Colonoscopic-assisted laparoscopic wedge resection for colonic neoplasms: a systematic review
Bibliographic record
Abstract
Objectives The current literature describes a variety of techniques detailed under the name of combined endoscopic-laparoscopic surgery (CELS) procedures. This systematic review of literature assessed the outcomes of colonoscopic-assisted laparoscopic-wedge resection (CAL-WR) in particular to evaluate its feasibility to remove colonic lesions that do not qualify for endoscopic resection.Materials and methods Electronic databases (PubMed, Embase, and Cochrane) were searched for studies evaluating CAL-WR for the treatment of colonic lesions. Studies with missing full text, language other than English, systematic reviews, and studies with fewer than ten patients were excluded. The quality of the studies was assessed using the Newcastle-Ottawa Scale.Results Out of 68 results, duplicate studies (n = 27) as well as studies that did not meet the inclusion criteria (n = 32) were removed. Nine studies were included, encompassing 326 patients who underwent a CAL-WR of the colon. The technical success rate varied from 93 to 100%, with an R0 resection rate of 91–100%. Morbidity ranged from 6% to 20%. The quality of the included studies was rated as low to moderate and contained heterogeneous terminology, methodology, and outcome measures.Conclusions There is insufficient high-quality data and substantial variation in outcome measures to draw firm conclusions regarding the value of CAL-WR. Although CAL-WR is a promising local resection technique for endoscopically unremovable neoplasms of the colon, further investigation of this technique in well-designed prospective, multicenter studies with predefined outcome measures is required.Trial registration: A protocol for this systematic review was registered in PROSPERO with the number CRD42023407966.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.006 |
| Bibliometrics | 0.011 | 0.011 |
| 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) | 0.004 | 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".