Analysis of British Columbia practice patterns in the management of female stress urinary incontinence with emphasis on mesh use
Bibliographic record
Abstract
INTRODUCTION: Female stress urinary incontinence (SUI) is common and has a profound impact on quality of life. Suburethral slings are the most common treatment for SUI in this population. These can be placed with synthetic mesh or autologous fascia. Mesh-related complications after midurethral sling procedures are documented in the literature but the risk of complications and reoperation is lower than the use of transvaginal mesh for pelvic organ prolapse repair. In this study, we sought to evaluate local practice patterns of management of female SUI with specific emphasis on mesh use. METHODS: A survey created by an expert panel was disseminated to respective provincial societies. RESULTS: Sixty-eight percent of respondents offer midurethral slings in their practice but only 60.6% of these respondents would offer surgical removal of the sling if there were complications, such as mesh erosion or pain. A large portion (39.4%) of respondents are performing transobturator slings as compared to retropubic midurethral slings (36.3%) and only 8.5% have removed the leg component associated with the transobturator sling in their practice. Furthermore, compared to most respondents offering midurethral slings (64.8%), only a minority of surgeons offer alternatives: 23.9% of respondents offer periurethral bulking agent injections, 15.5% offer pubovaginal slings, and 12.7% offer retropubic urethropexies. CONCLUSIONS: Our study supports that surgeons should continue to review surgical risks and alternative treatment options as part of the surgical consent process. As such, surgeons should be able to offer a variety of surgical approaches to manage female SUI.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".