Performance of Perioperative Tasks for Women Undergoing Anti-incontinence Surgery
Bibliographic record
Abstract
OBJECTIVES: Surgery for the correction of stress urinary incontinence is an elective procedure that can have a dramatic and positive impact on quality of life. Anti-incontinence procedures, like inguinal hernia repairs or cholecystectomies, can be classified as high-volume/low-morbidity procedures. The performance of a standard set of perioperative tasks has been suggested as one way to optimize quality of care in elective high-volume/low-morbidity procedures. Our primary objective was to evaluate the performance of 5 perioperative tasks-(1) offering nonsurgical treatment, (2) performance of a standard preoperative prolapse examination, (3) cough stress test, (4) postvoid residual test, and (5) intraoperative cystoscopy for women undergoing surgery for stress urinary incontinence-compared among surgeons with and without board certification in female pelvic medicine and reconstructive surgery (FPMRS). STUDY DESIGN: This study was a retrospective chart review of anti-incontinence surgical procedures performed between 2011 and 2013 at 9 health systems. Cases were reviewed for surgical volume, adverse outcomes, and the performance of 5 perioperative tasks and compared between surgeons with and without FPMRS certification. RESULTS: Non-FPMRS surgeons performed fewer anti-incontinence procedures than FPMRS-certified surgeons. Female pelvic medicine and reconstructive surgery surgeons were more likely to perform all 5 perioperative tasks compared with non-FPMRS surgeons. After propensity matching, FPMRS surgeons had fewer patients readmitted within 30 days of surgery compared with non-FPMRS surgeons. CONCLUSIONS: Female pelvic medicine and reconstructive surgery surgeons performed higher volumes of anti-incontinence procedures, were more likely to document the performance of the 5 perioperative tasks, and were less likely to have their patients readmitted within 30 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".