Transanal endoscopic microsurgery as day surgery – a single‐centre experience with 500 patients
Bibliographic record
Abstract
AIM: Transanal endoscopic microsurgery (TEM) is the current treatment of choice for rectal adenomas and early rectal cancer. Postoperative admission to hospital is common but possibly unnecessary. Our objective was to analyse predictors and outcomes of TEM patients having same day discharge (TEM-D) compared with those who were admitted to hospital (TEM-A). METHOD: At St Paul's Hospital (SPH), demographic, surgical, pathological and follow-up data have been collected prospectively since TEM was started in 2007. Trends in admission and readmission rates were analysed using the Cochran-Armitage trend test, and predictors of admission were analysed using univariate and multivariate logistic regressions. RESULTS: Between 2007 and 2016, 500 patients were treated by TEM at SPH. The overall admission rate was 29% (145/500), but this decreased to 19% in the last 3 years of the study (P < 0.001). The readmission rate was 5.2% (n = 26/500) and did not change significantly over the study period (P = 0.30). Reasons for admission included the following: surgeon discretion/monitoring (35%), urinary retention (26%), haemorrhage (10%), breach of peritoneal cavity (7%), infection (7%) and other (15%). The most common reasons for readmission were haemorrhage (54%, n = 14), pain (19%, n = 5) and infection (12%, n = 3). Factors associated with admission were as follows: tumour height (OR 1.09, 1.02-1.17), prolonged operative time (OR 1.25, 1.14-1.37), unsutured surgical defect (OR 1.99, 1.22-3.25) and surgeon experience (OR 4.62, 2.75-7.77). CONCLUSION: Outpatient TEM is safe and carries a low risk of readmission. In centres with an outpatient TEM strategy, predictors of hospital admission include proximal tumours, prolonged surgical time and open management of the surgical defect.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".