Patient Sex and Postoperative Outcomes after Inpatient Intraabdominal Surgery: A Population-based Retrospective Cohort Study
Bibliographic record
Abstract
BACKGROUND: Intraabdominal surgeries are frequently performed procedures that lead to a high volume of unplanned readmissions and postoperative complications. Patient sex may be a determinant of adverse outcomes in this population, possibly due to differences in biology or care delivery, but it is understudied. The authors hypothesized that there would be no association between patient sex and the risk of postoperative adverse outcomes in intraabdominal surgery. METHODS: This retrospective, population-based cohort study involved adult inpatients aged 18 yr or older who underwent intraabdominal surgeries in Ontario, Canada, between April 2009 and March 2016. The authors studied the association of patient sex on the primary composite outcome of all-cause death, hospital readmission, or major postoperative complications, all within 30 postoperative days. Inverse probability of exposure weighting based on propensity scores (computed using demographic characteristics such as rural residence status and median neighborhood income quintile, common comorbidities, and surgery- and hospital-specific characteristics) was used to estimate the adjusted association of sex on outcomes. RESULTS: The cohort included 215,846 patients (52.3% female). The primary outcome was observed in 24,712 (21.9%) females and 25,486 (24.7%) males (unadjusted risk difference, 2.8% [95% CI, 2.5 to 3.2%]; P < 0.001). After adjustment, the association between the male sex and the primary outcome was not statistically significant (adjusted risk difference, -0.2% [95% CI, -0.5 to 0.2%]; P = 0.378). CONCLUSIONS: In a large population of intraabdominal surgical patients, there was no differential risk between sexes in the composite outcome of all-cause death, hospital readmission, or major postoperative complications, all within 30 postoperative days.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".