Recurrence following perineal proctosigmoidectomy with levatorplasty: Review and meta-analyses
Bibliographic record
Abstract
Full-thickness rectal prolapse remains a challenging pathology to correct surgically with significant recurrence rates. Among perineal approaches, the proctosigmoidectomy with levatorplasty, commonly referred to as the Altemeier procedure is frequently performed. The addition of levatorplasty has been postulated to improve recurrence rates, however, its efficacy varies across studies. The aim of this study was to systematically review recurrence rates following proctosigmoidectomy with levatorplasty, and to meta-analyze pooled data comparing recurrence rates between proctosigmoidectomy with and without a levatorplasty. A search of EMBASE, OVID Medline, and CENTRAL was performed from database inception to October 2021 aimed at identifying studies investigating recurrences of rectal prolapse following proctosigmoidectomy with levatorplasty. Primary endpoint was recurrence of rectal prolapse. Articles that did not report this endpoint or did not evaluate proctosigmoidectomy with levatorplasty were excluded. A pairwise meta-analysis was performed using Mantel-Haenszel random effects. From 200 citations, 14 primary studies met inclusion criteria. A total of 620 patients (88.9% female, mean age: 71 years) underwent proctosigmoidectomy with levatorplasty, and 117 without levatorplasty. Of the patients undergoing levatorplasty, 86 (13.8%) experienced a recurrence. Mean follow up was 46 months. Meta-analysis comparing recurrence rates between proctosigmoidectomy with and without levatorplasty demonstrated no significant difference (RR 0.80, 0.92, 95% CI 0.32-2.59, P=0.87, I2 = 77%). Narrative review of postoperative quality of life metrics demonstrated decreased incontinence with levatorplasty as measured by Wexner and ICIQ-SIF scores. The addition of a levatorplasty does not significantly reduce the risk of recurrent rectal prolapse after proctosigmoidectomy, however it may improve postoperative continence.
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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 | 0.008 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.029 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".