Blood eosinophil guided prednisolone therapy for exacerbations of COPD: a further analysis
Bibliographic record
Abstract
To the Editor: Exacerbations of chronic obstructive pulmonary disease (COPD) are associated with significant morbidity and mortality [1]. Current guidelines advocate the use of systemic corticosteroids in addition to antibiotics to treat an exacerbation [2, 3], but these treatments are not universally effective and are not without harm [4]. Individualised treatment may, therefore, be an advance. Recently we showed that patients with a peripheral blood eosinophil count of ≥2% at the onset of an outpatient managed exacerbation respond promptly and completely to prednisolone, whereas those with a count of <2% had a higher rate of treatment failure compared with placebo [5]. Whether these findings can be replicated in a larger population, including patients hospitalised with exacerbations of COPD remains unclear. We set out to address these questions in a further analysis of randomised controlled studies comparing outcomes in patients with exacerbations of COPD treated with prednisolone or non-prednisolone (placebo or equivalent). We investigated the rates of treatment failures in patients stratified by the peripheral blood eosinophil count measured at the time of exacerbation. A literature search of the Medline, EMBASE and PubMed databases was performed using the MeSH terms: 1) chronic obstructive pulmonary disease; 2) exacerbations; 3) oral corticosteroid/prednisolone; and 4) randomised clinical trials. Six trials fulfilled these criteria and the authors were contacted about data sharing. Of these studies, the peripheral blood eosinophil count at the onset …
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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 | 0.012 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".