Systematic review and meta-analysis of the effect of North American working hours restrictions on mortality and morbidity in surgical patients
Bibliographic record
Abstract
BACKGROUND: Short duty hours, imposed by the Accreditation Council of Graduate Medical Education (ACGME) regulations, have been claimed to be associated with loss of continuity of care among surgical patients, leading to a potentially increased risk of adverse surgical outcomes. This systematic review and meta-analysis assessed the strength of associations between duty hour restrictions and morbidity and mortality of various surgical procedures. METHODS: MEDLINE, Embase, BIOSIS Previews(®), the Education Resources Information Center and the Cochrane Central Register of Controlled Trials (January 2000 to September 2009) were searched, and reports screened to identify comparative studies of mortality and morbidity before and after the introduction of ACGME regulation periods. Random-effects (RE) and quality-effects (QE) meta-analyses were performed to determine the risk of morbidity or death associated with long duty hours compared with shorter duty hours. Results are presented as odds ratio (OR) with 95 per cent confidence interval. RESULTS: A total of 19 data sets (10 articles), including 730,648 subjects in the mortality studies and 64,346 in the morbidity studies, were analysed. Long duty hours were associated with a non-significantly increased risk of death compared with shorter duty hours (OR 1·28, 0·94 to 1·73). There was no difference in morbidity between the two groups (OR 1·03, 0·67 to 1·57). Mortality associations were generally stronger for general surgery, more recent studies and higher-quality studies. Heterogeneity was evident among the studies included. CONCLUSION: The reduction in working hours has not affected patient care negatively in terms of demonstrable differences in morbidity and mortality. However, it cannot be distinguished whether this effect is actually due to a non-detrimental effect of the reduction in working hours or whether any such detriment is offset by continually improving patient care and increased surgical supervision.
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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 | 0.017 | 0.044 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".