Transanal endoscopic microsurgery: a review
Bibliographic record
Abstract
Rectal adenomas and cancers occur frequently. Small adenomas can be removed colonoscopically, whereas larger polyps are removed via conventional transanal excision. Owing to technical difficulties, adenomas of the mid- and upper rectum require radical resection. Transanal endoscopic microsurgery (TEM) was first designed as an alternative treatment for these lesions. However, since its development TEM has been also used for a variety of rectal lesions, including carcinoids, rectal prolapse and diverticula, early stage carcinomas and palliative resection of rectal cancers. The objective of this review is to describe the current status of TEM in the treatment of rectal lesions. Since the 1980s, TEM has advanced substantially. With low recurrence rates, it is the method of choice for resection of endoscopically unresectable adenomas. Some studies have shown benefits to its use in treating early T1 rectal cancers compared with radical surgery in select patients. However, for more advanced rectal cancers TEM should be considered palliative or experimental. This technique has also been shown to be safe for the treatment of other uncommon rectal tumours, such as carcinoids. Transanal endoscopic microsurgery may allow for new strategies in the treatment of rectal pathology where technical limitations of transanal techniques have limited endoluminal surgical innovations.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".