Counseling for stress urinary incontinence in the era of adverse publicity around mesh usage: Results from a large‐sample global survey
Bibliographic record
Abstract
OBJECTIVE: To investigate doctors' opinions of the use of synthetic mesh for the treatment of stress urinary incontinence (SUI) and the effect on patient's attitude following recent adverse publicity and legal findings. METHODS: Electronic survey approved by International Urogynecological Association (IUGA) and American Urogynecologic Society (AUGS), distributed to their members. RESULTS: A total of 593 respondents completed the survey. The preferred initial surgical treatment for SUI was retropubic midurethral sling (MUS) (62%), followed by trans-obturator MUS (19%), mini-slings (10%), and then bulking agents (5%). Despite prolongation of consultation, most respondents (87%) believed that clinicians should provide a patient information leaflet (PIL) for their patients. However, only 70% of respondents were doing this. Most participants would use either the IUGA PIL or their institution PIL (61%). Only 8% felt that patients have a positive preconception of synthetic mesh for SUI. Eighty-three per cent of respondents had not changed their recommendations for treatment and the consent process. A logistic regression model identified preferences of certain geographic areas as predictors of consenting practices. CONCLUSION: Despite the negative publicity and the current medicolegal litigation involving MUS for SUI treatment, the majority of respondents still prefer this as the initial surgical treatment. Most clinicians value PIL in the surgical consent process.
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".