Transanal total mesorectal excision for patients with rectal cancer : a Systematic review and meta-analysis.
Bibliographic record
Abstract
BACKGROUND: Transanal total mesorectal excision (TaTME) is a new technique that is designed to overcome the limits encountered during laparoscopic total mesorectal excision (LaTME) for rectal cancer, especially in male, obese patients with a narrow pelvis and mid and low rectal tumours. AIM: The objective of our meta-analysis is to evaluate short-term oncological and perioperative outcomes of transanal total mesorectal excision (TaTME) compared to laparoscopic total mesorectal excision (LaTME) for rectal cancer. METHODS: A meta-analysis based on Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines was conducted in MEDLINE (PubMed). All original studies published in English that compared TaTME with laTME were included. The quality of the included studies was assessed by the Newcastle- Ottawa Quality Assessment Scale (NOS) and Cochrane Library Handbook 5.1.0. Data analysis was conducted using the Review Manager 5.3 software. RESULTS: Twelve studies including 835 TaTME patients and 1707 LaTME patients with rectal cancer met the inclusion criteria in this meta-analysis. No statistical significant differences were observed in regard to positive circumferential resection margin (PCRM), positive distal resection margin (PDRM), macroscopic quality of mesorectum (MQM) and harvested lymph nodes (HLN). Concerning the perioperative outcomes, the results of conversion rates, operative time, hospital stay (HS), anastomotic leakage (AL) and postoperative complications were comparable between the two groups. CONCLUSION: Our meta-analysis provides that TaTME may be a valid alternative approach for the treatment of rectal cancer in comparison with LaTME.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.036 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".