COPD exacerbation purulence status and its association with pulmonary embolism: a systematic review with meta-analysis
Bibliographic record
Abstract
Background Diagnosing pulmonary embolism (PE) in patients with acute exacerbation of COPD (AECOPD) is challenging. Finding predictors of PE could help improve diagnostic management of patients with AECOPD. The aim was to evaluate the association between AECOPD purulence status and the presence of PE. Methods A systematic review with meta-analysis was conducted. Medline, Embase and CENTRAL were searched from inception to April 2024 for randomised trials, cohort or cross-sectional studies reporting on the prevalence of PE according to AECOPD purulence status. Relative risks with 95% confidence intervals of PE according to AECOPD purulence status and pooled proportions of PE with their 95% confidence intervals were calculated according to AECOPD purulence status. Results From 7059 citations identified, 14 studies (5056 participants) were included. The prevalence of PE varied between 0.4% and 33.2% across studies. The relative risk of PE was not statistically significantly lower in patients with purulent AECOPD compared to patients with nonpurulent/unknown aetiology AECOPD (relative risk 0.64, 95% CI 0.26–1.55; I 2 =88.0%). The pooled proportion of PE was 7.3% (95% CI 2.4–14.7%; I 2 =94.7%) and 13.3% (95% CI 8.0–19.7%; I 2 =96.0%) in studies including patients with purulent AECOPD and nonpurulent/unknown aetiology AECOPD, respectively. Conclusion The relative risk of PE was lower, but not statistically significant, in patients with purulent AECOPD compared to patients with nonpurulent/unknown aetiology AECOPD. Further studies are needed to confirm the association between PE and AECOPD purulence status and to assess its potential role in predicting PE.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.040 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".