Pre-operative use of aspirin in patients undergoing coronary artery bypass grafting: a systematic review and updated meta-analysis
Bibliographic record
Abstract
Background: Aspirin therapy improves saphenous vein graft (SVG) patency in patients undergoing coronary artery bypass graft (CABG), however, its use in the pre-operative period remains controversial. Therefore, we conducted a systematic review and meta-analysis of randomized-controlled trials (RCTs) to update the evidence about risk and benefits of pre-operative aspirin therapy in patients undergoing CABG. Methods: Electronic databases (Medline, Embase, PubMed, Cochrane Library, and Scopus) were searched to identify RCTs evaluating the effect of aspirin versus placebo/control before CABG. Two investigators independently and in duplicate screened citations and extracted data and rated the risk of bias. The strength of evidence was appraised using the Grading of Recommendation Assessment, Development, and Evaluation (GRADE) approach. Meta-analysis was performed using a random-effects model. The main outcomes of interest were 30-day mortality, peri-operative myocardial infarction (MI), chest tube drainage and SVG occlusion. Results: A total of 13 RCTs involving 4,377 participants (2,266/2,111 pre-operative aspirin/control) met the inclusion criteria. Pre-operative aspirin reduced the risk of SVG occlusion [risk ratio (RR): 0.69, 95% confidence interval (CI): 0.49–0.97, P=0.03, I2=16%], but no differences in mortality (RR: 1.41, 95% Cl: 0.73–2.74, I2=0%) and MI (RR: 0.84, 95% CI: 0.69–1.03, I2=0%) were found. However, pre-operative aspirin increased chest tube drainage (MD: 100.40 mL, 95% CI: 24.32–176.47 mL, P=0.01, I2=84%) and surgical re-exploration (RR: 1.52, 95% CI: 1.02–2.27, P=0.04, I2=8%), with no significant difference in RBC transfusion (RR: 1.06, 95% CI: 0.90–1.25, I2=35%). Conclusions: Based on trials where the rated body of evidence was of low to very-low quality, pre-operative aspirin improves SVG patency but increases chest tube drainage and need for surgical re-exploration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".