Epidural Analgesia Reduces Postoperative Myocardial Infarction: A Meta-Analysis
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Bibliographic record
Abstract
UNLABELLED: Postoperative cardiac morbidity and mortality continue to pose considerable risks to surgical patients. Postoperative epidural analgesia is considered to have beneficial effects on cardiac outcomes. The use in high-risk cardiac patients remains controversial. No study has shown that postoperative epidural analgesia decreases postoperative myocardial infarction (PMI) or death. All studies are underpowered to show such a result, and the cost of conducting a large trial is prohibitive. We performed a metaanalysis to determine whether postoperative epidural analgesia continued for more than 24 h after surgery reduces PMI or in-hospital death. The available databases were searched for randomized controlled trials of epidural analgesia that was extended at least 24 h into the postoperative period. The search yielded 17 studies, of which 11 were randomized controlled trials comprising 1173 patients. Metaanalysis was conducted by using the fixed-effects model, calculating both an odds ratio and a rate difference. Postoperative epidural analgesia resulted in better analgesia for the first 24 h after surgery. The rate of PMI was 6.3%, with lower rates in the Epidural group (rate difference, -3.8%; 95% confidence interval [CI] -7.4%, -0.2%; P = 0.049). The frequency of in-hospital death was 3.3%, with no significant difference between Epidural and Nonepidural groups (rate difference, -1.3%; 95% CI, -3.8%, 1.2%, P = 0.091). Subgroup analysis of postoperative thoracic epidural analgesia showed a significant reduction in PMI in the Epidural group (rate difference, -5.3%; 95% CI, -9.9%, -0.7%; P = 0.04). IMPLICATIONS: Postoperative epidural analgesia, especially thoracic epidural analgesia, continued for more than 24 h reduces postoperative myocardial infarctions.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.014 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 it