How Much Does the Asthma Outcome Definition Matter?

Abstract Background Asthma represents a syndrome for which our understanding of the molecular processes underlying discrete sub-diseases (i.e., endotypes), beyond atopic asthma, is limited. The public health needs to characterize etiology-associated endotype risks is becoming urgent. In particular, the roles of polyaromatic hydrocarbon (PAH), globally distributed combustion by-products, toward the two known endotypes – T helper 2 cell high (Th2) or T helper 2 cell low (non-Th2) – warrants clarification. Objectives To explain ambient B[a]P association with non-atopic asthma (i.e., a proxy of non-Th2 endotype) is markedly different from that with atopic asthma (i.e., a proxy for Th2-high endotype). Methods In a case-control study, we compare the non-atopic as well as atopic asthmatic boys and girls against their respective controls in terms of the ambient Benzo[a]pyrene concentration nearest to their home, plasma 15-Ft2-isoprostane (15-Ft2-isoP), urinary 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG), and lung function deficit. We repeated the analysis for i) dichotomous asthma outcome and ii) multinomial asthma—overweight/obese (OV/OB) combined outcomes. Results The non-atopic asthma cases are associated with a significantly higher median B[a]P (11.16 ng/m3) compared to that in the non-atopic controls (3.83 ng/m3; P-value < 0.001). In asthma-OV/OB stratified analysis, the non-atopic girls with lean and OV/OB asthma are associated with a step-wisely elevated B[a]P (median,11.16 and 18.00 ng/m3, respectively), compared to the non-atopic lean control girls (median, 4.28 ng/m3, P-value < 0.001). In contrast, atopic asthmatic children (2.73 ng/m3) are not associated with a significantly elevated median B[a]P, compared to the atopic control children (2.60 ng/m3; P-value > 0.05). Based on the logistic regression model, on ln-unit increate in B[a]P is associated with 4.7-times greater odds (95% CI, 1.9–11.5, P = 0.001) of asthma among the non-atopic boys. The same unit increase in B[a]P is associated with 44.8-times greater odds (95% CI, 4.7–428.2, P = 0.001) among the non-atopic girls after adjusting for urinary Cotinine, lung function deficit, 15-Ft2-isoP, and 8-oxodG. Conclusions Ambient B[a]P is robustly associated with non-atopic asthma, while it has no clear associations with atopic asthma among lean children. Furthermore, lung function deficit, 15-Ft2-isoP, and 8-oxodG are associated with profound alteration of B[a]P-asthma associations among the non-atopic children.

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Association between antioxidant vitamins and asthma outcome measures: systematic review and meta-analysis

Thorax ◽

10.1136/thx.2008.101469 ◽

2009 ◽

Vol 64 (7) ◽

pp. 610-619 ◽

Cited By ~ 104

Author(s):

S Allen ◽

J R Britton ◽

J A Leonardi-Bee

Keyword(s):

Systematic Review ◽

Outcome Measures ◽

Meta Analysis ◽

Antioxidant Vitamins ◽

Asthma Outcome

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Implications of prognostic pessimism in patients with chronic obstructive pulmonary disease (COPD) or asthma admitted to intensive care in the UK within the COPD and asthma outcome study (CAOS): multicentre observational cohort study

BMJ ◽

10.1136/bmj.39371.524271.55 ◽

2007 ◽

Vol 335 (7630) ◽

pp. 1132 ◽

Cited By ~ 73

Author(s):

Martin J Wildman ◽

Colin Sanderson ◽

Jayne Groves ◽

Barnaby C Reeves ◽

Jon Ayres ◽

...

Keyword(s):

Chronic Obstructive Pulmonary Disease ◽

Cohort Study ◽

Intensive Care ◽

Observational Cohort Study ◽

Chronic Obstructive ◽

Outcome Study ◽

Obstructive Pulmonary Disease ◽

Asthma Outcome ◽

Observational Cohort ◽

The Uk

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Predicting Asthma Outcome Using Partial Least Square Regression and Artificial Neural Networks

Advances in Artificial Intelligence ◽

10.1155/2013/435321 ◽

2013 ◽

Vol 2013 ◽

pp. 1-7 ◽

Cited By ~ 6

Author(s):

E. Chatzimichail ◽

E. Paraskakis ◽

A. Rigas

Keyword(s):

Neural Networks ◽

Artificial Neural Networks ◽

Clinical Decision Making ◽

Persistent Asthma ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Least Square Regression ◽

Asthma Outcome ◽

Artificial Neural

The long-term solution to the asthma epidemic is believed to be prevention and not treatment of the established disease. Most cases of asthma begin during the first years of life; thus the early determination of which young children will have asthma later in their life counts as an important priority. Artificial neural networks (ANN) have been already utilized in medicine in order to improve the performance of the clinical decision-making tools. In this study, a new computational intelligence technique for the prediction of persistent asthma in children is presented. By employing partial least square regression, 9 out of 48 prognostic factors correlated to the persistent asthma have been chosen. Multilayer perceptron and probabilistic neural networks topologies have been investigated in order to obtain the best prediction accuracy. Based on the results, it is shown that the proposed system is able to predict the asthma outcome with a success of 96.77%. The ANN, with which these high rates of reliability were obtained, will help the doctors to identify which of the young patients are at a high risk of asthma disease progression. Moreover, this may lead to better treatment opportunities and hopefully better disease outcomes in adulthood.

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Asthma Education, Action Plans, Psychosocial Issues and Adherence

Canadian Respiratory Journal ◽

10.1155/1999/413547 ◽

1999 ◽

Vol 6 (3) ◽

pp. 273-280 ◽

Cited By ~ 21

Author(s):

John Kolbe

Keyword(s):

Psychological Factors ◽

Management Strategies ◽

Psychosocial Issues ◽

Action Plans ◽

Asthma Education ◽

Psychological Issues ◽

Asthma Morbidity ◽

Flow Monitoring ◽

Adherence To Medication ◽

Asthma Outcome

This article deals with four separate but not disparate topics. The first section discusses asthma education, reviews the current literature and attempts to challenge some of the dogma that is associated with this area. Knowledge alone does not guarantee appropriate behaviour, due to a variety of adverse socioeconomic and psychological factors that need to be considered for each patient. Action plans and peak flow monitoring have both been disappointing in terms of reducing asthma morbidity; the former needs to be individualized, and the latter may be useful in specific situations. Space precludes an in-depth discussion of psychological issues and adherence, but an attempt has been made to address salient issues, particularly related to the first two topics. Psychological factors, especially anxiety, play an important role in asthma outcome. Adherence to medication prescriptions and other management strategies need to be taken into account when an individual’s treatment program is planned.

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Comorbidities associated with severe asthma

Journal of Precision Respiratory Medicine ◽

10.2500/jprm.2019.190006 ◽

2019 ◽

Vol 2 (1) ◽

pp. 5-9

Author(s):

Gayatri B. Patel ◽

Anju T. Peters

Keyword(s):

Severe Asthma ◽

Care Utilization ◽

Adequate Treatment ◽

Obstructive Sleep ◽

Asthma Outcome ◽

Control Asthma ◽

Relationship Of ◽

The Impact ◽

The Relationship

Background: Severe asthma can be a challenging disease to manage by the provider and by the patient, supported by evidence of increased health-care utilization by this population. Patients with severe asthma should be screened for comorbidities because these often contribute to poorly controlled asthma. The impact of comorbidities, however, are not completely understood. Objective: To review common comorbidities and their impact on severe asthma. Methods: A review of relevant clinical research studies that examined comorbidities in severe or difficult-to-treat asthma. Results: A number of comorbid diseases, including rhinitis, rhinosinusitis, gastroesophageal reflux, and obstructive sleep apnea, are associated with severe or difficult-to-treat asthma. If present and untreated, these conditions may adversely affect asthma control, quality of life, and/or lung function, despite adequate treatment with step-up asthma controller therapy. Conclusion: Treatable comorbidities are associated with severe and difficult-to-control asthma. Failure to recognize these comorbidities may divert appropriate care and increase disease burden. Assessment and management of these risk factors may contribute to improved asthma outcome; however, more investigation is needed to understand the relationship of comorbidities and asthma due to inconsistency in the findings.

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