Transvaginal Mesh Versus Native Tissue Repair for Anterior and Apical Pelvic Organ Prolapse
Bibliographic record
Abstract
OBJECTIVES: This prospective comparative cohort study aims to evaluate the safety and efficacy of transvaginal mesh compared to native tissue repair (NTR) in the surgical correction of anterior and apical compartment pelvic organ prolapse (POP) over a 36-month follow-up period. METHODS: Prospective comparative cohort study to prove superiority for efficacy and non-inferiority for serious adverse events (SAEs). The setting was 49 sites across the United States, Canada, Europe, and Australia. Women with bothersome POP symptoms indicated for vaginal surgery with pelvic organ prolapse quantification (POP-Q) scores of Ba ≥0 and C ≥ -1/2 total vaginal length were included. Interventions included vaginal NTR or single-incision transvaginal mesh based on shared decision-making. POP recurrence, the primary efficacy endpoint, was defined as anatomical prolapse beyond the hymenal ring, subjective perception of protrusion or bulge, or retreatment in the target compartment. The primary safety endpoint consisted of the proportion of device and/or procedure-related SAEs in the target compartment. Secondary endpoints included surgical parameters, quality of life, postoperative pain, and sexual function. RESULTS: POP recurrence rate at 12 months was 13.1% in the Mesh-arm and 11.5% in the NTR-arm (P = 0.44). The primary safety endpoint was met, with the Mesh-arm demonstrating statistically non-inferior outcomes compared to the NTR-arm in the incidence of device and/or procedure-related SAEs in the target compartment through 12 months (P < 0.01). At 36 months, the surgical POP recurrence rate was 26.7% in the Mesh-arm and 27.0% in the NTR-arm. CONCLUSIONS: At 12- and 36-month follow-up, transvaginal mesh was not superior, but non-inferior in terms of efficacy and safety when compared to NTR for patients with combined anterior and apical compartment prolapse.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".