EAES Rapid Recommendation Update Protocol: TaTME for Rectal Cancer – With ESCP and ESGAR Participation
Bibliographic record
Abstract
ABSTRACT Introduction Transanal total mesorectal excision (TaTME) was developed to overcome anatomical constraints related to TME. The European Association of Endoscopic Surgery (EAES) released clinical recommendations to support gastrointestinal surgeons in the treatment of rectal cancer, but contemporary evidence is available. Questions 1. Should patients receive TaTME or laparoscopic TME (laTME) for the surgical treatment of patients with low‐ or mid‐rectal cancers? 2. Should patients receive TaTME or robotic TME (roTME) for the surgical treatment of patients with low‐ or mid‐rectal cancers? Methods We will develop a rapid guideline update on the surgical management of low‐ and mid‐rectal cancers with TaTME compared to TME. Guideline development will begin with a systematic review and meta‐analysis performed by our systematic review and statistical analysis groups, followed by appraisal of the certainty of the evidence, and an in‐person consensus meeting among an international, multidisciplinary expert panel using a structured evidence‐to‐decision framework. The panel will consist of six general surgeons, a radiologist, a pathologist, two patient representatives, and two external advisors. Following the consensus meeting, recommendations will be finalized through a Delphi consensus process. This guideline will adhere to methodological standards according to GIN, GRADE, and AGREE‐S. Conflicts of interest will be declared by all participating members and addressed before guideline development. This clinical practice guideline will be presented at international congresses and published in the journal of Surgical Endoscopy & Other Interventional 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 | 0.051 | 0.161 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.012 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.005 | 0.006 |
| Research integrity | 0.008 | 0.006 |
| Insufficient payload (model declined to judge) | 0.094 | 0.023 |
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".