Does Off-pump Coronary Artery Bypass Reduce Mortality, Morbidity, and Resource Utilization When Compared with Conventional Coronary Artery Bypass? A Meta-analysis of Randomized Trials
Bibliographic record
Abstract
The authors undertook a meta-analysis of 37 randomized trials (3369 patients) of off-pump coronary artery bypass surgery versus conventional coronary artery bypass surgery. No significant differences were found for 30-day mortality (odds ratio [OR], 1.02; 95% confidence interval [CI], 0.58-1.80), myocardial infarction (OR, 0.77; 95%CI, 0.48-1.26), stroke (OR, 0.68; 95%CI, 0.33-1.40), renal dysfunction, intraaortic balloon pump, wound infection, rethoracotomy, or reintervention. However, off-pump coronary artery bypass surgery significantly decreased atrial fibrillation (OR, 0.58; 95%CI, 0.44-0.77), transfusion (OR, 0.43; 95%CI, 0.29-0.65), inotrope requirements (OR, 0.48; 95%CI, 0.32-0.73), respiratory infections (OR, 0.41; 95%CI, 0.23-0.74), ventilation time (weighted mean difference, -3.4 h; 95%CI, -5.1 to -1.7 h), intensive care unit stay (weighted mean difference, -0.3 days; 95%CI -0.6 to -0.1 days), and hospital stay (weighted mean difference, -1.0 days; 95%CI -1.5 to -0.5 days). Patency and neurocognitive function results were inconclusive. In-hospital and 1-yr direct costs were generally higher for conventional coronary artery bypass surgery versus off-pump coronary artery bypass surgery. Therefore, this meta-analysis demonstrates that mortality, stroke, myocardial infarction, and renal failure were not reduced in off-pump coronary artery bypass surgery surgery; however, selected short-term and mid-term clinical and resource outcomes were improved compared with conventional coronary artery bypass surgery.
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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 | 0.011 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.042 |
| Bibliometrics | 0.003 | 0.003 |
| 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".