Systematic review on recent advances in the surgical management of rectal prolapse
Bibliographic record
Abstract
INTRODUCTION: Surgical management of external rectal prolapse (ERP) remains a challenge with the breadth of choices available and varies on the international, national, regional and locoregional level. Significant innovation has led to new techniques to manage ERP including changes to both abdominal and perineal approaches. EVIDENCE ACQUISITION: A systematic, English-language search of major databases was conducted from 2006-2016. From 636 papers two reviewers identified 24 studies which compared two or more surgical techniques in adult patients with rectal prolapse and reported on complications, quality of life or recurrence. The Newcastle-Ottawa Scale (NOS) was used to score quality in non-randomized control trials (RCT) and the Cochrane Collaboration tool was use for RCTs. EVIDENCE SYNTHESIS: Abdominal and perianal surgeries both result in the resolution of symptoms and an improvement of quality of life for most patients. Short-term outcomes generally favored laparoscopy. Rectopexy with or without resection confers balances a low risk of recurrence with a similar complication rate to perineal surgery. The quality of included studies was general poor and most was at significant risk of bias. CONCLUSIONS: Most studies are of low quality and surgical management should be individualized to balance risk of the operation and the potential benefit to quality of life. Laparoscopy and modern anesthesia has made the abdominal approach more attractive even for elderly patients.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".