Targeted literature review: burden of disease associated with severe and uncontrolled asthma in France, Germany, Italy, Spain and the UK
Bibliographic record
Abstract
Introduction: Severe and uncontrolled asthma are associated with high disease burden. Objective: To summarize the disease burden (clinical, humanistic, economic) associated with severe and uncontrolled asthma in France, Germany, Italy, Spain and the UK. Methods: We conducted targeted searches of Medline, Embase, ScHARRHUD and websites of governmental bodies and key asthma agencies. Included studies reported relevant data in populations with moderate to severe or uncontrolled asthma in France, Germany, Italy, Spain or the UK. Results: Of 27 relevant articles, we prioritized 11 (France [1], Germany [1], Italy [2] Spain [2], UK [2], multiple regions [3]) for summary based on recency of publication, sample size and GINA-defined asthma severity. Outcomes assessed did not vary significantly by country. Over a 1-year period, 56 – 78% of patients with severe asthma experienced an exacerbation. Severe asthma was associated with high comorbidity burden (allergic rhinitis [21 – 62%], nasal polyps [13 – 30%], atopic dermatitis [9 – 19%]) and high systemic corticosteroid use (≤ 59%). Uncontrolled asthma was associated with poor quality of life, increased healthcare utilization, and higher direct and indirect costs to the individual countryʼs healthcare system than controlled asthma. Conclusion: Severe and uncontrolled asthma are associated with high disease burden in the assessed countries. Further research is needed to quantify burden within severe asthma phenotypes and how this affects patients. When asked to comment, Tonya Winders (president, GAAPP patient group) said “Patients with severe asthma live with daily limitations and frustrations like, social isolation”. Publication History Article published online: 30 April 2021 © 2021. Thieme. All rights reserved. Georg Thieme Verlag KG Rüdigerstraße 14, 70469 Stuttgart, Germany
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.018 | 0.019 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".