An Observational Study to Evaluate 2 Target Times for Elective Coronary Bypass Surgery
Bibliographic record
Abstract
BACKGROUND: Guidelines for timing of elective bypass surgery were established by expert opinion; yet, there is little evidence to support the recommended target times. OBJECTIVES: To estimate the effect of timing of the procedure on in-hospital mortality by comparing groups of patients that differ in the duration of time between decision to operate and performed procedure. RESEARCH DESIGN: We used a population-based registry to identify patients who underwent surgical coronary revascularization and their hospital discharge summaries to identify in-hospital death. SUBJECTS: We studied 9593 patients who underwent surgical revascularization between 1992 and 2006 after registration on a wait list for first-time isolated coronary artery bypass grafting on an elective basis. MEASURES: The outcome was postoperative in-hospital death. The study variable was the timing of surgery, categorized as short, prolonged, and excessive delays according to the guidelines. METHODS: The probability of in-hospital death in relation to timing of surgery was modeled by logistic regression that included a precalculated risk score for in-hospital death, with weighting observations by inverse propensity scores for the 3 surgery timing groups. RESULTS: In-hospital death among patients with short delays was one third as likely as among those with excessive delays: adjusted odds ratio=0.32 (95% confidence interval 0.20-0.51). The protective effect was smaller and not significant for patients with prolonged delays; odds ratio=0.78 (95% confidence interval, 0.38-1.63). CONCLUSIONS: Our findings suggest a survival benefit from performing elective surgical revascularization within the time frame recommended by the stricter of the 2 guidelines. Our results have implications for health systems that provide universal coverage and that budget the annual number of procedures.
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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 | 0.001 | 0.002 |
| 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) | 0.001 | 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".