Evaluating the influence of metabolic bariatric surgery on urinary and fecal incontinence outcomes: a one-year postoperative analysis
Bibliographic record
Abstract
PURPOSE: The most prevalent conditions affecting the pelvic floor include fecal incontinence (FI) and urinary incontinence (UI), both of which are particularly common among women with obesity. Although the effect of metabolic bariatric surgery (MBS) on FI remains a topic of ongoing discussion, the present study seeks to assess the impact of effective bariatric surgery on UI and FI in women with obesity. MATERIALS AND METHODS: An observational prospective study was conducted at the Tours University Hospital, involving 212 women who underwent MBS. Participants completed pre-operative and post-operative questionnaires to evaluate UI and FI one-year after surgery. Additionally, urinary symptom profile (USP) and Wexner score (WS) were utilized for the assessment of UI and FI, respectively. RESULTS: Of the 212 patients, 148 achieved a weight loss of more than 20% of their weight one-year after surgery, and of these 40 (27.0%) completed all questionnaires. The median pre-surgical BMI was found to be 41.8 kg/m², which reduced to 29.1 kg/m² one-year post-surgery. A significant improvement was observed in stress urinary incontinence (SUI), which decreased from 32.5% pre-operatively to 22.5% post-operatively (p < 0.0001). FI showed slight exacerbation, with an increase in moderate FI (from 5.0% to 10.0%), frequency of liquid stool per week (from 2.5% to 5.0%), and gas-related symptoms (from 0 to 2.5%). CONCLUSION: The findings of this study indicate that MBS significantly improves SUI in women with obesity, yet has minimal impact on FI one-year postoperatively. Further studies are required to more accurately assess the impact of metabolic bariatric surgery on postoperative FI.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".