Treatment of Rectal Cancer with Trans-Anal Mesorectal Excision: A Mini-Review of the Literature
Bibliographic record
Abstract
Background: The aim of this mini-review is to summarize the body of literature based on studies on the perioperative and oncological outcomes of transanal total mesorectal excision (TaTME) for the treatment of rectal cancer. Methods: A literature search of PubMED database was performed using subject headings and keywords related to rectal adenocarcinoma and transanal mesorectal excision. Results: Five case series were identified, reporting on a total of 378 patients with mean/median age ranging from 56.5 to 67.6 years and body mass index ranging from 25.2 to 27.5 kg/m2. The mean/median operative time was 166 to 270 minutes. Conversion rate to open approach ranged from 0% to 7.3% whereas postoperative complication rate ranged from 26% to 39%. The length of stay ranged from 4.5 to 10 days. The completeness of circumferential resection margin (CRM) was reported to be between 72% to 97.1%. CRM positivity ranged from 2.5% to 6.4%. The distal resection margin (DRM) ranged from 10 mm to 37.1 mm and DRM positivity ranged from 0% to 2%. The mean/median lymph node harvested ranged from 12 to 20. Short-term oncological outcome (median follow-up period of 15.1 to 29 months) was reported with local recurrence rate from 1.9% to 4% and distal recurrence rate of 3.9% to 14.5%. Conclusions: TaTME appears to be a safe technique for treatment of rectal cancer although the current evidence is limited by the heterogeneity of the quality of available studies. Randomized control trials would be necessary to assess the longterm safety and oncological outcomes of TaTME as compared to conventional rectal surgery techniques.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".