Bleeding events in patients using clopidogrel undergoing thoracentesis: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Objective This systematic review and meta-analysis aimed to evaluate the proportion of major bleeding events in patients using clopidogrel who underwent thoracentesis or other pleural procedures. As clopidogrel is a widely used antiplatelet agent, its continuation during invasive procedures raises safety concerns. Methods A comprehensive search was conducted in PubMed, Cochrane Library and Embase from inception to July 2025, following PRISMA guidelines. Eligible studies included observational or randomised trials that reported major bleeding outcomes in patients who continued clopidogrel during thoracentesis, small-bore chest tube insertion, or pleural catheter placement. Data extracted included demographic variables, procedural details and bleeding event rates. Study quality was assessed using the Newcastle-Ottawa Scale. The pooled proportion of bleeding events was calculated using a random-effects model. A subgroup analysis was conducted for studies specific to thoracentesis. Heterogeneity was assessed with the I 2 statistic. Sensitivity analyses and meta-regression (based on publication year and sample size) were performed to evaluate result stability and potential effect modifiers. Results Twelve studies including 392 patients met the inclusion criteria. The pooled bleeding event rate was 0.0004 (95% CI: 0.0000–0.0102), and for thoracentesis-only studies it was 0.0012 (95% CI: 0.0000–0.0148). Heterogeneity was negligible (I 2 = 0%). Leave-one-out analysis confirmed robustness, and no significant publication bias was detected. Meta-regression did not identify any significant moderators. Conclusion The findings suggest that clopidogrel continuation during thoracentesis is associated with a very low risk of major bleeding. Routine discontinuation may not be necessary, although additional high-quality studies are warranted.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.034 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.054 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 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".