The Effect of the 80-Hour Work Week on General Surgery Resident Operative Case Volume
Bibliographic record
Abstract
To meet the new duty hour restrictions on July 1, 2003, our general surgery residency program underwent many changes. The purpose of this study was to examine whether the implementation of these changes, made in part to comply with new duty hour restrictions, would adversely impact general surgery residents' operative volume. The operative cases of categorical surgical residents were recorded from July 1, 2000 to December 31, 2004. The main outcome measure was the median number of operative cases performed by each resident per quarter (a 3-month period). The number of in-house calls each resident took per quarter was also recorded. From 2000 to 2004, the median number of in-house calls per quarter significantly decreased (27, 25, 15, 10, and 14, respectively; P < 0.001). The median number of operative procedures performed did not vary from quarter to quarter (P = 0.49). There was a trend toward an increase in number of cases performed at the postgraduate year (PGY) 1 (P = 0.07) and 2 (P = 0.04) levels, a decrease at the PGY3 level (P = 0.058), and no change at the PGY4 and 5 years. The 80-hour work week did not adversely affect the operative experience of our categorical surgical residents despite significant reductions of in-house call.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".