Comparison of Postoperative Outcomes Among Patients Treated by Male Versus Female Surgeons
Bibliographic record
Abstract
OBJECTIVE: To compare clinical outcomes of patients treated by female surgeons versus those treated by male surgeons. BACKGROUND: It remains unclear as to whether surgical performance and outcomes differ between female and male surgeons. METHODS: We conducted a meta-analysis to compare patients' clinical outcomes-including patients' postoperative mortality, readmission, and complication rates-between female versus male surgeons. MEDLINE, Embase, CENTRAL, ICTRP, and ClinicalTrials.gov were searched from inception to September 8, 2022. The update search was conducted on July 19, 2023. We used random-effects models to synthesize data and GRADE to evaluate the certainty. RESULTS: A total of 15 retrospective cohort studies provided data on 5,448,121 participants. We found that patients treated by female surgeons experienced a lower postoperative mortality compared with patients treated by male surgeons [8 studies; adjusted odds ratio (aOR), 0.93; 95% CI, 0.88-0.97; I2 =27%; moderate certainty of the evidence]. We found a similar pattern for both elective and nonelective (emergent or urgent) surgeries, although the difference was larger for elective surgeries (test for subgroup difference P =0.003). We found no evidence that female and male surgeons differed for patient readmission (3 studies; aOR, 1.20; 95% CI, 0.83-1.74; I2 =92%; very low certainty of the evidence) or complication rates (8 studies; aOR, 0.94; 95% CI, 0.88-1.01; I2 =38%; very low certainty of the evidence). CONCLUSION: This systematic review and meta-analysis suggests that patients treated by female surgeons have a lower mortality compared with those treated by male surgeons.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".