A Comprehensive, Evidence-Based Literature Review of the Surgical Treatment of Rectus Diastasis
Bibliographic record
Abstract
BACKGROUND: Rectus diastasis is a common condition that can result in a protruding abdomen, causing cosmetic and functional disability. Although it is usually repaired during abdominoplasty or herniorrhaphy, there is a lack of consensus with regard to the repair indications and optimal surgical techniques. The goal of this study is to provide an updated review of the surgical techniques used for rectus diastasis repair and their comparative efficacy. METHODS: In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, the PubMed, Embase, and Cochrane databases were searched for articles that discussed the surgical management of rectus diastasis and reported on either outcomes, complications, or recurrence rates. Data detailing surgical techniques were extracted, and pooled analyses of complication and recurrence rates were performed, controlling for surgical approach, common variations in technique, and an associated herniorrhaphy. RESULTS: Thirty-seven studies describing 45 techniques were included. An open rectus diastasis repair was performed in 24 of the studies. After controlling for an associated herniorrhaphy, there was no statistically significant difference in surgical complication and recurrence rates between open and laparoscopic approaches (p = 0.165 and p = 0.133, respectively). Although a double-layer suture closure was associated with a significantly lower rate of complications (p = 0.002), no significant difference was found for suture type absorbability. CONCLUSIONS: Surgical repair of rectus diastasis is safe and effective through both open and laparoscopic approaches. Although suture type absorbability does not affect complication or recurrence rates, a double-layer suture closure can decrease surgical complications. The pooled analysis of complication and recurrence rates can help improve informed consent and patient education.
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 | 0.006 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".