The Impact of Surgeon Volume on Postoperative Outcomes After Surgery for Crohnʼs Disease
Bibliographic record
Abstract
BACKGROUND: High hospital procedural volume has been associated with better postoperative inflammatory bowel disease outcomes. We assessed the independent contribution of surgeon volume to health outcomes after surgery for Crohn's disease. METHODS: We identified 2842 individuals with Crohn's disease who underwent first inflammatory bowel disease-related surgery between 1996 and 2009. We assessed the association between surgeon volume, hospital volume, comorbidity and demographic variables, and postoperative outcomes. RESULTS: The in-hospital mortality rate was 4.4%. Being in the lowest income, quintile was associated with 3-fold higher mortality compared with the highest income quartile (odds ratio, 3.10; 95% CI, 1.44-6.48). The late hospitalization (>3 mo after surgery) rate among those operated by surgeons in the bottom quartile for inflammatory bowel disease surgery volume was nearly 1.5-fold higher than that of those operated by surgeons in the second, third, and top quartiles (3.4/100 person-years [py] versus 2.4/100 py, 2.1/100 py, and 2.3/100 py, respectively; P < 0.05). After multivariate adjustment, the relative incidence ratio for late hospitalization for surgeons in the second, third, and top quartiles were 0.88 (95% CI, 0.83-0.93), 0.88 (95% CI, 0.83-0.94), and 0.87 (95% CI, 0.79-0.94) compared with the bottom quartile, respectively. The 5-year risk of recurrent surgery was 24.3%, and was not associated with surgeon volume. CONCLUSIONS: Low surgeon volumes were associated with increased risk of late hospitalizations after Crohn's disease surgery. Prospective studies are warranted to elucidate whether this correlation is a late-onset consequence of surgical inexperience or other healthcare utilization factors that are associated with lower surgeon volume.
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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 | 0.007 |
| 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 | 0.001 | 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".