Robotic transanal minimally invasive surgery (R-TAMIS): current evidence in the treatment of early rectal neoplasia
Bibliographic record
Abstract
INTRODUCTION: Robotic transanal minimally invasive surgery (R-TAMIS) was introduced in 2012 for the excision of benign rectal polyps and low grade rectal cancer. Ergonomic improvements over traditional laparoscopic TAMIS (L-TAMIS) include increased dexterity within a small operative field, with possibility of better surgical precision. We aim to collate the existing data surrounding the use of R-TAMIS to treat rectal neoplasms from cohort studies and larger case series, providing a foundation for future, large-scale, comparative studies. METHODS: Medline, EMBASE and Web of Science were searched as part of our review. Randomised controlled trials (RCTs), cohort studies or large case series (≥ 5 patients) investigating the use of R-TAMIS to resect rectal neoplasia (benign or malignant) were eligible for inclusion in our analysis. Quality assessment of included studies was performed via the Newcastle Ottawa Scale (NOS) risk of bias tool. Outcomes extracted included basic participant characteristics, operative details and histopathological/oncological outcomes. RESULTS: Eighteen studies on 317 participants were included in our analysis. The quality of studies was generally satisfactory. Overall complication rate from R-TAMIS was 9.7%. Clear margins (R0) were reported in 96.2% of patients. Local recurrence (benign or malignant) occurred in 2.2% of patients during the specified follow-up periods. CONCLUSION: Our review highlights the current evidence for R-TAMIS in the local excision of rectal lesions. While R-TAMIS appears to have complication, margin negativity and recurrence rates superior to those of published L-TAMIS series, comparative studies are needed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".