Clinical and inflammatory characteristics of Asthma-COPD overlap in workers with occupational asthma
Bibliographic record
Abstract
INTRODUCTION: Although Asthma-COPD Overlap (ACO) has been described among populations of subjects with COPD or asthma, ACO has never been described among a population of subjects with occupational asthma (OA). OBJECTIVES: The aims of this study were to: 1. identify ACO in a population of subjects with OA; and 2. compare the clinical characteristics between ACO and OA. METHODS: This retrospective study included all subjects diagnosed with OA between 2000 and 2017 in an OA referral center. Occupational Asthma-COPD Overlap (OACO) was defined as post-bronchodilator FEV1/FVC < 70% and smoking history ≥ 10 pack-years, along with a diagnosis of OA. RESULTS: Three hundred and four subjects were included, 262 (86.2%) were classified as OA and 42 (13.8%) as OACO. OA subjects presented higher sputum eosinophil counts after a specific-inhalation challenge than subjects with OACO (median [IQR]: 6.5 [17.0] vs 2.3 [3.5]). After adjusting for confounding factors, subjects with OACO were older (OR: 1.10 [1.05; 1.14]) and were taking higher doses of inhaled corticosteroids than OA subjects (OR, 5.20 [1.77; 16.48]). Subjects with OACO were less often atopic than OA subjects (OR, 0.19 [0.07; 0.62]). CONCLUSIONS: Subjects with OACO constitute a distinct clinical and inflammatory phenotype from subjects with OA.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".