Laparoscopic sigmoid resection with transrectal specimen extraction: a systematic review
Bibliographic record
Abstract
AIM: A systematic review was performed to identify differences in surgical technique, postoperative morbidity, length of hospital stay and safety for procedures involving left-sided laparoscopic colectomy with natural orifice specimen extraction. METHOD: A PubMed search was performed to retrieve studies reporting on left-sided laparoscopic colorectal resection with transrectal specimen extraction. The quality of the different reports was assessed according to the Newcastle-Ottawa Scale. Six studies were included and all but one were cohort studies. Studies on transanal, transvaginal or transcolonic specimen extraction were excluded, as were reports on paediatric surgery. RESULTS: Six papers (including 94 patients) fulfilled the search criteria. The techniques reported were not standardized and this technical heterogeneity hampered pooled analysis. A meta-analysis could also not be performed because of differences in inter-study methods, study population and results. All studies showed, nevertheless, that the technique is feasible with low morbidity and short postoperative hospital stay. No anal dysfunction was reported. CONCLUSION: To date, the evidence in favour of left-sided laparoscopic colectomy with transrectal specimen extraction is weak (level IV-V). Future clinical research should focus on standardization of the technique. Randomized controlled trials are necessary to show the superiority of this approach with regard to postoperative pain and morbidity, hospital stay, recovery, function and cosmesis.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.006 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".