Can preoperative urodynamic studies predict de novo stress urinary incontinence following advanced pelvic organ prolapse surgery?
Bibliographic record
Abstract
INTRODUCTION: We aimed to assess the predictivity of preoperative urodynamics (UDS) on de novo stress urinary incontinence (SUI) in patients having advanced pelvic organ prolapse (POP). METHODS: Between January 2016 and June 2019, 133 patients with symptomatic POP at stage 3 or higher were included in the study. The presence of postoperative SUI symptoms after a minimum of six months of followup was considered the primary outcome. The results of all patients' preoperative UDS were compared to their postoperative SUI symptoms. In addition, patients were divided into two groups based on whether SUI was detected during preoperative UDS testing (group 1) or not (group 2). RESULTS: Although preoperative measurements, such as bladder capacity and residual urine volume, were not different between groups, group 1 had lower maximal urethral closure pressures (p=0.001). Preoperative SUI symptoms had a sensitivity of 32.1% and a specificity of 91.4% for predicting de novo SUI. In patients with advanced POP, preoperative UDS had a sensitivity of 60.7% and a specificity of 87.6% for predicting de novo SUI. CONCLUSIONS: Urodynamic examination with a pessary can significantly predict the development of de novo 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".