High-Dose β-Blockers and Tight Heart Rate Control Reduce Myocardial Ischemia and Troponin T Release in Vascular Surgery Patients
Bibliographic record
Abstract
BACKGROUND: Adverse perioperative cardiac events occur frequently despite the use of beta (beta)-blockers. We examined whether higher doses of beta-blockers and tight heart rate control were associated with reduced perioperative myocardial ischemia and troponin T release and improved long-term outcome. METHODS AND RESULTS: In an observational cohort study, 272 vascular surgery patients were preoperatively screened for cardiac risk factors and beta-blocker dose. Beta-blocker dose was converted to a percentage of maximum recommended therapeutic dose. Heart rate and ischemic episodes were recorded by continuous 12-lead electrocardiography, starting 1 day before to 2 days after surgery. Serial troponin T levels were measured after surgery. All-cause mortality was noted during follow-up. Myocardial ischemia was detected in 85 of 272 (31%) patients and troponin T release in 44 of 272 (16.2%). Long-term mortality occurred in 66 of 272 (24.2%) patients. In multivariate analysis, higher beta-blocker doses (per 10% increase) were significantly associated with a lower incidence of myocardial ischemia (hazard ratio [HR], 0.62; 95% confidence interval [CI], 0.51 to 0.75), troponin T release (HR, 0.63; 95% CI, 0.49 to 0.80), and long-term mortality (HR, 0.86; 95% CI, 0.76 to 0.97). Higher heart rates during electrocardiographic monitoring (per 10-bpm increase) were significantly associated with an increased incidence of myocardial ischemia (HR, 2.49; 95% CI, 1.79 to 3.48), troponin T release (HR, 1.53; 95% CI, 1.16 to 2.03), and long-term mortality (HR, 1.42; 95% CI, 1.14 to 1.76). CONCLUSIONS: This study showed that higher doses of beta-blockers and tight heart rate control are associated with reduced perioperative myocardial ischemia and troponin T release and improved long-term outcome in vascular surgery patients.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".