Bibliographic record
Abstract
BACKGROUND: Achalasia is the most common major esophageal motility disorder, characterized by impaired lower esophageal sphincter relaxation and absent or ineffective peristalsis. Peroral endoscopic myotomy (POEM), pneumatic dilation, and botulinum toxin injection are the main endoscopic therapies available. This review highlights recent advances, technical variations, and updated evidence on the efficacy and safety of POEM. SUMMARY: POEM has emerged as a highly effective and minimally invasive treatment for achalasia, with randomized controlled trials demonstrating excellent long-term clinical success and durability. Its safety profile and capacity for a tailored myotomy offer distinct advantages over alternative therapies. However, gastroesophageal reflux disease (GERD) remains a key concern. Ongoing efforts are focused on optimizing procedural techniques, including myotomy length and orientation, sling fiber preservation, and the addition of fundoplication. Additionally, training protocols, patient selection criteria, and strategies to prevent and predict GERD are critical areas of development. Future research should aim to refine follow-up strategies and define objective measures of success to enhance the safety, efficacy, and accessibility of POEM. KEY MESSAGES: Endoscopic treatments of achalasia, particularly POEM, offer effective and durable outcomes. Optimizing technique, refining training, and managing GERD are essential for improving safety and long-term success.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".