A Systematic Review and Meta-Analysis of Single-Incision Versus Multiport Laparoscopic Complete Mesocolic Excision Colectomy for Colon Cancer
Bibliographic record
Abstract
Background. Our aim was to compare the emerging technique of single-incision laparoscopic surgery complete mesocolic excision (SILS CME) colectomy with the standard multiport laparoscopic CME (MPL CME) colectomy. Methods. MEDLINE (PubMed), Scopus, EMBASE, Ovid, and the Cochrane library were searched. Studies comparing the SILS CME with MPL CME in adults with colon adenocarcinoma were included. The Jadad and Newcastle Ottawa Scales were used to critically appraise the studies. The presence of statistical heterogeneity or publication bias was examined. Results. Seven studies (3 randomized) with a total number of 1344 patients were included (546 SILS CME and 798 MPL CME). No difference was found in anastomotic leakage (odds ratio [OR] = 0.79 [0.31 to 2.03]; P = .63), number of lymph nodes (weighted mean difference [WMD] = 0.85 [−0.97 to 2.66]; P = .36), hospital stay (WMD = 0.01 [−0.19 to 0.20]; P = .96), overall survival (hazard ratio [HR] = 1.19 [0.29 to 4.80]; P = .81), and disease-free survival (HR = 1.30 [0.30 to 5.61]; P = .72). Skin incision was shorter in SILS CME group (WMD = −3.02 [−3.25 to −2.80]; P < .00001) but with no difference in pain reported in postoperative day 1 (standardized mean difference [SMD] = −0.21 [−0.50 to 0.09]; P = .17) or day 2 (SMD = 0.16 [−0.52 to 0.84]; P = .64). Conclusions. SILS CME, although technically more demanding, has equivalent short- and long-term outcomes when compared with MPL CME. Potential benefits in cosmesis or postoperative pain need to be further explored by high-quality randomized controlled trials.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.021 | 0.031 |
| Bibliometrics | 0.007 | 0.008 |
| 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".