Macrolide Therapy for <i>Chlamydia pneumoniae</i> in the Secondary Prevention of Coronary Artery Disease: A Meta‐Analysis of Randomized Controlled Trials
Bibliographic record
Abstract
STUDY OBJECTIVE: As recent studies have shown that antibiotic therapy to eradicate Chlamydia pneumoniae may be beneficial in the secondary prevention of coronary artery disease, and studies to date may have lacked statistical power, we conducted a meta-analysis of randomized controlled trials to determine the role of antibiotic therapy in this patient population. DESIGN: Systematic review and meta-analysis of randomized controlled trials. PATIENTS: A total of 12,032 patients from nine studies. MEASUREMENTS AND MAIN RESULTS: We searched MEDLINE, EMBASE, the Cochrane Controlled Trials Register, and abstracts of conference proceedings to identify pertinent studies. The random effects model was used to estimate a pooled relative risk. Heterogeneity was assessed using the bootstrap version of the Q statistic with 1000 replications. In total, we reviewed nine randomized controlled trials enrolling 12,032 patients; six enrolled patients with acute coronary syndrome, two enrolled patients with stable coronary artery disease, and one enrolled a mixed population. Compared with placebo, macrolide therapy was not associated with a significant reduction in any coronary event (relative risk [RR] 0.98, 95% confidence interval [CI] 0.88-1.08), myocardial infarction or angina (RR 0.89, 95% CI 0.68-1.16), or overall mortality (RR 0.95, 95% CI 0.81-1.12). CONCLUSION: Our results do not support routine use of antichlamydial therapy for secondary prevention of coronary events.
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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 | 0.031 | 0.054 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.057 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".