Synthetic Meshes in Pelvic Organ Prolapse: A Narrative Review
Bibliographic record
Abstract
Introduction: Pelvic organ prolapse is a common condition that can affect 50% of parous women. The surgical management can be divided into two approaches: A trans-vaginal and a trans-abdominal approach. In view of current controversies and discrepancies between guidelines, this review aims to scope the historically available data on synthetic meshes in the management of POP mainly on outcomes and complications of the trans-vaginal approach and the trans-abdominal approach. Methods: This study is a narrative review of the use of synthetic meshes in POP surgery. The different indications, the results, and comparisons to other surgical management were collected using MEDLINE and Google Scholar. Results: Regarding the trans-vaginal approach, 31 articles were included. The anatomical success rate is high, around 90%. However, this technique was recently considered cost-ineffective mostly because of high rates of erosions, ranging from 4 to 40% depending on the series. Obesity seems to be the most important risk factor of mesh erosion, followed by age and smoking. Regarding the trans-abdominal approach, 36 articles were included. In the literature, anatomical success is between 70 and 95%, with an erosion rate between 0 and 11%. Minimally invasive sacrocolpopexy and open sacrocolpopexy seem to be equally effective on anatomical outcomes and recurrence rates. Concomitant total hysterectomy might be effective but may be associated with more mesh erosions. Concomitant laparoscopic supracervical hysterectomy may be the preferred option for patients with cervical and uterine lesions but should not be performed for the sole purpose of reducing the occurrence of endometrial carcinoma, especially when uterine preservation seems effective and is associated with less blood loss and shorter operating time. Conclusion: Our review reports limited application for trans-vaginal repair because of high complications rates, leading countries to suspend their utilization. Our review reports a gold standard application for trans-abdominal sacrocolpopexy. The use of synthetic meshes in trans-abdominal sacrocolpopexy for POP repair provide durable cure rates with a lower rate of mesh-related complications and therefore may be considered the gold standard approach.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".