Incidence of stress urinary incontinence following vaginal repair of pelvic organ prolapse in objectively continent women
Bibliographic record
Abstract
OBJECTIVE: To estimate the incidence of stress urinary incontinence (SUI) following vaginal repair of pelvic organ prolapse (POP) in preoperatively continent women and to evaluate the impact of the problem. METHODS: Women were eligible if they had undergone vaginal repairs for any degree or type of POP with no anti-incontinence procedure between July 1, 2004 and June 30, 2006, and had been continent preoperatively, as defined by a negative cough stress test with or without reduction of prolapse. Demographic, preoperative, operative, and postoperative data were retrieved from hospital charts. The incidence of postoperative SUI (POSUI) and its quality of life (QoL) impact were assessed by mailed questionnaire. The POSUI endpoint was defined by the report of SUI symptoms on the mailed questionnaire and/or affirmation of postoperative treatment for SUI. RESULTS: Forty-two out of 100 respondents reported POSUI within the 2-year average follow-up period. Twelve of 37 symptomatic women (32%) were moderately or greatly bothered by their symptoms. The QoL impact score was generally low but was statistically greater in women with POSUI compared to those with no POSUI (13 vs. 3, P=0.0006). CONCLUSION: The risk of POSUI following vaginal repairs of POP may be higher than previously reported and approximately one-third of women are bothered by these symptoms. These findings deserve further investigation.
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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 | 0.001 |
| 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".