Transgastric NOTES: Current Experience and Potential Implications for Urologic Applications
Bibliographic record
Abstract
Natural orifice translumenal endoscopic surgery (NOTES) in its current form uses flexible endoscopy technology to perform surgical procedures in the abdomen. NOTES is emerging as a potential alternative to both open and laparoscopic surgery, and the technique eliminates the requirement of abdominal incisions. To date, multiple intraperitoneal procedures have been reported in animal models while only a few reports of NOTES performed in humans exist. Several potential advantages of NOTES include the elimination of visible scars, less postoperative pain, and the reduction of postoperative complications, such as wound infection, abdominal wall pain, hernias, and adhesions. Current clinical applications of NOTES that are being studied heavily include its use in percutaneous endoscopic gastrostomy tube rescue and diaphragmatic pacing in intensive care unit patients. A number of barriers still exist regarding the technical challenges of transgastric NOTES, including access to the peritoneal cavity, the need for endoscope retroflexion for upper abdominal procedures, and endoscopic closure of the gastrotomy. The application of transgastric NOTES in urology has been limited to case reports in the porcine model, and no urologic procedure has been performed solely through a transgastric route. This article discusses the rationale of transgastric NOTES, its potential advantages and disadvantages, past and present work performed, current clinical applications, and its potential use in the future of urology.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".