The outcomes of women undergoing an incision or excision of midurethral sling mesh
Bibliographic record
Abstract
Midurethral slings (MUS) are a common treatment for stress urinary incontinence, however in some cases complications require repeat surgery. Our objective was to assess the impact of MUS revision/removal procedures on subjective outcomes and use the validated Urogenital Distress Index questionnaire (UDI-6) to assess longer-term outcomes. We conducted a retrospective review of 48 patients who underwent MUS revision/removal between September 2013 and December 2021. Patients were categorized into three groups: Transection (TVSI), Excision (TVSE), and Complete excision (CSE). UDI-6 scores were collected at 3–6 months post-surgery. We found that de novo stress urinary incontinence occurred in 29%–40% of patients based on the type of mesh revision surgery. Worsening SUI was observed in 19% of TVSE and 40% of CSE patients. De novo urge incontinence was exclusive to TVSE (33%). UDI-6 scores after a median of 2–3 years indicated 25%–38% of patients achieved “asymptomatic” urinary health status, with most of the other women reporting mild to moderate symptoms. Questions on frequent urination and urge incontinence had the highest scores, while voiding dysfunction and pain had the lowest across the three types of MUS revision/removal. These results may help clinicians and patients make informed decisions regarding the treatment of MUS complications.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".