Peroral endoscopic myotomy for complex achalasia and the POEM difficulty score: An update
Bibliographic record
Abstract
Abstract Objectives We present an update on the (peroral endoscopic myotomy (POEM) difficulty score [PDS] by introducing a novel knife with waterjet functionality. Methods This is a retrospective review of patients who underwent POEM between May 2018 and July 2023 at the Kingston Health Sciences Center. Demographic and procedural variables were compared using descriptive and inferential statistics. Results One hundred thirty‐nine consecutive POEMs were included in the study. Seventy‐four (56.7% male; aged 56.7 ± 16.5 years) complex achalasia (CA) and 65 (55.4% female; aged 47.3 ± 20.2 years) non‐CA POEM procedures were performed. PDS correlates moderately with procedural efficiency with a correlation coefficient of 0.595 (Spearman's p < 0.001). The mean efficiency for non‐CA was 3.3 ± 1.2 min/cm compared to CA as follows: type III 3.3 ± 1.3 min/cm; prior myotomy 5.3 ± 2.3 min/cm; ≧4 prior procedures 4.0 ± 1.7 min/cm; sigmoid type 5.2 ± 2.4 min/cm. The median PDS for non‐CA was 1 (1–5). In comparison, the median PDS for CA is as follows: type III 3 (2–4); prior myotomy 4 (3–5); ≧4 prior procedures 3 (1.25–4); sigmoid type 3 (2–4). PDS excluding the presence of spastic contractions correlated better with procedural velocity, with a correlation coefficient of 0.645 (Spearman's p < 0.001). Conclusions PDS continues to moderately correlate with procedural efficiency using the novel knife. The presence of spastic contractions correlated poorly with procedural efficiency. Thus, it may be omitted in further studies.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".