Bleeding risk with antiplatelet use during thoracentesis: systematic review with confounder matrix
Bibliographic record
Abstract
Background: While thoracentesis is considered a low bleeding risk procedure, many patients with pleural effusion have cardiovascular comorbidities indicating antiplatelet use. Several recent guidelines on pleural procedures make no mention of antiplatelets. Ethical concerns preclude the conduct of randomized trials to address this question. Objective: This study aimed to determine the safety of antiplatelet use in terms of bleeding risk among adults undergoing thoracentesis. Methods: A systematic review of non-randomized studies of interventions was conducted to estimate the effect of current antiplatelet use on bleeding risk in adults undergoing thoracentesis. A causal directed acyclic graph was constructed by pulmonary medicine content experts and a methodologist to assess confounder control for the primary outcome of any bleeding event. Electronic databases (PubMed, Cochrane Library and CINAHL) were queried using text words and subject headings for observational studies until 15 February 2024. Characteristics and outcome data were extracted from eligible studies. The Newcastle-Ottawa Scale was used to assess study quality. Random-effects meta-analyses using the generic inverse variance method were performed using Review Manager 5.4. Results: Seven cohort studies (n = 2,380) with moderate risk of bias were included. Most involved patients receiving clopidogrel in the exposure group. None adequately adjusted for confounders. Pooled analysis from 3 studies showed that bleeding events were increased with antiplatelet use (OR 2.68, 95% CI 1.05-6.79, I2 = 0%). Conclusion: Very low certainty evidence suggests that bleeding risk is increased with antiplatelet use when performing thoracentesis.
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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 | 0.023 | 0.100 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.021 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".