Does the Use of Preoperative Aspirin Increase the Risk of Bleeding in Patients Undergoing Coronary Artery Bypass Grafting Surgery? Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: The traditional recommendation has been to stop Aspirin seven to 10 days prior to coronary artery bypass surgery to reduce the potential risk of bleeding. A few reports have shown that Aspirin did not increase the risk of bleeding and may be beneficial to be continued until the time of surgery. The objective of this review was to evaluate the effect of preoperative Aspirin on bleeding in patients undergoing elective bypass surgery. METHODS: A meta-analysis of 10 randomized and nonrandomized studies reporting comparisons between Aspirin and control was undertaken. The primary outcome was the total amount of postoperative chest tube drainage. Secondary outcomes were the number of units of packed red blood cell transfusion, platelet transfusion, fresh frozen plasma transfusion, and number of patients reexplored for bleeding. RESULTS: Ten studies, involving 1748 patients, met the inclusion criteria for this review of whom 913 were in the Aspirin group and 835 were in the control group. Pooling the results of all studies showed a significant increase in blood loss and transfusion of red blood cells and fresh frozen plasma in the Aspirin group (p < 0.05). There was no significant difference between the two groups in the rate of platelet transfusion, or the incidence of reexploration (p > 0.05). Included studies were heterogeneous and of low methodological quality. CONCLUSION: Aspirin is associated with increased chest tube drainage and may be associated with a greater requirement for blood products. High-quality prospective studies are warranted to reassess the effect of Aspirin on important postoperative outcomes.
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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 | 0.012 | 0.040 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.030 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".