The Effect of Time During the Academic Year or Resident Training Level on Complication Rates After Lower-Extremity Orthopaedic Trauma Procedures
Bibliographic record
Abstract
BACKGROUND: Few studies have evaluated the effect of resident participation on morbidity and mortality after orthopaedic trauma surgery. The goal of this study was to evaluate whether complications after orthopaedic trauma procedures involving residents correlate with the level of resident training and the timing in the academic year. METHODS: The American College of Surgeons National Surgical Quality Improvement Program database was queried for all patients who underwent operative fixation of proximal femoral fractures, femoral shaft fractures, and tibial shaft fractures from 2005 to 2012. A total of 1,851 cases with resident involvement were identified, and complication rates were calculated and analyzed with respect to resident level of training (postgraduate year [PGY] 1 through 6) and the academic quarter in which the procedure took place. RESULTS: The composite complication rates in the first academic quarter for serious adverse events (10.96%), any adverse events (18.57%), and surgical complications (9.62%) did not significantly differ from those during the remainder of the year (11.40%, 17.81%, and 7.19%, respectively). The rates of any adverse event were significantly higher for senior-level residents (quarter 1, 20.58%; quarter 2, 20.05%) than for junior residents (quarter 1, 11.76%; quarter 2, 12.44%) during the first half of the academic year (quarter 1, p = 0.044; quarter 2, p = 0.024). CONCLUSIONS: This evaluation of the composite complication rates found no "July effect" in lower-extremity orthopaedic trauma surgery. There was evidence for a July effect for superficial surgical site infections, in that there was a significantly higher rate in the first academic quarter. Senior residents may benefit from more oversight or instruction during the first portion of the academic year.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".