TP6.2.14 Outcome of POEM (Per-oral endoscopic myotomy) for achalasia
Bibliographic record
Abstract
Abstract Aims Laparoscopic Heller’s myotomy (LHM) has been the surgical gold standard for treatment of oesophageal achalasia. Peroral endoscopic myotomy (POEM) has been proposed as an alternative technique. The aim of this study was to assess the safety and efficacy of POEM for achalasia in our unit. Methods We have operated on 202 patients for oesophageal achalasia since 2005: 107 had LHM, 86 had POEM, and 9 had an oesophagectomy. We assessed the clinical outcome of POEM comparing pre- and postoperative endoscopic, radiologic and manometric findings, as well as Eckardt-, GERD- and DsQoL score for achalasia. All follow-up patients were offered endoscopy. Results Data were completed for the first 45 POEM patients. The average age was 45 years. 18 patients (40%) had prior achalasia treatment. The median hospital stay was 2 days (2-5). There was no mortality, but 4 patients (9%) had post-operative complications. The median follow-up was 24 months (12-49). Clinical success (Eckardt score ≤ 3) was achieved in 39 patients (87%). Thirteen patients (29%) were taking PPIs for chest symptoms. Eleven of these underwent pH studies of whom only 1 had a DeMeester score > 14.5. Of the 24 patients who had post-operative endoscopy, 40% was diagnosed with oesophagitis grade A, yet only 5 of them were symptomatic. Conclusions POEM appears to be safe and effective and warrants consideration as first-line therapy in expert achalasia centres. Longer term randomized studies comparing the outcomes of POEM with LHM and pneumatic dilatation will determine its place in the treatment of achalasia.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".