scheme and the quality indicators applied. They can be useful as part of a wider programme to raise quality and afford benefits over rewarding fee-for-service activity.

Appropriate practice organisation and systems focussing on the identification, diagnosis and treatment are pivotal for quality asthma care. There was compelling evidence to indicate that integrated, multi-faceted practice-based approaches for the management of patients improves outcomes and reduces the need for referral to secondary care 22 , 25 , 72 . Coordinated practice systems that combine several interventions such as decision support tools, flagging of electronic records, use of care pathways, staff training and structured approaches to patient education, if consistently implemented, afford the greatest benefits. Implementation of practice schemes is likely to be enhanced where there is dedicated clinical and administrative leadership.

Intuitively an accurate diagnosis should lead to better patient outcomes, although we found conflicting evidence that access to proper diagnosis has an impact on patient outcomes 33 , 73 . Nevertheless, an accurate diagnosis remains the fulcrum on which optimal asthma management depends. Indeed programmes in which an expanded medical team improved the quality of asthma care within the primary care setting (such as a diagnostic and management support organisation) show clear benefit on patient outcome 32 .

Spirometry combined with an assessment of reversibility has been set as gold standard for asthma diagnosis 2 . However, standards on quality of spirometry such as those set by the ERS and ATS are often not achieved 74 , 75 , 76 and impose an unnecessarily high and potentially unachievable threshold in primary care 73 . Nevertheless, some studies have demonstrated that primary care office spirometry can meet the acceptability criteria 77 , 78 , 79 . Although such standards are laudable particularly in a specialist setting, their practicability in primary care, where patients commonly have mild–moderate, intermittent disease, is debatable. The latest ATS-ERS spirometry guidelines (published in October 2019) may address some of these issues. 80 However, the use of spirometry in the diagnosis of asthma remains beyond reach in primary care around the world.

In many countries primary care physicians have limited or no access to tests of lung function or airway inflammation. The creation of diagnostic hubs in the community may open access to these tests 32 . A structured approach to diagnosis including applicability and feasibility for primary care is currently under development by an ERS taskforce; its outcome not available at the time of writing.

With rising clinical workloads, increasing clinical complexity and in many countries a shortage of trained primary care physicians, multi-professional teamworking is increasingly important. 81 , 82 This is accentuated by the expectation for primary care to manage patients with chronic illness.

In many parts of the world, appropriately asthma-trained personnel, such as primary care nurses, are key to the delivery of high-quality asthma care. Dedicated nursing staff can offer continuity to patients, providing education and routine follow-up 35 . Evidence supports the concept that pharmacists working alone or in teams in collaboration with GPs are an accessible asset for the effective management of asthma and can positively influence asthma outcomes 36 .

Healthcare practitioner education is pivotal and the need for guideline-focused training in primary care is well established 82 . The literature seems to support this viewpoint but in many studies the effect on outcome has not been adequately considered, highlighting a need for more outcome-focussed research. Healthcare systems faced with the challenge of moving the care of people with long-term conditions such as asthma from established specialist services to primary care should consider implementing collaborative educational strategies 44 . Matrix-support collaborative care that includes training and support for primary care physicians/nurses from specialists, including joint consultations, case discussions and tailored education, has been shown to be well-accepted by primary care professionals and was associated with improved knowledge and reduced respiratory secondary care referrals 44 . A scoping exercise and literature review of the effectiveness of educational interventions in either changing health professional practice or in improving health outcomes was commissioned by The International Primary Care Respiratory Group (IPCRG) 83 . The impact of education interventions on their own was inconclusive, although there was some evidence of effectiveness when they are combined with other quality improvement strategies or incentives 83 .

Asthma continues to be a substantial cause of morbidity and mortality worldwide and there is need for a coordinated effort to improve care. A well-resourced primary care service is central to the provision of accessible and effective asthma care. An expert team identified the drivers that could enable improvements in both clinical management and patient outcomes, and a literature search showed that each of these individual drivers is supported by varying degrees of evidence. Objectively assessing the outcomes of such interventions is challenging because studies in this area are inherently complex, difficult to undertake and resource intensive, and so definitive research is seldom undertaken. In contrast single interventions studies are easier to conduct but frequently methodologically less robust and therefore tend to be inconclusive. Nevertheless, if substantial improvements in the management of asthma in primary care at a global level are to be achieved, combinations of interventions appear to be most effective. Well-supported holistic interventions involving the entire healthcare system and including the patient voice appear to provide the best outcomes.

Expert panel

An expert panel of 12 primary care global asthma experts—ten General Practitioners and two specialist nurses—was convened in Amsterdam. An initial teleconference between the panel preceded the meeting to gather ideas. The expert panel undertook a brainstorming exercise as part of a force-field analysis in order to reveal their ideas and experience regarding drivers of successful management of asthma in primary care 84 . A force-field analysis can be used to determine the forces (factors) that may prevent change from occurring and to identify those that cultivate change. During the brainstorming session, the experts were divided into facilitated groups to discuss the relative importance of the drivers and identify the factors which underpin each of them. Results were analysed thematically and circulated after the meeting for comment and agreement.

Literature review

To identify whether evidence existed for the drivers and factors identified by the expert panel, literature was searched from PUBMED using the terms asthma and primary care in combination with other terms listed in Table 5 . Proposed search terms were combined using Boolean operators. The initial search was limited to papers published in English over the last 10 years and studies in adults aged over 18 years old. The experts were also asked for additional papers and in addition, more articles were identified from the references from the selected papers. Papers identified were subsequently screened for eligibility by MF and TM (Fig. 1 ). A total of 171 were included in the summary table of which 50 papers were identified as having evidence for the factors identified by the panel.

Process by which papers identified by literature review were subsequently screened for eligibility and the different stages in this process. This highlights the number of articles that were selected at each stage of the process, as well as the number of articles excluded and the reasons for exclusion. n number of articles.

Data availability

Anonymised individual participant data from this study and its associated documents can be requested for further research from www.clinicalstudydatarequest.com .

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Acknowledgements

The authors gratefully acknowledge the Expert Panel contributions of Tan Tze Lee (Singapore). Editorial support (in the form of writing assistance, collating author comments, assembling tables/figures, grammatical editing, fact checking, and referencing) was provided by Diana Jones, Ph.D., of Cambrian Clinical Associates Ltd. (UK) and was funded by GlaxoSmithKline plc. The expert panel meeting was funded by GlaxoSmithKline plc.

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Asthma UK Centre for Applied Research, Usher Institute, University of Edinburgh, Old Medical School, Teviot Place, Edinburgh, EH8 9AG, UK

Monica J. Fletcher

Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece

Ioanna Tsiligianni

General Practitioners Research Institute, 59713 GH, Groningen, The Netherlands

Janwillem W. H. Kocks

University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, The Netherlands

Observational and Pragmatic Research Institute, Singapore, Singapore

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Jaime Correia de Sousa

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Mike Thomas

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Peter Kardos

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All authors participated in the expert panel meeting. M.F. and T.v.d.M. were responsible for screening the papers identified in the literature search for suitability for inclusion in the article. All authors developed the manuscript and approved the final version to be submitted.

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Correspondence to Monica J. Fletcher .

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D.L. is an employee of GlaxoSmithKline plc., and holds stocks in GlaxoSmithKline plc. M.F. and T.v.d.M. are former employees of GlaxoSmithKline plc., and M.F. holds stocks in GlaxoSmithKline plc. I.T. reports advisory boards from AstraZeneca, Boehringer Ingelheim, GlaxoSmithKline plc. and Novartis and a grant from GlaxoSmithKline Greece, outside the submitted work. J.K. reports grants and personal fees from AstraZeneca, grants and personal fees from Boehringer Ingelheim, grants from Chiesi, grants and personal fees from GlaxoSmithKline plc., grants and personal fees from Novartis, grants from Mundipharma, grants from TEVA, outside the submitted work. A.C. reports a grant from AstraZeneca for an asthma study. C.C. reports grants from Pfizer China, outside of the submitted work. M.T. reports the following conflicts of interest: neither M.T. nor any member of his close family has any shares in pharmaceutical companies; receipt in the last 3 years of speaker’s honoraria for speaking at sponsored meetings or satellite symposia at conferences from GlaxoSmithKline plc. and Novartis, companies marketing respiratory and allergy products; receipt of honoraria for attending advisory panels with Boehringer Inglehiem, GlaxoSmithKline plc. and Novartis; membership of the BTS SIGN Asthma guideline steering group and the NICE Asthma Diagnosis and Monitoring guideline development group. P.K. reports personal fees from AstraZeneca, GlaxoSmithKline plc., Chiesi, Menarini, Novartis, Klosterfrau, Bionorica, Willmar Schwabe and MSD, and other support (for a phase 3 investigator cough study) from MSD, all outside the submitted work. C.S. has no shares in any pharmaceutical companies, she has received consultant agreements and honoraria for presentations from several pharmaceutical companies that market inhaled medication including AstraZeneca, Boehringer Ingelheim, Chiesi, GlaxoSmithKline plc., Napp Pharmaceuticals and Teva. J.C.d.S. reports personal fees and speaker’s honoraria from Boheringer Ingelheim, personal fees and speaker’s honoraria from GlaxoSmithKline plc., personal fees and speaker’s honoraria from AstraZeneca, personal fees and speaker’s honoraria from Mundipharma outside the submitted work. M.R.R. reports personal fees from AstraZeneca, personal fees from Boehringer Ingelheim, personal fees from Chiesi, grants and personal fees from GlaxoSmithKline plc., personal fees from Menarini, personal fees from Mundipharma, personal fees from Novartis, personal fees from Pfizer, personal fees from Teva, personal fees from Bial, outside the submitted work. E.M.K. received honoraria for attending advisory board meeting from GlaxoSmithKline plc., Boehringer Inglehiem and grant from Novartis outside the submitted work.

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Fletcher, M.J., Tsiligianni, I., Kocks, J.W.H. et al. Improving primary care management of asthma: do we know what really works?. npj Prim. Care Respir. Med. 30 , 29 (2020). https://doi.org/10.1038/s41533-020-0184-0

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DOI : https://doi.org/10.1038/s41533-020-0184-0

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Yeast-fermented bread shows promise in preventing asthma symptoms

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A recent study published in Current Developments in Nutrition investigated the effects of a functional bread fermented with yeast ( Saccharomyces cerevisiae ) in asthma prevention.

Study: A Functional Bread Fermented with Saccharomyces cerevisiae UFMG A-905 Prevents Allergic Asthma in Mice. Image Credit: Sunshine Seeds/Shutterstock.com

Asthma is a complex, heterogeneous disease characterized by airway inflammation, remodeling, and hyper-responsiveness.

Asthma prevalence has been increasing, particularly in more urbanized and high-income countries. Various factors, such as lifestyle changes, obesity, gut microbiota, diet, and environmental exposures, are associated with this surge in prevalence.

Preclinical studies have demonstrated that fungi, bacteria, and other microbes could prevent the development of asthma. While the potential role of probiotics has been highlighted, the best microbe, dose, preparation, and regime are yet to be defined. Probiotics are bacteria from Bifidobacterium and Lactobacillus genera.

Other bacteria and yeasts are also used as probiotics. S. cerevisiae UFMG A-905, isolated from a Brazilian alcoholic beverage, exhibits probiotic characteristics and can prevent bacterial infection, food allergy, colitis, and mucositis.

Previously, the study’s authors reported that the isolation prevented asthma-like characteristics in an animal model.

About the study

In the present study, researchers examined the effects of S. cerevisiae UFMG A-905-fermented bread (UFMG-A905 bread) in asthma prevention. They developed microcapsules containing the yeast isolate by the ionotropic gelation method.

The number of viable cells in the microcapsules was determined. Further, they prepared three bread formulations: 1) commercial yeast-fermented bread (COM bread), UFMG-A905 bread, and UFMG-A905 bread with microcapsules (UFMG-A905-C bread).

Conclusions

The study examined the effects of bread fermented with S. cerevisiae UFMG A-905 on asthma prevention in mice. The UFMG A-905 group exhibited partially decreased airway inflammation.

In contrast, adding microcapsules reduced airway hyper-responsiveness and elevated IL-17A levels. Notably, the team did not examine the survival of yeast in microcapsules after baking. Besides, they did not test COM bread with microcapsules.

Calazans APCT, Milani TMS, Prata AS, et al. (2024) A Functional Bread Fermented with Saccharomyces cerevisiae UFMG A-905 Prevents Allergic Asthma in Mice. Current Developments in Nutrition ,. doi: 10.1016/j.cdnut.2024.102142 . https://cdn.nutrition.org/article/S2475-2991(24)00076-3/fulltext

Posted in: Medical Science News | Life Sciences News | Medical Research News | Biochemistry | Medical Condition News

Tags: Airway Inflammation , Allergy , Animal Model , Asthma , Bacteria , Bread , Cell , Cytokine , Diet , Eosinophil , Food , Food Allergy , fungi , Inflammation , Lactobacillus , Lungs , Mucositis , Nutrition , Obesity , Preclinical , Probiotic , Probiotics , Respiratory , S. cerevisiae , Saccharomyces Cerevisiae , Yeast

Tarun Sai Lomte

Tarun is a writer based in Hyderabad, India. He has a Master’s degree in Biotechnology from the University of Hyderabad and is enthusiastic about scientific research. He enjoys reading research papers and literature reviews and is passionate about writing.

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Sai Lomte, Tarun. "Yeast-fermented bread shows promise in preventing asthma symptoms". News-Medical . 21 June 2024. <https://www.news-medical.net/news/20240620/Yeast-fermented-bread-shows-promise-in-preventing-asthma-symptoms.aspx>.

Sai Lomte, Tarun. "Yeast-fermented bread shows promise in preventing asthma symptoms". News-Medical. https://www.news-medical.net/news/20240620/Yeast-fermented-bread-shows-promise-in-preventing-asthma-symptoms.aspx. (accessed June 21, 2024).

Sai Lomte, Tarun. 2024. Yeast-fermented bread shows promise in preventing asthma symptoms . News-Medical, viewed 21 June 2024, https://www.news-medical.net/news/20240620/Yeast-fermented-bread-shows-promise-in-preventing-asthma-symptoms.aspx.

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Asthma: diagnosis, monitoring and chronic asthma management

NICE Guideline, No. 80

This guideline is the basis of QS25 and QS181.

This guideline covers diagnosing, monitoring and managing asthma in adults, young people and children. It aims to improve the accuracy of diagnosis, help people to control their asthma and reduce the risk of asthma attacks. It does not cover managing severe asthma or acute asthma attacks.

In March 2021 , we highlighted the importance of including advice in the personalised action plan on minimising indoor air pollution and reducing exposure to outdoor air pollution.

Who is it for?

GPs and practice nurses
Healthcare professionals in secondary care and tertiary asthma services
Commissioners and providers
People with suspected or diagnosed asthma, their families and carers
Recommendations

People have the right to be involved in discussions and make informed decisions about their care, as described in NICE’s information on making decisions about your care .

Making decisions using NICE guidelines explains how we use words to show the strength (or certainty) of our recommendations, and has information about prescribing medicines (including off-label use), professional guidelines, standards and laws (including on consent and mental capacity), and safeguarding.

1.1. Initial clinical assessment

See also algorithm A for initial clinical assessment in adults, young people and children with suspected asthma.

Algorithm A

Initial clinical assessment for adults, young people and children with suspected asthma. A full-size downloadable PDF version of algorithm A is available in tools and resources.

Clinical history

wheeze, cough or breathlessness, and any daily or seasonal variation in these symptoms
any triggers that make symptoms worse
a personal or family history of atopic disorders. [2017]

Do not use symptoms alone without an objective test to diagnose asthma . [2017]

Do not use a history of atopic disorders alone to diagnose asthma. [2017]

Physical examination

Examine people with suspected asthma to identify expiratory polyphonic wheeze and signs of other causes of respiratory symptoms, but be aware that even if examination results are normal the person may still have asthma. [2017]

Initial treatment and objective tests for acute symptoms at presentation

Treat people immediately if they are acutely unwell at presentation, and perform objective tests for asthma (for example, fractional exhaled nitric oxide [FeNO], spirometry and peak flow variability) if the equipment is available and testing will not compromise treatment of the acute episode. [2017]

If objective tests for asthma cannot be done immediately for people who are acutely unwell at presentation, carry them out when acute symptoms have been controlled, and advise people to contact their healthcare professional immediately if they become unwell while waiting to have objective tests. [2017]

Be aware that the results of spirometry and FeNO tests may be affected in people who have been treated empirically with inhaled corticosteroids. [2017]

Testing for asthma

skin prick tests to aeroallergens
serum total and specific IgE
peripheral blood eosinophil count
exercise challenge (to adults aged 17 and over). [2017]

Use skin prick tests to aeroallergens or specific IgE tests to identify triggers after a formal diagnosis of asthma has been made. [2017]

Occupational asthma

Are symptoms better on days away from work?
Are symptoms better when on holiday (time away from work longer than usual breaks at weekends or between shifts)?

Make sure all answers are recorded for later review. [2017]

Refer people with suspected occupational asthma to an occupational asthma specialist. [2017]

1.2. Diagnosing asthma in young children

For children under 5 with suspected asthma, treat symptoms based on observation and clinical judgement, and review the child on a regular basis (see the section on pharmacological treatment pathway for children under 5 ). If they still have symptoms when they reach 5 years, carry out objective tests (see the section on objective tests for diagnosing asthma in adults, young people and children aged 5 and over and algorithm B ). [2017]

continue to treat based on observation and clinical judgement
try doing the tests again every 6 to 12 months until satisfactory results are obtained
consider referral for specialist assessment if the child repeatedly cannot perform objective tests and is not responding to treatment. [2017]

Algorithm B

Objective tests for asthma in children and young people aged 5 to 16. A full-size downloadable PDF version of algorithm B is available in tools and resources.

1.3. Objective tests for diagnosing asthma in adults, young people and children aged 5 and over

See also table 1 for a summary of objective test threshold levels.

Positive test thresholds for objective tests for adults, young people and children (aged 5 and over).

Diagnostic hubs

Those responsible for planning diagnostic service support to primary care (for example, clinical commissioning groups) should consider establishing asthma diagnostic hubs to achieve economies of scale and improve the practicality of implementing the recommendations in this guideline. [2017]

Airway inflammation measures

Fractional exhaled nitric oxide.

Offer a FeNO test to adults (aged 17 and over) if a diagnosis of asthma is being considered. Regard a FeNO level of 40 parts per billion (ppb) or more as a positive test. [2017]

normal spirometry or
obstructive spirometry with a negative bronchodilator reversibility (BDR) test.

Regard a FeNO level of 35 ppb or more as a positive test. Note: apply the principles in recommendation 1.2.2 for young children unable to do the FeNO test adequately. [2017]

Be aware that a person’s current smoking status can lower FeNO levels both acutely and cumulatively. However, a high level remains useful in supporting a diagnosis of asthma. [2017]

Lung function tests

Offer spirometry to adults, young people and children aged 5 and over if a diagnosis of asthma is being considered. Regard a forced expiratory volume in 1 second/forced vital capacity (FEV1/FVC) ratio of less than 70% (or below the lower limit of normal if this value is available) as a positive test for obstructive airway disease (obstructive spirometry). [2017]

Bronchodilator reversibility

Offer a BDR test to adults (aged 17 and over) with obstructive spirometry (FEV1/FVC ratio less than 70%). Regard an improvement in FEV1 of 12% or more, together with an increase in volume of 200 ml or more, as a positive test. [2017]

Consider a BDR test in children and young people (aged 5 to 16) with obstructive spirometry (FEV1/FVC ratio less than 70%). Regard an improvement in FEV1 of 12% or more as a positive test. [2017]

Peak expiratory flow variability

obstructive spirometry, reversible airways obstruction (positive BDR) but a FeNO level of 39 ppb or less.

Regard a value of more than 20% variability as a positive test. [2017]

obstructive spirometry and
irreversible airways obstruction (negative BDR) and
a FeNO level between 25 ppb and 39 ppb.
obstructive spirometry, irreversible airways obstruction (negative BDR) and a FeNO level of 35 ppb or more.

Airway hyperreactivity measures

Direct bronchial challenge test with histamine or methacholine.

In November 2017, the use of histamine and methacholine described in recommendations 1.3.11 and 1.3.12 was off label. See NICE’s information on prescribing medicines .

FeNO level of 40 ppb or more and no variability in peak flow readings or
FeNO level of 39 ppb or less with variability in peak flow readings.

Regard a PC20 value of 8 mg/ml or less as a positive test. [2017]

obstructive spirometry without bronchodilator reversibility and
a FeNO level between 25 ppb and 39 ppb and
no variability in peak flow readings (less than 20% variability over 2 to 4 weeks).

If a direct bronchial challenge test with histamine or methacholine is unavailable, suspect asthma and review the diagnosis after treatment, or refer to a centre with access to a histamine or methacholine challenge test. [2017]

Diagnosis in children and young people aged 5 to 16

See also algorithm B for objective tests in young people and children aged 5 to 16.

a FeNO level of 35 ppb or more and positive peak flow variability or
obstructive spirometry and positive bronchodilator reversibility. [2017]
a FeNO level of 35 ppb or more with normal spirometry and negative peak flow variability or
a FeNO level of 35 ppb or more with obstructive spirometry but negative bronchodilator reversibility and no variability in peak flow readings or
normal spirometry, a FeNO level of 34 ppb or less and positive peak flow variability.

Do not rule out other diagnoses if symptom control continues to remain poor after treatment. Review the diagnosis after 6 weeks by repeating any abnormal tests and reviewing symptoms. [2017]

Refer children and young people (aged 5 to 16) for specialist assessment if they have obstructive spirometry, negative bronchodilator reversibility and a FeNO level of 34 ppb or less. [2017]

Consider alternative diagnoses and referral for specialist assessment in children and young people (aged 5 to 16) if they have symptoms suggestive of asthma but normal spirometry, a FeNO level of 34 ppb or less and negative peak flow variability. [2017]

Diagnosis in adults aged 17 and over

See also algorithm C for objective tests in adults aged 17 and over.

Algorithm C

Objective tests for asthma in adults aged 17 and over. A full-size downloadable PDF version of algorithm C is available in tools and resources.

a FeNO level of 40 ppb or more with either positive bronchodilator reversibility or positive peak flow variability or bronchial hyperreactivity or
a FeNO level between 25 ppb and 39 ppb and a positive bronchial challenge test or
positive bronchodilator reversibility and positive peak flow variability irrespective of FeNO level. [2017]
negative bronchodilator reversibility, and either a FeNO level of 40 ppb or more, or a FeNO level between 25 ppb and 39 ppb and positive peak flow variability or
positive bronchodilator reversibility, a FeNO level between 25 ppb and 39 ppb and negative peak flow variability.

Do not rule out other diagnoses if symptom control continues to remain poor after treatment. Review the diagnosis after 6 to 10 weeks by repeating spirometry and objective measures of asthma control and reviewing symptoms. [2017]

a FeNO level below 40 ppb, normal spirometry and positive peak flow variability or
a FeNO level of 40 ppb or more but normal spirometry, negative peak flow variability, and negative bronchial challenge test or
obstructive spirometry with bronchodilator reversibility, but a FeNO level below 25 ppb, and negative peak flow variability or
positive peak flow variability but normal spirometry, a FeNO level below 40 ppb, and a negative bronchial challenge test or
obstructive spirometry with negative bronchodilator reversibility, a FeNO level below 25 ppb, and negative peak flow variability (if measured). [2017]

Diagnosis in people who are unable to perform an objective test

For young children who cannot perform objective tests, see the section on diagnosing asthma in young children .

If an adult, young person or child with symptoms suggestive of asthma cannot perform a particular test, try to perform at least 2 other objective tests. Diagnose suspected asthma based on symptoms and any positive objective test results. [2017]

Good clinical practice in asthma diagnosis

Record the basis for a diagnosis of asthma in a single entry in the person’s medical records, alongside the coded diagnostic entry. [2017]

1.4. Diagnostic summary

The following algorithms have been produced that summarise clinical assessment and objective testing for asthma. Table 1 summarises the objective test threshold levels.

1.5. Principles of pharmacological treatment

alternative diagnoses
lack of adherence
suboptimal inhaler technique
smoking (active or passive)
occupational exposures
psychosocial factors
seasonal or environmental factors. [2017]

After starting or adjusting medicines for asthma, review the response to treatment in 4 to 8 weeks (see the section on monitoring asthma control ). [2017]

If inhaled corticosteroid (ICS) maintenance therapy is needed, offer regular daily ICS rather than intermittent or ‘when required’ ICS therapy. [2017]

Adjust maintenance therapy ICS doses over time, aiming for the lowest dose required for effective asthma control. [2017]

at any asthma review, either routine or unscheduled
whenever a new type of device is supplied. [2017]

1.6. Pharmacological treatment pathway for adults (aged 17 and over)

This section is for people with newly diagnosed asthma or asthma that is uncontrolled on their current treatment. Where the recommendations represent a change from traditional clinical practice, people whose asthma is well controlled on their current treatment should not have their treatment changed purely to follow this guidance.

Offer a short-acting beta 2 agonist (SABA) as reliever therapy to adults (aged 17 and over) with newly diagnosed asthma. [2017]

For adults (aged 17 and over) with asthma who have infrequent, short-lived wheeze and normal lung function, consider treatment with SABA reliever therapy alone. [2017]

symptoms at presentation that clearly indicate the need for maintenance therapy (for example, asthma-related symptoms 3 times a week or more, or causing waking at night) or
asthma that is uncontrolled with a SABA alone. [2017]

If asthma is uncontrolled in adults (aged 17 and over) on a low dose of ICS as maintenance therapy, offer a leukotriene receptor antagonist (LTRA) in addition to the ICS and review the response to treatment in 4 to 8 weeks. [2017]

discuss with the person whether or not to continue LTRA treatment
take into account the degree of response to LTRA treatment. [2017]

If asthma is uncontrolled in adults (aged 17 and over) on a low dose of ICS and a LABA, with or without an LTRA, as maintenance therapy, offer to change the person’s ICS and LABA maintenance therapy to a MART regimen with a low maintenance ICS dose. [2017]

If asthma is uncontrolled in adults (aged 17 and over) on a MART regimen with a low maintenance ICS dose, with or without an LTRA, consider increasing the ICS to a moderate maintenance dose (either continuing on a MART regimen or changing to a fixed dose of an ICS and a LABA, with a SABA as a reliever therapy). [2017]

increasing the ICS to a high maintenance dose (this should only be offered as part of a fixed-dose regimen, with a SABA used as a reliever therapy) or
a trial of an additional drug (for example, a long-acting muscarinic receptor antagonist or theophylline) or
seeking advice from a healthcare professional with expertise in asthma. [2017]

1.7. Pharmacological treatment pathway for children and young people aged 5 to 16

This section is for children and young people with newly diagnosed asthma or asthma that is uncontrolled on their current treatment. Where the recommendations represent a change from traditional clinical practice, children and young people whose asthma is well controlled on their current treatment should not have their treatment changed purely to follow guidance.

Not all LTRAs and LABAs had a UK marketing authorisation for children and young people aged under 18 for the use described in recommendations 1.7.4 and 1.7.5 .
The use of MART described in recommendations 1.7.6 , 1.7.7 and 1.7.8 was off label in children and young people (aged under 12).

See NICE’s information on prescribing medicines .

Offer a SABA as reliever therapy to children and young people (aged 5 to 16) with newly diagnosed asthma. [2017]

For children and young people (aged 5 to 16) with asthma who have infrequent, short-lived wheeze and normal lung function, consider treatment with SABA reliever therapy alone. [2017]

If asthma is uncontrolled in children and young people (aged 5 to 16) on a paediatric low dose of ICS as maintenance therapy, consider an LTRA in addition to the ICS and review the response to treatment in 4 to 8 weeks. [2017]

If asthma is uncontrolled in children and young people (aged 5 to 16) on a paediatric low dose of ICS and an LTRA as maintenance therapy, consider stopping the LTRA and starting a LABA in combination with the ICS. [2017]

If asthma is uncontrolled in children and young people (aged 5 to 16) on a paediatric low dose of ICS and a LABA as maintenance therapy, consider changing their ICS and LABA maintenance therapy to a MART regimen with a paediatric low maintenance ICS dose. Ensure that the child or young person is able to understand and comply with the MART regimen. [2017]

If asthma is uncontrolled in children and young people (aged 5 to 16) on a MART regimen with a paediatric low maintenance ICS dose, consider increasing the ICS to a paediatric moderate maintenance dose (either continuing on a MART regimen or changing to a fixed dose of an ICS and a LABA, with a SABA as a reliever therapy). [2017]

increasing the ICS dose to paediatric high maintenance dose (only as part of a fixed-dose regimen, with a SABA used as a reliever therapy) or
a trial of an additional drug (for example, theophylline). [2017]

1.8. Pharmacological treatment pathway for children under 5

It can be difficult to confirm asthma diagnosis in young children, therefore these recommendations apply to children with suspected or confirmed asthma. Asthma diagnosis should be confirmed when the child is able to undergo objective tests (see the section on diagnosing asthma in young children ).

This section is for children under 5 with newly suspected or confirmed asthma, or with asthma symptoms that are uncontrolled on their current treatment. Where the recommendations represent a change from traditional clinical practice, children whose asthma is well controlled on their current treatment should not have their treatment changed purely to follow this guidance.

Offer a SABA as reliever therapy to children under 5 with suspected asthma . This should be used for symptom relief alongside all maintenance therapy. [2017]

suspected asthma that is uncontrolled with a SABA alone. [2017]
if symptoms did not resolve during the trial period, review whether an alternative diagnosis is likely
if symptoms resolved then reoccurred within 4 weeks of stopping ICS treatment, restart the ICS at a paediatric low dose as first-line maintenance therapy
if symptoms resolved but reoccurred beyond 4 weeks after stopping ICS treatment, repeat the 8-week trial of a paediatric moderate dose of ICS. [2017]

If suspected asthma is uncontrolled in children under 5 on a paediatric low dose of ICS as maintenance therapy, consider an LTRA in addition to the ICS. [2017]

In November 2017, not all LTRAs had a UK marketing authorisation for this use in children aged under 5. See NICE’s information on prescribing medicines .

If suspected asthma is uncontrolled in children under 5 on a paediatric low dose of ICS and an LTRA as maintenance therapy, stop the LTRA and refer the child to a healthcare professional with expertise in asthma for further investigation and management. [2017]

1.9. Adherence

For guidance on managing non-adherence to medicines in people with asthma, see the NICE guideline on medicines adherence . [2017]

1.10. Self-management

Offer an asthma self-management programme, comprising a written personalised action plan and education.
Explain that pollution can trigger or exacerbate asthma, and include in the personalised action plan approaches for minimising exposure to indoor and outdoor air pollution.

For more guidance on how to minimise exposure and the effect of air pollution on health, see: the recommendations on vulnerable groups in the NICE guideline on air pollution: outdoor air quality and health and the recommendations on people with asthma, other respiratory conditions or cardiovascular conditions in the NICE guideline on indoor air quality at home . [2017, amended 2021]

consider quadrupling the regular ICS dose
do not exceed the maximum licensed daily dose. [2017]

For children and young people aged 5 to 16 with a diagnosis of asthma, include advice in their self-management programme on contacting a healthcare professional for a review if their asthma control deteriorates (see the section on monitoring asthma control ). [2020]

For children and young people aged 5 to 16 with deteriorating asthma who have not been taking their ICS consistently, explain that restarting regular use may help them to regain control of their asthma. The evidence for increasing ICS doses to self-manage deteriorating asthma control is limited. [2020]

Consider an asthma self-management programme, comprising a written personalised action plan (including approaches to minimising exposure to indoor and outdoor air pollution) and education, for the families or carers of children under 5 with suspected or confirmed asthma. [2017, amended 2021]

For a short explanation of why the committee made the 2020 recommendations on self-management and removed the 2017 recommendation on increasing ICS treatment within a self-management programme in children and young people and how this might affect practice, see the rationale and impact section on self-management .

Full details of the evidence and the committee’s discussion are in evidence review A: increasing ICS treatment within supported self-management for children and young people .

1.11. Decreasing maintenance therapy

Consider decreasing maintenance therapy when a person’s asthma has been controlled with their current maintenance therapy for at least 3 months. [2017]

Discuss with the person (or their family or carer if appropriate) the potential risks and benefits of decreasing maintenance therapy. [2017]

Stop or reduce dose of medicines in an order that takes into account the clinical effectiveness when introduced, side effects and the person’s preference.
Only consider stopping ICS treatment completely for people who are using low dose ICS alone as maintenance therapy and are symptom free. [2017]

Agree with the person (or their family or carer if appropriate) how the effects of decreasing maintenance therapy will be monitored and reviewed, including self-monitoring and a follow-up with a healthcare professional. [2017]

Review and update the person’s asthma action plan when decreasing maintenance therapy. [2017]

1.12. Risk stratification

Consider using risk stratification to identify people with asthma who are at increased risk of poor outcomes, and use this information to optimise their care. Base risk stratification on factors such as non-adherence to asthma medicines, psychosocial problems and repeated episodes of unscheduled care for asthma. [2017]

1.13. Monitoring asthma control

confirm the person’s adherence to prescribed treatment in line with the recommendations on assessing adherence in the NICE guideline on medicines adherence
review the person’s inhaler technique
review if treatment needs to be changed
ask about occupational asthma (see recommendation on checking for possible occupational asthma ) and/or other triggers, if relevant. [2017]

Consider using a validated questionnaire (for example, the Asthma Control Questionnaire or Asthma Control Test) to monitor asthma control in adults (aged 17 and over). [2017]

Monitor asthma control at each review in adults, young people and children aged 5 and over using either spirometry or peak flow variability testing. [2017]

Do not routinely use FeNO to monitor asthma control. [2017]

Consider FeNO measurement as an option to support asthma management in people who are symptomatic despite using inhaled corticosteroids. (This recommendation is from NICE’s diagnostics guidance on measuring fractional exhaled nitric oxide concentration in asthma .) [2017]

Do not use challenge testing to monitor asthma control. [2017]

at every consultation relating to an asthma attack, in all care settings
when there is deterioration in asthma control
when the inhaler device is changed
at every annual review
if the person asks for it to be checked. [2017]

Terms used in this guideline

This section defines terms that have been used in a particular way for this guideline. For other definitions, see the NICE glossary .

A wheeze is a continuous, whistling sound produced in the airways during breathing. It is caused by narrowing or obstruction in the airways. An expiratory polyphonic wheeze has multiple pitches and tones heard over different areas of the lung when the person breathes out.

ICS doses and their pharmacological strengths vary across different formulations. In general, people with asthma should use the smallest doses of ICS that provide optimal control for their asthma, in order to reduce the risk of side effects.

less than or equal to 400 micrograms budesonide or equivalent would be considered a low dose
more than 400 micrograms to 800 micrograms budesonide or equivalent would be considered a moderate dose
more than 800 micrograms budesonide or equivalent would be considered a high dose.
less than or equal to 200 micrograms budesonide or equivalent would be considered a paediatric low dose
more than 200 micrograms to 400 micrograms budesonide or equivalent would be considered a paediatric moderate dose
more than 400 micrograms budesonide or equivalent would be considered a paediatric high dose.

Maintenance and reliever therapy (MART) is a form of combined ICS and LABA treatment in which a single inhaler, containing both ICS and a fast-acting LABA, is used for both daily maintenance therapy and the relief of symptoms as required. MART is only available for ICS and LABA combinations in which the LABA has a fast-acting component (for example, formoterol).

Tests carried out to help determine whether a person has asthma, the results of which are not based on the person’s symptoms, for example, tests to measure lung function or evidence of inflammation. There is no single objective test to diagnose asthma.

Risk stratification is a process of categorising a population by their relative likelihood of experiencing certain outcomes. In the context of this guideline, risk stratification involves categorising people with asthma by their relative likelihood of experiencing negative clinical outcomes (for example, severe exacerbations or hospitalisations). Factors including non-adherence to asthma medicines, psychosocial problems and repeated episodes of unscheduled care can be used to guide risk stratification. Once the population is stratified, the delivery of care for the population can be targeted with the aim of improving the care of the strata with the highest risk.

Suspected asthma describes a potential diagnosis of asthma based on symptoms and response to treatment that has not yet been confirmed with objective tests.

Uncontrolled asthma describes asthma that has an impact on a person’s lifestyle or restricts their normal activities. Symptoms such as coughing, wheezing, shortness of breath and chest tightness associated with uncontrolled asthma can significantly decrease a person’s quality of life and may lead to a medical emergency. Questionnaires are available that can be quantify this.

3 or more days a week with symptoms or
3 or more days a week with required use of a SABA for symptomatic relief or
1 or more nights a week with awakening due to asthma.
Putting this guideline into practice

NICE is recommending objective testing with spirometry and FeNO for most people with suspected asthma. This is a significant enhancement to current practice, which will take the NHS some time to implement, with additional infrastructure and training needed in primary care. New models of care, being developed locally, could offer the opportunity to implement these recommendations. This may involve establishing diagnostic hubs to make testing efficient and affordable. They will be able to draw on the positive experience of NICE’s primary care pilot sites, which trialled the use of FeNO.

The investment and training required to implement the new guidance will take time. In the meantime, primary care services should implement what they can of the new guidelines, using currently available approaches to diagnosis until the infrastructure for objective testing is in place.

NICE has produced tools and resources to help you put this guideline into practice.

Adoption support resource
Resource impact report
Resource impact templates
Recommendations for research

The 2017 guideline committees made the following recommendations for research on diagnosing and monitoring asthma and for managing chronic asthma (marked [2017] ). The committee’s full set of research recommendations is detailed in the 2017 full guideline on asthma: diagnosis and monitoring and the 2017 full guideline on chronic asthma management .

As part of the 2020 update, the guideline committee made 1 new research recommendation on managing asthma within a self-management programme for children and young people (marked [2020] ).

Diagnosing and monitoring asthma

1. diagnosing asthma in children and young people aged 5 to 16.

What is the acceptability and diagnostic accuracy of objective tests that could be used to comprise a diagnostic pathway for asthma in children and young people aged 5 to 16 (for example, exercise challenge, direct bronchial challenge with histamine or methacholine, indirect bronchial challenge with mannitol and peripheral blood eosinophil count)? [2017]

2. Diagnosing asthma in adults (aged 17 and over)

What is the clinical and cost effectiveness of using an indirect bronchial challenge test with mannitol to diagnose asthma in adults (aged 17 and over)? [2017]

3. Monitoring adherence to treatment

What is the clinical and cost effectiveness of using electronic alert systems designed to monitor and improve adherence with regular inhaled maintenance therapy in people with asthma? [2017]

4. Monitoring inhaler technique

What is the current frequency and the current method being used to check the inhaler technique of people with asthma? What is the optimal frequency and the best method of checking inhaler technique to improve clinical outcomes for people with asthma? [2017]

5. Monitoring asthma control using tele-healthcare

What is the long-term (more than 12 months) clinical and cost effectiveness of using tele-healthcare as a means to monitor asthma control in adults, young people and children? Methods of tele-healthcare can include telephone interview (with healthcare professional involvement) and internet or smartphone-based monitoring support (no healthcare professional involvement). [2017]

Managing chronic asthma

1. increasing the dose of ics within a personalised self-management programme for children and young people.

For children and young people with asthma that is managed in primary care, is there an advantage to increasing the inhaled corticosteroid (ICS) dose when asthma control has deteriorated compared with using the usual dose in a self-management programme? [2020]

For a short explanation of why the committee made the recommendation for research, see the rationale on increasing the dose of ICS within a personalised self-management programme for children and young people .

Full details of the research recommendation are in evidence review A: increasing ICS treatment within supported self-management for children and young people .

2. Starting asthma treatment

In adults, young people and children with asthma who have not been treated previously, is it more clinically and cost effective to start treatment with a reliever alone (a short-acting beta 2 agonist [SABA]) or with a reliever (a SABA) and maintenance therapy (such as ICS)? Are there specific prognostic features that indicate that one of these treatment options may be more appropriate for some groups? [2017]

3. Second-line maintenance therapy in children and young people (under 16)

Is maintenance therapy more effective with a paediatric low dose of ICS plus a leukotriene receptor antagonist (LTRA) or with a paediatric low dose of ICS plus a long-acting beta 2 agonist (LABA) in the treatment of asthma in children and young people (under 16) who have uncontrolled asthma on a paediatric low dose of ICS alone? [2017]

4. Additional maintenance therapy for asthma uncontrolled on a moderate dose of ICS plus LABA with or without LTRA

What is the clinical and cost effectiveness of offering additional maintenance therapy to adults, young people and children with asthma that is uncontrolled on a moderate dose of ICS plus LABA with or without LTRA? [2017]

5. Decreasing pharmacological treatment

In adults, young people and children with well-controlled asthma, what are the objective measurements and prognostic factors that indicate that a decrease in regular maintenance treatment is appropriate? [2017]

6. Improving adherence to asthma medication

What are the most clinically and cost-effective strategies to improve medicines adherence in adults, young people and children with asthma who are non-adherent to prescribed medicines? [2017]

Rationale and impact

This section briefly explain why the committee made the recommendations and how they might affect practice. They link to details of the evidence and a full description of the committee’s discussion.

Self-management

Recommendations 1.10.3 and 1.10.4

Why the committee changed the recommendations

The evidence for children and young people found that increasing the dose of inhaled corticosteroid (ICS) when asthma control deteriorates did not result in any benefits or harms compared to the usual dose in terms of reducing subsequent asthma exacerbations. It was limited to only 1 study with a small number of participants who had a personalised action plan. The committee also looked at studies in adults, but agreed that the evidence was not applicable because of the high average age of participants.

The 2017 guideline recommended that quadrupling the dose of ICS could be considered within a self-management programme for children and young people whose asthma is deteriorating. The 2020 update committee agreed that this 2017 recommendation was based on limited evidence, mostly in adults, and that the new evidence identified in this update did not support this. However, it also agreed that there wasn’t any significant evidence to suggest that increasing the dose of ICS is harmful compared to the usual dose. Based on their experience, the committee agreed that increasing the dose of ICS within the licensed limit would not adversely affect child growth. This was supported by the evidence, which showed that increasing the ICS dose in the short term did not result in a statistically significant decrease in child growth, even though the doses used in the study exceeded the licensed limit. Therefore, the committee decided to remove the 2017 recommendation rather than replacing it with a recommendation that prohibits increasing the dose of ICS.

The committee discussed the importance of a personalised action plan to guide children and young people if their asthma worsens and to reassure them that they are in control of their treatment. Children and young people who find that increasing their dose of ICS is helpful when their asthma control worsens should be able to continue to do this as an agreed strategy in their action plan. However, based on their experience the committee members agreed that it is important to review the child or young person’s self-management plan if their asthma control is deteriorating. Reviews involve checking current medicines and inhaler technique, discussing any factors that may be triggering symptoms, discussing adherence and education needs, and reviewing their action plan. They should be carried out as needed, in addition to annual review. The committee also stressed the importance of continuing regular ICS maintenance therapy, or restarting it if the child or young person has stopped taking it, to prevent deterioration.

The committee discussed the importance of an individualised approach for children and young people, because they have varied and changing support needs at different ages. Studies have shown that most child asthma deaths involve children who have frequent but mild symptoms that are not responding to management in their personalised action plan. This recommendation should help to ensure that these children and young people receive the support that they need if they start to have problems with their asthma control.

The committee agreed that further research is needed to give clearer guidance on increasing the dose of ICS in children and young people within a self-management programme and made a research recommendation on increasing the dose of ICS within a personalised self-management programme for children and young people to promote further research and inform future practice.

How the recommendations might affect practice

The recommendations will lead to an increase in the review of self-management programmes for children and young people and reduce the variation in current practice for this. The increase in resources needed for this is likely to be offset by a reduction in the cost of treating asthma exacerbations.

Return to recommendations

Asthma is a chronic inflammatory respiratory disease. It can affect people of any age, but often starts in childhood. Asthma is a variable disease which can change throughout a person’s life, throughout the year and from day to day. It is characterised by attacks (also known as exacerbations) of breathlessness and wheezing, with the severity and frequency of attacks varying from person to person. The attacks are associated with variable airflow obstruction and inflammation within the lungs, which if left untreated can be life-threatening, however with the appropriate treatment can be reversible.

In 2018, the Global Asthma report estimated that asthma affects 339 million people worldwide. It is the most common chronic condition to affect children, and in the UK approximately 5.4 million people (1.1 million children and 4.3 million adults) currently get treatment for asthma ( Asthma UK ).

The causes of asthma are not well understood. A number of risk factors are associated with the condition, often in combination. These influences can be genetic (the condition clusters in families) and/or environmental (such as inhalation of allergens or chemical irritants). Occupational causes of asthma in adults are often under-recognised.

Diagnosis and monitoring

There is currently no gold standard test available to diagnose asthma; diagnosis is principally based on a thorough history taken by an experienced clinician. Studies of adults diagnosed with asthma suggest that up to 30% do not have clear evidence of asthma. Some may have had asthma in the past, but it is likely that many have been given an incorrect diagnosis. Conversely, other studies suggest that asthma may be underdiagnosed in some cases.

The diagnosis recommendations will improve patient outcomes and will be cost effective to the NHS in the long-term; NICE’s cost impact assessment projects a saving of approximately £12 million per year in England, before implementation costs.

Initial clinical assessment should include questions about symptoms (wheezing, cough, breathing and chest problems) and any personal or family history of allergies, atopic disorders or asthma. Various tests can be used to support a diagnosis, but there is no single test that can definitively diagnose asthma.

A number of methods and assessments are available to determine the likelihood of asthma. These include measuring airflow obstruction (spirometry and peak flow) and assessment of reversibility with bronchodilators, with both methods being widely used in current clinical practice. However, normal results do not exclude asthma and abnormal results do not always mean it is asthma, because they could be indicators of other respiratory diseases or spurious readings.

Testing for airway inflammation is increasingly used as a diagnostic strategy in clinical practice. This includes measuring fractional exhaled nitric oxide (FeNO).

Other diagnostic strategies include blood or skin prick tests to detect allergic reactions to environmental influences, exercise tests to detect evidence of bronchoconstriction, and measures of airway hyperreactivity such as histamine/methacholine or mannitol challenge tests. However, it is debatable which test or measure, or combination of them, is the most effective to accurately diagnose asthma.

It is recognised that asthma control is suboptimal in many people with asthma. This has an impact on their quality of life, their use of healthcare services and the associated costs. Asthma control can be monitored by measuring airway obstruction or inflammation and by using validated questionnaires, but the most effective monitoring strategy is unclear.

The severity of asthma varies; some people have severe asthma that limits normal activities, whereas others are able to lead a relatively normal life. The illness fluctuates during the year and over time, so the level of treatment needs to be tailored to the person’s current level of asthma severity. Many people with asthma, particularly children, seem to have fewer symptoms over time, and an important part of management is decreasing treatment if asthma is well controlled.

There is no cure for asthma, so management focuses on reducing exposure to known triggers if possible, relief of symptoms if there is airway narrowing, and reduction in airway inflammation by regular preventive treatment. Adherence to regular treatment reduces the risk of significant asthma attacks in most people with asthma. The focus of asthma management in recent years has been on supporting people with asthma and their healthcare professional to devise a personalised treatment plan that is effective and relatively easy to implement.

The aims of this guideline

The guideline covers children under 5, children and young people aged 5 to 16, and adults aged 17 and over with suspected or diagnosed asthma. The guideline applies to all primary, secondary and community care settings in which NHS-funded care is provided for people with asthma.

The sections on diagnosing and monitoring asthma ( sections 1.1 to 1.4 and 1.13 ) aim to provide clear advice on effectively diagnosing people presenting with new symptoms of suspected asthma and monitoring to ensure optimum asthma control. It is not intended to be used to re-diagnose people who already have an asthma diagnosis.

The sections on managing chronic asthma ( sections 1.5 to 1.12 ) aim to provide clear advice for healthcare professionals and people with asthma to develop a personalised action plan. The plan should support self-management of asthma, and ensure that the person is receiving the best possible treatment for their current level of illness. It focuses on the pharmacological management of chronic asthma, in particular the treatment pathway for people with uncontrolled asthma. It also covers adherence to treatment, risk stratification and self-management.

The guideline does not cover severe, difficult-to-control asthma or the management of acute asthma attacks.

In 2018, new evidence was identified by the NICE surveillance team on increasing the dose of inhaled corticosteroids within a self-management programme in children and young people with asthma. Topic experts, including those who helped to develop the 2017 guideline, agreed that the new evidence could have an impact on the recommendations. This evidence was reviewed and the recommendations in this area updated.

Finding more information and committee details

You can see everything NICE says on this topic in the NICE Pathway on asthma .

To find NICE guidance on related topics, including guidance in development, see the NICE webpage on asthma .

For full details of the evidence and the guideline committees’ discussions, see the 2020 evidence review and 2017 full guidelines . You can also find information about how the guideline was developed , including details of the committees .

NICE has produced tools and resources to help you put this guideline into practice. For general help and advice on putting NICE guidelines into practice, see resources to help you put guidance into practice .

Update information

March 2021: In recommendations 1.10.1 and 1.10.5 , we clarified that approaches to minimising indoor air pollution and reducing exposure to outdoor air pollution should be included in a personalised action plan because pollution can trigger and exacerbate asthma. We added links to the NICE guidelines on air pollution: outdoor air quality and health and indoor air quality at home in recommendation 1.10.1 .

February 2020: We reviewed the evidence on increasing the dose of inhaled corticosteroids within a self-management programme in children and young people with asthma and removed a recommendation. We made new recommendations on self-management in children and young people. These recommendations are marked [2020] .

Recommendations marked [2017] last had an evidence review in 2017. In some cases minor changes have been made to the wording to bring the language and style up to date, without changing the meaning.

Your responsibility : The recommendations in this guideline represent the view of NICE, arrived at after careful consideration of the evidence available. When exercising their judgement, professionals and practitioners are expected to take this guideline fully into account, alongside the individual needs, preferences and values of their patients or the people using their service. It is not mandatory to apply the recommendations, and the guideline does not override the responsibility to make decisions appropriate to the circumstances of the individual, in consultation with them and their families and carers or guardian.

Local commissioners and providers of healthcare have a responsibility to enable the guideline to be applied when individual professionals and people using services wish to use it. They should do so in the context of local and national priorities for funding and developing services, and in light of their duties to have due regard to the need to eliminate unlawful discrimination, to advance equality of opportunity and to reduce health inequalities. Nothing in this guideline should be interpreted in a way that would be inconsistent with complying with those duties.

Commissioners and providers have a responsibility to promote an environmentally sustainable health and care system and should assess and reduce the environmental impact of implementing NICE recommendations wherever possible.

Created: November 29, 2017; Last Update: March 22, 2021.

Cite this Page Asthma: diagnosis, monitoring and chronic asthma management. London: National Institute for Health and Care Excellence (NICE); 2021 Mar 22. (NICE Guideline, No. 80.)
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Related NICE guidance and evidence

Increasing ICS treatment within supported self-management for children and young people: Asthma: diagnosis, monitoring and chronic asthma management: Evidence review A
NICE Guideline 80: Asthma: diagnosis and monitoring of asthma in adults, children and young people
NICE Guideline 80: Chronic asthma: management
2018 exceptional surveillance of asthma: diagnosis, monitoring and chronic asthma management (NICE guideline NG80)
2021 exceptional surveillance of asthma: diagnosis, monitoring and chronic asthma management (NICE guideline NG80)

Supplemental NICE documents

NICE Pathway: Asthma overview (PDF)
NICE Quality Standard QS25: Asthma (PDF)
NICE Quality Standard QS181: Air pollution: outdoor air quality and health (PDF)

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Introducing Apple’s On-Device and Server Foundation Models

At the 2024 Worldwide Developers Conference , we introduced Apple Intelligence, a personal intelligence system integrated deeply into iOS 18, iPadOS 18, and macOS Sequoia.

Apple Intelligence is comprised of multiple highly-capable generative models that are specialized for our users’ everyday tasks, and can adapt on the fly for their current activity. The foundation models built into Apple Intelligence have been fine-tuned for user experiences such as writing and refining text, prioritizing and summarizing notifications, creating playful images for conversations with family and friends, and taking in-app actions to simplify interactions across apps.

In the following overview, we will detail how two of these models — a ~3 billion parameter on-device language model, and a larger server-based language model available with Private Cloud Compute and running on Apple silicon servers — have been built and adapted to perform specialized tasks efficiently, accurately, and responsibly. These two foundation models are part of a larger family of generative models created by Apple to support users and developers; this includes a coding model to build intelligence into Xcode, as well as a diffusion model to help users express themselves visually, for example, in the Messages app. We look forward to sharing more information soon on this broader set of models.

Our Focus on Responsible AI Development

Apple Intelligence is designed with our core values at every step and built on a foundation of groundbreaking privacy innovations.

Additionally, we have created a set of Responsible AI principles to guide how we develop AI tools, as well as the models that underpin them:

Empower users with intelligent tools : We identify areas where AI can be used responsibly to create tools for addressing specific user needs. We respect how our users choose to use these tools to accomplish their goals.
Represent our users : We build deeply personal products with the goal of representing users around the globe authentically. We work continuously to avoid perpetuating stereotypes and systemic biases across our AI tools and models.
Design with care : We take precautions at every stage of our process, including design, model training, feature development, and quality evaluation to identify how our AI tools may be misused or lead to potential harm. We will continuously and proactively improve our AI tools with the help of user feedback.
Protect privacy : We protect our users' privacy with powerful on-device processing and groundbreaking infrastructure like Private Cloud Compute. We do not use our users' private personal data or user interactions when training our foundation models.

These principles are reflected throughout the architecture that enables Apple Intelligence, connects features and tools with specialized models, and scans inputs and outputs to provide each feature with the information needed to function responsibly.

In the remainder of this overview, we provide details on decisions such as: how we develop models that are highly capable, fast, and power-efficient; how we approach training these models; how our adapters are fine-tuned for specific user needs; and how we evaluate model performance for both helpfulness and unintended harm.

Pre-Training

Our foundation models are trained on Apple's AXLearn framework , an open-source project we released in 2023. It builds on top of JAX and XLA, and allows us to train the models with high efficiency and scalability on various training hardware and cloud platforms, including TPUs and both cloud and on-premise GPUs. We used a combination of data parallelism, tensor parallelism, sequence parallelism, and Fully Sharded Data Parallel (FSDP) to scale training along multiple dimensions such as data, model, and sequence length.

We train our foundation models on licensed data, including data selected to enhance specific features, as well as publicly available data collected by our web-crawler, AppleBot. Web publishers have the option to opt out of the use of their web content for Apple Intelligence training with a data usage control.

We never use our users’ private personal data or user interactions when training our foundation models, and we apply filters to remove personally identifiable information like social security and credit card numbers that are publicly available on the Internet. We also filter profanity and other low-quality content to prevent its inclusion in the training corpus. In addition to filtering, we perform data extraction, deduplication, and the application of a model-based classifier to identify high quality documents.

Post-Training

We find that data quality is essential to model success, so we utilize a hybrid data strategy in our training pipeline, incorporating both human-annotated and synthetic data, and conduct thorough data curation and filtering procedures. We have developed two novel algorithms in post-training: (1) a rejection sampling fine-tuning algorithm with teacher committee, and (2) a reinforcement learning from human feedback (RLHF) algorithm with mirror descent policy optimization and a leave-one-out advantage estimator. We find that these two algorithms lead to significant improvement in the model’s instruction-following quality.

Optimization

In addition to ensuring our generative models are highly capable, we have used a range of innovative techniques to optimize them on-device and on our private cloud for speed and efficiency. We have applied an extensive set of optimizations for both first token and extended token inference performance.

Both the on-device and server models use grouped-query-attention. We use shared input and output vocab embedding tables to reduce memory requirements and inference cost. These shared embedding tensors are mapped without duplications. The on-device model uses a vocab size of 49K, while the server model uses a vocab size of 100K, which includes additional language and technical tokens.

For on-device inference, we use low-bit palletization, a critical optimization technique that achieves the necessary memory, power, and performance requirements. To maintain model quality, we developed a new framework using LoRA adapters that incorporates a mixed 2-bit and 4-bit configuration strategy — averaging 3.5 bits-per-weight — to achieve the same accuracy as the uncompressed models.

Additionally, we use an interactive model latency and power analysis tool, Talaria , to better guide the bit rate selection for each operation. We also utilize activation quantization and embedding quantization, and have developed an approach to enable efficient Key-Value (KV) cache update on our neural engines.

With this set of optimizations, on iPhone 15 Pro we are able to reach time-to-first-token latency of about 0.6 millisecond per prompt token, and a generation rate of 30 tokens per second. Notably, this performance is attained before employing token speculation techniques, from which we see further enhancement on the token generation rate.

Model Adaptation

Our foundation models are fine-tuned for users’ everyday activities, and can dynamically specialize themselves on-the-fly for the task at hand. We utilize adapters, small neural network modules that can be plugged into various layers of the pre-trained model, to fine-tune our models for specific tasks. For our models we adapt the attention matrices, the attention projection matrix, and the fully connected layers in the point-wise feedforward networks for a suitable set of the decoding layers of the transformer architecture.

By fine-tuning only the adapter layers, the original parameters of the base pre-trained model remain unchanged, preserving the general knowledge of the model while tailoring the adapter layers to support specific tasks.

We represent the values of the adapter parameters using 16 bits, and for the ~3 billion parameter on-device model, the parameters for a rank 16 adapter typically require 10s of megabytes. The adapter models can be dynamically loaded, temporarily cached in memory, and swapped — giving our foundation model the ability to specialize itself on the fly for the task at hand while efficiently managing memory and guaranteeing the operating system's responsiveness.

To facilitate the training of the adapters, we created an efficient infrastructure that allows us to rapidly retrain, test, and deploy adapters when either the base model or the training data gets updated. The adapter parameters are initialized using the accuracy-recovery adapter introduced in the Optimization section.

Performance and Evaluation

Our focus is on delivering generative models that can enable users to communicate, work, express themselves, and get things done across their Apple products. When benchmarking our models, we focus on human evaluation as we find that these results are highly correlated to user experience in our products. We conducted performance evaluations on both feature-specific adapters and the foundation models.

To illustrate our approach, we look at how we evaluated our adapter for summarization. As product requirements for summaries of emails and notifications differ in subtle but important ways, we fine-tune accuracy-recovery low-rank (LoRA) adapters on top of the palletized model to meet these specific requirements. Our training data is based on synthetic summaries generated from bigger server models, filtered by a rejection sampling strategy that keeps only the high quality summaries.

To evaluate the product-specific summarization, we use a set of 750 responses carefully sampled for each use case. These evaluation datasets emphasize a diverse set of inputs that our product features are likely to face in production, and include a stratified mixture of single and stacked documents of varying content types and lengths. As product features, it was important to evaluate performance against datasets that are representative of real use cases. We find that our models with adapters generate better summaries than a comparable model.

As part of responsible development, we identified and evaluated specific risks inherent to summarization. For example, summaries occasionally remove important nuance or other details in ways that are undesirable. However, we found that the summarization adapter did not amplify sensitive content in over 99% of targeted adversarial examples. We continue to adversarially probe to identify unknown harms and expand our evaluations to help guide further improvements.

In addition to evaluating feature specific performance powered by foundation models and adapters, we evaluate both the on-device and server-based models’ general capabilities. We utilize a comprehensive evaluation set of real-world prompts to test the general model capabilities. These prompts are diverse across different difficulty levels and cover major categories such as brainstorming, classification, closed question answering, coding, extraction, mathematical reasoning, open question answering, rewriting, safety, summarization, and writing.

We compare our models with both open-source models (Phi-3, Gemma, Mistral, DBRX) and commercial models of comparable size (GPT-3.5-Turbo, GPT-4-Turbo) 1 . We find that our models are preferred by human graders over most comparable competitor models. On this benchmark, our on-device model, with ~3B parameters, outperforms larger models including Phi-3-mini, Mistral-7B, and Gemma-7B. Our server model compares favorably to DBRX-Instruct, Mixtral-8x22B, and GPT-3.5-Turbo while being highly efficient.

We use a set of diverse adversarial prompts to test the model performance on harmful content, sensitive topics, and factuality. We measure the violation rates of each model as evaluated by human graders on this evaluation set, with a lower number being desirable. Both the on-device and server models are robust when faced with adversarial prompts, achieving violation rates lower than open-source and commercial models.

Our models are preferred by human graders as safe and helpful over competitor models for these prompts. However, considering the broad capabilities of large language models, we understand the limitation of our safety benchmark. We are actively conducting both manual and automatic red-teaming with internal and external teams to continue evaluating our models' safety.

To further evaluate our models, we use the Instruction-Following Eval (IFEval) benchmark to compare their instruction-following capabilities with models of comparable size. The results suggest that both our on-device and server model follow detailed instructions better than the open-source and commercial models of comparable size.

We evaluate our models’ writing ability on our internal summarization and composition benchmarks, consisting of a variety of writing instructions. These results do not refer to our feature-specific adapter for summarization (seen in Figure 3 ), nor do we have an adapter focused on composition.

The Apple foundation models and adapters introduced at WWDC24 underlie Apple Intelligence, the new personal intelligence system that is integrated deeply into iPhone, iPad, and Mac, and enables powerful capabilities across language, images, actions, and personal context. Our models have been created with the purpose of helping users do everyday activities across their Apple products, and developed responsibly at every stage and guided by Apple’s core values. We look forward to sharing more information soon on our broader family of generative models, including language, diffusion, and coding models.

[1] We compared against the following model versions: gpt-3.5-turbo-0125, gpt-4-0125-preview, Phi-3-mini-4k-instruct, Mistral-7B-Instruct-v0.2, Mixtral-8x22B-Instruct-v0.1, Gemma-1.1-2B, and Gemma-1.1-7B. The open-source and Apple models are evaluated in bfloat16 precision.

Apple Natural Language Understanding Workshop 2023

Earlier this year, Apple hosted the Natural Language Understanding workshop. This two-day hybrid event brought together Apple and members of the academic research community for talks and discussions on the state of the art in natural language understanding.

In this post, we share highlights from workshop discussions and recordings of select workshop talks.

Discover opportunities in Machine Learning.

Our research in machine learning breaks new ground every day.

Work with us

“I saw the NIAID Research Agenda for 2024 H5N1 Influenza and I want to apply for H5N1 research funding, but I can’t find a corresponding notice of funding opportunity. What should I do?”

Funding News Edition: June 20, 2024 See more articles in this edition

Last month, we published the NIAID Research Agenda for 2024 H5N1 Influenza .

NIAID has no notice of funding opportunity (NOFO) or notice of special interest (NOSI) specifically targeting Influenza A/H5N1. Still, you as an interested researcher could prepare and submit an investigator-initiated application in response to a Parent NOFO . We provide advice on how to align your application’s Research Strategy with NIAID’s programmatic priorities in the absence of a solicited initiative at Unsolicited, Investigator-Initiated Research and Draft Specific Aims . For example, you should choose a parent NOFO with the activity code (e.g., R01, R03, or R21) most appropriate to the scope of your planned project.

Note, as well, that NIAID is responding to public health concerns around Influenza A/H5N1 by mobilizing our intramural and extramural-supported research infrastructure, e.g., the Centers for Excellence for Influenza Research and Response (CEIRR) network and the Collaborative Influenza Vaccine Innovation Centers (CIVICs). Central to the NIAID Mission is that we maintain Programs and Networks with capacity to respond appropriately to emerging and re-emerging disease threats.

Email us at [email protected] for help navigating NIAID’s grant and contract policies and procedures.

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Apple Intelligence Preview

AI for the rest of us.

Coming in beta this fall *

Static image of multiple iPhones showing Apple Intelligence features.

Built into your iPhone, iPad, and Mac to help you write, express yourself, and get things done effortlessly.

Draws on your personal context while setting a brand-new standard for privacy in AI.

Write with intelligent new tools. Everywhere words matter.

Apple Intelligence powers new Writing Tools, which help you find just the right words virtually everywhere you write. With enhanced language capabilities, you can summarize an entire lecture in seconds, get the short version of a long group thread, and minimize unnecessary distractions with prioritized notifications.

Explore new features for writing, focus, and communication.

UI for Writing Tools with a text field to enter prompts, buttons for Proofread and Rewrite, different tones of writing voice, and options for summarize, key points, table, and list

Transform how you communicate using intelligent Writing Tools that can proofread your text, rewrite different versions until the tone and wording are just right, and summarize selected text with a tap. Writing Tools are available nearly everywhere you write, including third-party apps.

Notifications list on an iPhone highlights Most Important at the top of the stack

Priority notifications appear at the top of the stack, letting you know what to pay attention to at a glance. And notifications are summarized, so you can scan them faster.

iPhone shows inbox in Mail app with important messages at the top and highlighted a different color

Priority messages in Mail elevate time-sensitive messages to the top of your inbox — like an invitation that has a deadline today or a check-in reminder for your flight this afternoon.

An email in the Mail app is shown with a summary you can read at the top.

Tap to reveal a summary of a long email in the Mail app and cut to the chase. You can also view summaries of email right from your inbox.

Phone app is shown with a new record function on a live call. A second iPhone shows a summary of the call based on live audio transcription.

Just hit record in the Notes or Phone apps to capture audio recordings and transcripts. Apple Intelligence generates summaries of your transcripts, so you can get to the most important information at a glance.

iPhone with Reduce Notifications Focus enabled shows a single notification marked "maybe important."

Reduce Interruptions is an all-new Focus that understands the content of your notifications and shows you the ones that might need immediate attention, like a text about picking up your child from daycare later today.

Smart Reply options in the Mail app are shown on an iPhone.

Use a Smart Reply in Mail to quickly draft an email response with all the right details. Apple Intelligence can identify questions you were asked in an email and offer relevant selections to include in your response. With a few taps you’re ready to send a reply with key questions answered.

Delightful images created just for you.

Apple Intelligence enables delightful new ways to express yourself visually. Create fun, original images and brand-new Genmoji that are truly personal to you. Turn a rough sketch into a related image that complements your notes with Image Wand. And make a custom memory movie based on the description you provide.

Custom images are shown in the Message app and the Image Wand feature in Notes is shown on an iPad.

Create expressive images, unique Genmoji, and custom memory movies.

UI of the Image Playground experience shows a colorful image of a brain surrounded by classical instruments and music notation with suggestions for more elements to add to the image

Produce fun, original images in seconds with the Image Playground experience right in your apps. Create an entirely new image based on a description, suggested concepts, and even a person from your Photos library. You can easily adjust the style and make changes to match a Messages thread, your Freeform board, or a slide in Keynote.

Image Playground app is shown on iPad. A custom image in the center is surrounded by different ideas and keywords used to make it.

Experiment with different concepts and try out image styles like animation, illustration, and sketch in the dedicated Image Playground app . Create custom images to share with friends in other apps or on social media.

Preview of a custom Genmoji of someone named Vee based on the prompt, race car driver

Make a brand-new Genmoji right in the keyboard to match any conversation. Provide a description to see a preview, and adjust your description until it’s perfect. You can even pick someone from your Photos library and create a Genmoji that looks like them.

A hand holding Apple Pencil draws a circle around a sketch in the Notes app on iPad.

Image Wand can transform your rough sketch into a related image in the Notes app. Use your finger or Apple Pencil to draw a circle around your sketch, and Image Wand will analyze the content around it to produce a complementary visual. You can even circle an empty space, and Image Wand will use the surrounding context to create a picture.

Cover of a custom new memory based on the description entered in the text field in the Photos app

Create a custom memory movie of the story you want to see, right in Photos. Enter a description, and Apple Intelligence finds the best photos and videos that match. It then crafts a storyline with unique chapters based on themes it identifies and arranges your photos into a movie with its own narrative arc.

A grid of photos based on the search prompt Katie with stickers on her face

Search for photos and videos in the Photos app simply by describing what you’re looking for. Apple Intelligence can even find a particular moment in a video clip that fits your search description and take you right to it.

A hand taps an object in the background of a photo on iPhone to highlight what to clean up

Remove distractions in your photos with the Clean Up tool in the Photos app. Apple Intelligence identifies background objects so you can remove them with a tap and perfect your shot — while staying true to the original image.

The start of a new era for Siri.

Siri draws on Apple Intelligence for all-new superpowers. With an all-new design, richer language understanding, and the ability to type to Siri whenever it’s convenient for you, communicating with Siri is more natural than ever. Equipped with awareness of your personal context, the ability to take action in and across apps, and product knowledge about your devices’ features and settings, Siri will be able to assist you like never before.

Mac, iPad, and iPhone are shown with new Siri features powered by Apple Intelligence

Discover an even more capable, integrated, personal Siri.

A light, colorful glow is barely visible around the edge of an iPhone showing the home screen

Siri has an all-new design that’s even more deeply integrated into the system experience, with an elegant, glowing light that wraps around the edge of your screen.

A text field at the top of keyboard in iPhone says Ask Siri

With a double tap on the bottom of your iPhone or iPad screen, you can type to Siri from anywhere in the system when you don’t want to speak out loud.

An iPhone is shown with step-by-step guidelines on how to schedule a text message to send later

Tap into the expansive product knowledge Siri has about your devices’ features and settings. You can ask questions when you’re learning how to do something new on your iPhone, iPad, and Mac, and Siri can give you step-by-step directions in a flash.

Siri, set an alarm for — oh wait no, set a timer for 10 minutes. Actually, make that 5.

Richer language understanding and an enhanced voice make communicating with Siri even more natural. And when you refer to something you mentioned in a previous request, like the location of a calendar event you just created, and ask ”What will the weather be like there?” Siri knows what you’re talking about.

A notification in the Apple TV+ app reminds you that a contact shared a show recommendation with you

Apple Intelligence empowers Siri with onscreen awareness , so it can understand and take action with things on your screen. If a friend texts you their new address, you can say “Add this address to their contact card,” and Siri will take care of it.

Snippets of information like calendar events, photos, and notes shows the many sources Siri can draw from

Awareness of your personal context enables Siri to help you in ways that are unique to you. Can’t remember if a friend shared that recipe with you in a note, a text, or an email? Need your passport number while booking a flight? Siri can use its knowledge of the information on your device to help find what you’re looking for, without compromising your privacy.

Photos library is shown on an iPhone along with a search description. A second iPhone is open to a single photo favorited based on the search. A third iPhone shows the photo incorporated into a note in the Notes app.

Seamlessly take action in and across apps with Siri. You can make a request like “Send the email I drafted to April and Lilly” and Siri knows which email you’re referencing and which app it’s in. And Siri can take actions across apps, so after you ask Siri to enhance a photo for you by saying “Make this photo pop,” you can ask Siri to drop it in a specific note in the Notes app — without lifting a finger.

Great powers come with great privacy.

Apple Intelligence is designed to protect your privacy at every step. It’s integrated into the core of your iPhone, iPad, and Mac through on-device processing. So it’s aware of your personal information without collecting your personal information. And with groundbreaking Private Cloud Compute, Apple Intelligence can draw on larger server-based models, running on Apple silicon, to handle more complex requests for you while protecting your privacy.

Private Cloud Compute

Your data is never stored
Used only for your requests
Verifiable privacy promise

ChatGPT, seamlessly integrated.

With ChatGPT from OpenAI integrated into Siri and Writing Tools, you get even more expertise when it might be helpful for you — no need to jump between tools. Siri can tap into ChatGPT for certain requests, including questions about photos or documents. And with Compose in Writing Tools, you can create and illustrate original content from scratch.

You control when ChatGPT is used and will be asked before any of your information is shared. Anyone can access ChatGPT for free, without creating an account. ChatGPT subscribers can connect accounts to access paid features within these experiences.

The Compose in Writing Tools feature is shown on a MacBook

New possibilities for your favorite apps.

New App Intents, APIs, and frameworks make it incredibly easy for developers to integrate system-level features like Siri, Writing Tools, and Image Playground into your favorite apps.

Learn more about developing for Apple Intelligence

Apple Intelligence is compatible with these devices.

Apple Intelligence is free to use and will initially be available in U.S. English. Coming in beta this fall. *

iPhone 15 Pro Max A17 Pro
iPhone 15 Pro A17 Pro
iPad Pro M1 and later
iPad Air M1 and later
MacBook Air M1 and later
MacBook Pro M1 and later
iMac M1 and later
Mac mini M1 and later
Mac Studio M1 Max and later
Mac Pro M2 Ultra

IMAGES

Asthma-COPD Overlap Information Paper
Introduction to Asthma
Asthma in Adults: The Great Asthma Myth Essay [1283 words]
Asthma research paper outline
Articles on Asthma from Three Websites Free Essay Example
Asthma Essay [821 words]

VIDEO

How to Read Research Paper Quickly
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كيفية كتابة بحث How to write research paper
When your supervisors ask you to write a journal paper after finishing your PhD #shortsfeed #shorts
How to write research paper with ai tools

COMMENTS

Treatment strategies for asthma: reshaping the concept of asthma management
Background. Asthma, a major global health problem affecting as many as 235 million people worldwide [], is a common, non-communicable, and variable chronic disease that can result in episodic or persistent respiratory symptoms (e.g. shortness of breath, wheezing, chest tightness, cough) and airflow limitation, the latter being due to bronchoconstriction, airway wall thickening, and increased ...
Epidemiology of Asthma in Children and Adults
We have summarized the evidence on asthma trends, environmental determinants, and long-term impacts while comparing these epidemiological features across childhood asthma and adult asthma. While asthma incidence and prevalence are higher in children, morbidity, and mortality are higher in adults. Childhood asthma is more common in boys while ...
Epidemiology and risk factors for asthma
The diagnosis of asthma has increased exponentially in recent decades parallel with urbanization and industrialization, and is now considered a global public health issue. According to the Global Burden of Disease report for 2015, asthma was the most common chronic respiratory disorder, with an estimated prevalence of 358 million cases [1]. Assessment of the scope and burden of disease is ...
Advances and recent developments in asthma in 2020
Abstract. In this review, we discuss recent publications on asthma and review the studies that have reported on the different aspects of the prevalence, risk factors and prevention, mechanisms, diagnosis, and treatment of asthma. Many risk and protective factors and molecular mechanisms are involved in the development of asthma.
Asthma
Asthma is one of the most common chronic non-communicable diseases worldwide and is characterised by variable airflow obstruction, causing dyspnoea and wheezing. Highly effective therapies are available; asthma morbidity and mortality have vastly improved in the past 15 years, and most patients can attain good asthma control. However, undertreatment is still common, and improving patient and ...
Improving primary care management of asthma: do we know what really
Introduction. Asthma is a common chronic condition that is estimated to affect 339 million people worldwide 1,2.Despite major advances in asthma treatment and the availability of both global 2 and national guidance, asthma continues to cause a substantial burden in terms of both direct and indirect costs 1.In 2016, estimated worldwide asthma deaths were 420,000 1 and although there have been ...
Asthma in Adults
The prevalence of asthma in adults in the United States is approximately 7.7%. 1 It is one of the most common chronic, noncommunicable diseases in the country and worldwide. 1,2 Among U.S. adults ...
Diagnosis and Management of Asthma in Adults: A Review
Abstract. Importance: Asthma affects about 7.5% of the adult population. Evidence-based diagnosis, monitoring, and treatment can improve functioning and quality of life in adult patients with asthma. Observations: Asthma is a heterogeneous clinical syndrome primarily affecting the lower respiratory tract, characterized by episodic or persistent ...
Update in Adult Asthma 2020
Longitudinal studies of adult asthma and airway obstruction have shed light on the importance of considering occupational and environmental exposures in a patient's evaluation. Trends in work-related asthma (WRA) were evaluated using data from the Michigan surveillance program from 1988 to 2018 . Although there was a decreased overall ...
(PDF) An Overview of Asthma and its treatment
Asthma is a disorder characterized by chronic airway inflammation, air way hypersensitivity to a variety of. stimuli, and airway obstruction. It is at least partially reversible, either ...
Full article: An update on asthma diagnosis
Introduction. Asthma is the most common chronic respiratory disease affecting millions of people of all ages across the globe (Citation 1-6).The average global prevalence ranges between 5-10% (Citation 2).Traditionally, asthma diagnosis was based on the history and the response to a trial of various treatments, but emerging evidence shows that under the umbrella of asthma, several subtypes ...
The Burden of Asthma in the United States
Asthma imposes a growing burden on society in terms of morbidity, quality of life, and healthcare costs. An increasing body of evidence describes the rising prevalence of asthma within the United States and around the world (1-3).Data from the National Health Interview Study suggest that in the United States alone, the number of cases of asthma reported since 1980 has increased by 75% and ...
Advances and recent developments in asthma in 2020
According to an EAACI position paper in 2019, biomarkers for the clinical and inflammatory phenotype of asthma were summarized as follows (1) type 2 asthma: (a) ... Asthma research produces up to 9000 publications per year and represents one of the most rapidly developing areas. Most of the novel developments of the last year focus in the areas ...
Articles
Long-term follow-up studies of adults with well-characterized asthma are sparse. We aimed to explore static lung volumes and diffusion capacity after 30 + years with asthma. Conrad Uldall Becker Schultz, Oliver Djurhuus Tupper and Charlotte Suppli Ulrik. Asthma Research and Practice 2022 8 :4.
Asthma: a case study, review of pathophysiology, and management
Purpose: To review the pathophysiology of asthma, present a case study, and provide management strategies for treating this common, yet complex disorder in children and adults. Data sources: Selected clinical guidelines, clinical articles, and research studies. Conclusions: Asthma is a chronic inflammatory airway disorder with acute exacerbations that currently affects approximately 14 million ...
Innate immune responses are increased in children with acute asthma
In acute asthma exacerbation, innate immune pathways remained increased while adaptive immune responses related to T helper cells are blunted and are independent of trigger or asthma severity. Our novel findings highlight the need to identify new therapies to target persistent innate immune responses to improve outcomes in acute asthma.
Asthma: Pathophysiology and Diagnosis
Introduction. Although asthma is a common disorder affecting approximately 7.8% of the United States population (Schiller et al. 2006) or 23 million Americans, the pathogenesis of this disease remains to be fully elucidated.Extensive research over the last few decades has yielded a better understanding of asthma.
Artificial intelligence techniques in asthma: a systematic review and
Artificial intelligence (AI) when coupled with large amounts of well characterised data can yield models that are expected to facilitate clinical practice and contribute to the delivery of better care, especially in chronic diseases such as asthma. The purpose of this paper is to review the utilisation of AI techniques in all aspects of asthma research, i.e. from asthma screening and diagnosis ...
Latest asthma Research Papers/Journal Articles
Effectiveness of Asthma Home Management Manual and Low-Cost Air Filter on Quality of Life Among Asthma Adults: A 3-Arm Randomized Controlled Trial. Muanprasong S, Aqilah S, Hermayurisca F, Taneepanichskul N. Journal of Multidisciplinary Healthcare 2024, 17:2613-2622. Published Date: 24 May 2024. Original Research.
Asthma: Epidemiological Analysis and Care Plan Essay
Introduction. Asthma is an illness that disproportionately affects many adults and children globally. In 2019, 262 million people had asthma, causing 461 000 deaths (WHO, 2020). Scholars have done asthma-related research to provide information on causes, symptoms, therapies, and asthma mitigation. This study will describe asthma as a chronic ...
A text-based conversational agent for asthma support: Mixed-methods
An initial protocol paper outlined a study plan for developing and evaluating the feasibility of a chatbot designed to assist patients with asthma with risk self-assessment and self-management. 21 The user research and co-design phase of the project, which involved respiratory specialist physicians, asthma nurses, representatives from an asthma ...
Asthma Essay With Conclusions
Conclusion. In conclusion asthma can be described as a chronic respiratory condition which can be identified by breathing difficulty, wheezing, cough and chest tightness. Narrowing and swelling of the airways and increased mucus production are the major episodes looked for to establish an asthma condition.
173 Asthma Topic Ideas to Write about & Essay Samples
The Nature and Control of Non-Communicable Disease - Asthma. Asthma is caused due to the inflammation of the airways which in turn induces cough, wheezing, breathlessness and a feeling of tightness in the chest. Application: Asthma. The features of the air passage include the bronchi, alveoli and the bronchioles.
Improving primary care management of asthma: do we know what ...
Asthma is a common chronic condition that is estimated to affect 339 million people worldwide 1,2.Despite major advances in asthma treatment and the availability of both global 2 and national ...
Yeast-fermented bread shows promise in preventing asthma symptoms
Please use one of the following formats to cite this article in your essay, paper or report: APA. Sai Lomte, Tarun. (2024, June 20). Yeast-fermented bread shows promise in preventing asthma symptoms.
Asthma: diagnosis, monitoring and chronic asthma management
The committee's full set of research recommendations is detailed in the 2017 full guideline on asthma: diagnosis and monitoring and the 2017 full guideline on chronic asthma management. As part of the 2020 update, the guideline committee made 1 new research recommendation on managing asthma within a self-management programme for children and ...
Introducing Apple's On-Device and Server Foundation Models
Figure 1: Modeling overview for the Apple foundation models. Pre-Training. Our foundation models are trained on Apple's AXLearn framework, an open-source project we released in 2023.It builds on top of JAX and XLA, and allows us to train the models with high efficiency and scalability on various training hardware and cloud platforms, including TPUs and both cloud and on-premise GPUs.
"I saw the NIAID Research Agenda for 2024 H5N1 Influenza and I want to
Note, as well, that NIAID is responding to public health concerns around Influenza A/H5N1 by mobilizing our intramural and extramural-supported research infrastructure, e.g., the Centers for Excellence for Influenza Research and Response (CEIRR) network and the Collaborative Influenza Vaccine Innovation Centers (CIVICs).
Apple Intelligence Preview
Apple Intelligence powers new Writing Tools, which help you find just the right words virtually everywhere you write. With enhanced language capabilities, you can summarize an entire lecture in seconds, get the short version of a long group thread, and minimize unnecessary distractions with prioritized notifications. ...
Rethinking English essay scores: The argument for ...
To get high scores at essay writing tests, learners of English as a foreign language need to focus on good arguments more than on complex grammar. The finding challenges conventional approaches to ...

Psychological distress and associated factors among asthmatic patients in Southern, Ethiopia, 2021

Retrospective assessment of a collaborative digital asthma program for Medicaid-enrolled children in southwest Detroit: reductions in short-acting beta-agonist (SABA) medication use

Nonadherence to antiasthmatic medications and its predictors among asthmatic patients in public hospitals of Bahir Dar City, North West Ethiopia: using ASK-12 tool

The hen and the egg question in atopic dermatitis: allergy or eczema comes first

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Monoclonal antibodies targeting small airways: a new perspective for biological therapies in severe asthma

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Static lung volumes and diffusion capacity in adults 30 years after being diagnosed with asthma

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A serological biomarker of type I collagen degradation is related to a more severe, high neutrophilic, obese asthma subtype

Adherence to inhalers and associated factors among adult asthma patients: an outpatient-based study in a tertiary hospital of Rajshahi, Bangladesh

The link between atopic dermatitis and asthma- immunological imbalance and beyond

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Determinants of asthma in Ethiopia: age and sex matched case control study with special reference to household fuel exposure and housing characteristics

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Self-reported vs. objectively assessed adherence to inhaled corticosteroids in asthma

Association between prevalence of obstructive lung disease and obesity: results from The Vermont Diabetes Information System

Changes in quantifiable breathing pattern components predict asthma control: an observational cross-sectional study

The role of leukotriene modifying agent treatment in neuropsychiatric events of elderly asthma patients: a nested case control study

Asthma and stroke: a narrative review

Comparison of dental caries (DMFT and DMFS indices) between asthmatic patients and control group in Iran: a meta-analysis

ICS/formoterol in the management of asthma in the clinical practice of pulmonologists: an international survey on GINA strategy

Sustainability of residential environmental interventions and health outcomes in the elderly

Non-adherence to inhaled medications among adult asthmatic patients in Ethiopia: a systematic review and meta-analysis

The outcome of COVID-19 among the geriatric age group in African countries: protocol for a systematic review and meta-analysis

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Disease control in patients with asthma and respiratory symptoms (wheezing, cough) during sleep

The burden, admission, and outcomes of COVID-19 among asthmatic patients in Africa: protocol for a systematic review and meta-analysis

The healthcare seeking behaviour of adult patients with asthma at Chitungwiza Central Hospital, Zimbabwe

Continuous versus intermittent short-acting β2-agonists nebulization as first-line therapy in hospitalized children with severe asthma exacerbation: a propensity score matching analysis

Patient perceived barriers to exercise and their clinical associations in difficult asthma

Asthma management with breath-triggered inhalers: innovation through design

A nationwide study of asthma correlates among adolescents in Saudi Arabia

A comparison of biologicals in the treatment of adults with severe asthma – real-life experiences

Determinants of Acute Asthma Attack among adult asthmatic patients visiting hospitals of Tigray, Ethiopia, 2019: case control study

Determinants of non-adherence to inhaled steroids in adult asthmatic patients on follow up in referral hospital, Ethiopia: cross-sectional study

Development of a framework for increasing asthma awareness in Chitungwiza, Zimbabwe

Epidemiology and utilization of primary health care services in Qatar by asthmatic children 5–12 years old: secondary data analysis 2016–2017

Is asthma in the elderly different? Functional and clinical characteristics of asthma in individuals aged 65 years and older

Factors associated with exacerbations among adults with asthma according to electronic health record data

What is safe enough - asthma in pregnancy - a review of current literature and recommendations

Biomarkers in asthma: state of the art

Exhaled biomarkers in childhood asthma: old and new approaches

Assessment of predictors for acute asthma attack in asthmatic patients visiting an Ethiopian hospital: are the potential factors still a threat?

Effect of adjusting the combination of budesonide/formoterol on the alleviation of asthma symptoms

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Latest Research on Asthma

Healthcare Resource Utilization Associated with Intermittent Oral Corticosteroid Prescribing Patterns in Asthma

Baseline Systemic Oral Corticosteroid Use in Patients with Asthma Initiating Dupilumab Treatment in the Real World: From the RAPID Global Registry

Research on the Mechanism and Application of Acupuncture Therapy for Asthma: A Review

Factors Affecting Usage of a Digital Asthma Monitoring Application by Old-Age Asthmatics Living in Inner Central Portugal

Effectiveness of Asthma Home Management Manual and Low-Cost Air Filter on Quality of Life Among Asthma Adults: A 3-Arm Randomized Controlled Trial

Impact of Anxiety and Depression on the Level of Asthma Control Among Jordanian Adults with Asthma

The Efficacy & Molecular Mechanisms of a Terpenoid Compound Ganoderic Acid C1 on Corticosteroid-Resistant Neutrophilic Airway Inflammation: In vivo and in vitro Validation

Elevated Saliva Pepsin Concentration as a Risk Factor for Asthma in Children with Allergic Rhinitis: A Preliminary Study

Bronchial Thermoplasty Improves Ventilation Heterogeneity Measured by Functional Respiratory Imaging in Severe Asthma

Costs of Air Pollution in California’s San Joaquin Valley: A Societal Perspective of the Burden of Asthma on Emergency Departments and Inpatient Care

Usefulness of Computed Tomography for Evaluating the Effects of Bronchial Thermoplasty in Japanese Patients with Severe Asthma