The More the Better?
Bibliographic record
Abstract
OBJECTIVE: To determine the in-hospital mortality rates for patients undergoing colorectal resection for malignant or benign conditions, and to identify risk factors for in-hospital death, particularly the relationships with surgeon and hospital volume. BACKGROUND: Although there is strong evidence that complex cancer operations are best performed at specialized high-volume centers and by high-volume surgeons, the relationship between surgeon and hospital volume and perioperative outcomes is less well defined for more common procedures such as colorectal resections, particularly for benign diseases. METHODS: We obtained data from the Canadian Institute for Health Information Discharge Abstract Database on all adult patients who underwent colorectal resection between April 1, 2005 and March 31, 2006. We performed a logistic regression to identify variables associated with a higher likelihood of in-hospital death. RESULTS: Twenty-one thousand seventy-four patients underwent colorectal resection, with the majority being elective (59.4%). Malignancy represented the most common indication for resection (56.8%), followed by diverticular disease (16.2%) and inflammatory bowel disease (7.1%). The overall in-hospital mortality rate among patients undergoing colorectal resection was 5.3%. Increased age (adjusted Odds Ratio [OR]: 1.97 per 10 years, P < 0.001), urgent operation (OR: 2.63, P < 0.001), indication for resection (P < 0.001), nature of the surgery (P < 0.001), and several comorbidities were all independently associated with an increased risk of death. Surgeons with higher volumes of colorectal resections achieved significantly lower mortality rates (OR: 0.92 per 20 cases/y, P = 0.003), corresponding to an adjusted mortality rate of 5.6% for surgeons in the bottom decile (1 case per year) compared with 4.5% for surgeons in the top decile (greater than 43 cases per year). Hospital volume was not associated with mortality (OR: 1.00 per 10 cases, P = 0.504). CONCLUSIONS: This large, population-based study suggests that surgeons who perform high volumes of colorectal resections achieve lower in-hospital mortality rates than surgeons with low volumes, whereas the hospital volume does not influence mortality.
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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 | 0.005 | 0.026 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.034 | 0.005 |
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".