Guide to endoscope selection for peroral endoscopic myotomy procedures
Bibliographic record
Abstract
Background and Aims: Peroral endoscopic myotomy (POEM) is the standard of care for achalasia treatment. Although prior studies have addressed technique, electrosurgical settings, and accessories, there is limited guidance on endoscope selection. This review highlights key characteristics, advantages, and limitations of commonly used endoscopes for POEM. Methods: Endoscopes from 3 major vendors were reviewed and compared across several parameters: distal outer diameter (OD), accessory channel size and position, working length, tip angulation, and ergonomics. Results: Scopes with a 3.2-mm accessory channel demonstrated greater suction capacity than 2.8-mm channels when accessory tools are in place. Vendor 1 (Olympus, Center Valley, Pa, USA) offers a slim pediatric colonoscope with a 3.2-mm channel and high maneuverability, maintaining a comparable OD to other scopes. Newer diagnostic endoscopes from vendor 2 (Fujifilm, Tokyo, Japan), including slim designs with 7.9-mm OD and 3.2-mm channels, provide enhanced suction and tip control. Conclusions: Various endoscopes are suitable for POEM, each with specific tradeoffs. Slim colonoscopes offer better maneuverability but may limit device compatibility. Intermediate-length scopes and newer 3.2-mm diagnostic scopes improve function and flexibility. Endoscopy units performing third-space procedures should consider adopting diagnostic scopes with 3.2-mm channels, which may represent a future standard of care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.045 | 0.042 |
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".