Limberg flap versus Karydakis flap for treating pilonidal sinus disease: a systematic review and meta-analysis
Bibliographic record
Abstract
Background: The Limberg flap reconstruction and the Karydakis flap reconstruction are the 2 most used off-midline closure techniques in pilonidal sinus surgery. The current evidence is inconclusive as to which is the optimal technique. The aim of this systematic review and meta-analysis was to compare differences in outcomes between these 2 flap-based techniques. Methods: We identified studies by a systematic literature search of the Embase, MEDLINE (PubMed), Cochrane Library and Google Scholar databases and studies selected as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Only randomized controlled trials (RCTs) that compared the Limberg flap (standard or modified) and the Karydakis flap were included in this review. Results: Operative time was shorter by 7 minutes in the Karydakis group than in the Limberg group (mean difference 7.00 min, 95% confidence interval [CI] 0.53 to 13.48). The seroma formation rate was significantly higher in the Karydakis cohort (odds ratio [OR] 0.36, 95% CI 0.24 to 0.56); however, after excluding studies with a high risk of bias, the sensitivity analysis showed no significant differences in seroma formation rate between the 2 techniques (OR 0.76, 95% CI 0.31 to 1.85). Other outcomes of interest showed no significant differences between the Limberg and Karydakis techniques. Conclusion: There were no significant differences between the Limberg and Karydakis techniques. Future RCTs with strict adherence to CONSORT guidelines will further elucidate the efficacy of these surgical procedures.
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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 | 0.009 | 0.022 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.018 | 0.036 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".