Predictors of sling revision after mid‐urethral sling procedures: a case–control study
Bibliographic record
Abstract
OBJECTIVE: To identify patient characteristics and surgical factors predictive of complications requiring mid-urethral sling (MUS) revision/removal. DESIGN: Case-control study. SETTING: Tertiary academic centre in Canada. POPULATION: One hundred and seven women undergoing MUS revision/removal between 2005 and 2016 were matched with 214 controls by date of index MUS procedure (2:1 ratio). METHODS: Data on patient and surgical factors were obtained via manual electronic and paper chart review. Three sets of pre-specified simple and multivariable logistic regression models were fitted to: (1) examine previously reported risk factors for MUS revision after primary surgical treatment; (2) identify preoperative predictors of MUS complications requiring revision/removal; and (3) identify surgical factors associated with this outcome after adjusting for potential confounding factors. MAIN OUTCOME MEASURES: Crude and adjusted odds ratios (ORs) with 95% confidence intervals (95% CIs) for patient and surgical factors. RESULTS: The median time to MUS revision was 153 days (interquartile range, IQR 49-432 days). Active smoking status (OR 2.29, 95% CI 1.13-4.63, P = 0.03), having had a previous hysterectomy (OR 3.88, 95% CI 2.02-7.46, P < 0.01), and undergoing concomitant pelvic organ prolapse surgery at the time of the index MUS procedure (OR 2.63, 95% CI 1.32-5.52, P < 0.01) were independently associated with the need for MUS revision/removal. Sling type (obturator versus retropubic), method of tensioning (to cough versus over instrument), anaesthetic type, and estimated blood loss were not associated with this outcome in the analysis presented here. CONCLUSIONS: Active smoking status, having had a previous hysterectomy, and undergoing concomitant surgery for pelvic organ prolapse are risk factors for requiring subsequent MUS revision/removal. TWEETABLE ABSTRACT: Risk factors for sling revision include smoking, previous hysterectomy, and concomitant prolapse surgery.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".