Effect of β-Blockers on Perioperative Myocardial Ischemia in Patients Undergoing Noncardiac Surgery
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Myocardial ischemia remains a major cause of morbidity in patients undergoing noncardiac surgery. The purpose of the paper was to review the evidence of the use of perioperative beta-blockers for the reduction of myocardial ischemia in patients having noncardiac surgery. METHOD: Pubmed was searched for articles that included beta-blockers and perioperative myocardial ischemia. Randomized controlled trials that assessed the effect of beta-blockers on myocardial ischemia in patients undergoing noncardiac surgery were included in this review and a meta-analysis were performed. RESULTS: Sixteen randomized controlled trials including 2230 patients were included. The study methodologies and results were summarized and meta-analysis performed. Ten trials used beta-blockers in the postoperative period; 954 patients received beta-blockers and 924 patients in the control group. Of the six trials that used beta-blocker for premedication, there were 207 patients in the beta- blocker and 145 patients in the control group. For the cohort when beta-blockers were used postoperatively, myocardial ischemia was reduced significantly with the use of beta-blockers (OR 0.42; 95% CI 0.27-0.65; P=0.0001; I(2)=0%). A similar beneficial effect was observed in trials that used beta- blocker for premedication (OR 0.16; 95% CI 0.07-0.35; P%lt;0.00001; I(2)=40%). CONCLUSION: The meta-analysis shows that the use of beta-blockers, both as premedication and postoperatively, in noncardiac surgery is associated with a significant reduction in perioperative myocardial ischemia.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 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 | 0.001 |
| 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 it