Macrolides for better resolution of community-acquired pneumonia: A global meta-analysis of clinical outcomes with focus on microbial aetiology
Bibliographic record
Abstract
OBJECTIVES: This meta-analysis examined the effect of macrolides on resolution of community-acquired pneumonia (CAP) and interpretation of clinical benefit according to microbiology; emphasis is given to data under-reported countries (URCs). METHODS: This meta-analysis included 47 publications published between 1994 and 2022. Publications were analysed for 30-d mortality (58 759 patients) and resolution of CAP (6465 patients). A separate meta-analysis was done for the prevalence of respiratory pathogens in URCs. RESULTS: Mortality after 30 d was reduced by the addition of macrolides (odds ratio [OR] 0.65, 95% confidence interval [CI] 0.51-0.82). The OR for CAP resolution when macrolides were added to the treatment regimen was 1.23 (95% CI 1.00-1.52). In the CAP resolution analysis, the most prevalent pathogen was Streptococcus pneumoniae (12.68%; 95% CI 9.36-16.95%). Analysis of the pathogen epidemiology from the URCs included 12 publications. The most prevalent pathogens were S. pneumoniae (24.91%) and Klebsiella pneumoniae (12.90%). CONCLUSION: The addition of macrolides to the treatment regimen led to 35% relative decrease of 30-d mortality and to 23% relative increase in resolution of CAP.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.040 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".