Prospective Evaluation of Consultant Surgeon Sleep Deprivation and Outcomes in More Than 4000 Consecutive Cardiac Surgical Procedures
Bibliographic record
Abstract
OBJECTIVE: To determine the effect of consultant surgeon sleep hours on patient outcomes in cardiac surgery. DESIGN: Prospective observational cohort study. SUBJECTS: Between January 2004 and December 2009, we prospectively collected sleep hours of 6 consultant surgeons, ranging in age from 32 to 55 years, working in a tertiary care academic institution. The prospective study cohort included all patients undergoing coronary artery bypass, valve, combined valve-coronary artery bypass, and aortic surgery. The predicted risk of death and/or any of 10 major complications was calculated using our institutional multivariable model, which was then compared with observed values. Additional prespecified analyses examined the interaction between surgeon age, sleep hours, and postoperative outcomes. This study had more than 90% power to detect a 4% (clinically important) difference in overall complication rates among groups. MAIN OUTCOME MEASURES: Complication and mortality rates in operations performed by surgeons with 0 to 3, 3 to 6, or more than 6 hours' sleep the evening prior to surgery. RESULTS: Of 4047 consecutive surgical procedures, 83 were performed by a consultant with 0 to 3 hours, 1595 with 3 to 6 hours, and 2369 with more than 6 hours of sleep. Rates of mortality (3 [3.6%], 44 [2.8%], and 80 [3.4%], respectively; P = .53) were similar in the 3 groups, as were the observed vs expected ratios of major complications (1.20, 0.95, and 1.07, respectively; P = .25). There was no significant interaction between surgeon age, hours of sleep, and occurrence of death or any of 10 major complications (P = .09). CONCLUSION: This well-powered prospective study showed no evidence that consultant surgeon sleep hours had an effect on postoperative outcomes.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".