Global burden of allergic bronchopulmonary aspergillosis with asthma and its complication chronic pulmonary aspergillosis in adults
Bibliographic record
Abstract
Allergic bronchopulmonary aspergillosis (ABPA) complicates asthma and may lead to chronic pulmonary aspergillosis (CPA) yet global burdens of each have never been estimated. Antifungal therapy has a place in the management of ABPA and is the cornerstone of treatment in CPA, reducing morbidity and probably mortality. We used the country-specific prevalence of asthma from the Global Initiative for Asthma (GINA) report applied to population estimates to calculate adult asthma cases. From five referral cohorts (China, Ireland, New Zealand, Saudi Arabia and South Africa), we estimated the prevalence of ABPA in adults with asthma at 2.5% (range 0.72-3.5%) (scoping review). From ABPA case series, pulmonary cavitation occurred in 10% (range 7-20%), allowing an estimate of CPA prevalence worldwide using a deterministic scenario-based model. Of 193 million adults with active asthma worldwide, we estimate that 4,837,000 patients (range 1,354,000-6,772,000) develop ABPA. By WHO region, the ABPA burden estimates are: Europe, 1,062,000; Americas, 1,461,000; Eastern Mediterranean, 351,000; Africa, 389,900; Western Pacific, 823,200; South East Asia, 720,400. We calculate a global case burden of CPA complicating ABPA of 411,100 (range 206,300-589,400) at a 10% rate with a 15% annual attrition. The global burden of ABPA potentially exceeds 4.8 million people and of CPA complicating ABPA ˜ 400,000, which is more common than previously appreciated. Both conditions respond to antifungal therapy justifying improved case detection. Prospective population and clinical cohort studies are warranted to more precisely ascertain the frequency of ABPA and CPA in different locations and ethnic groups and validate the model inputs.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".