Achalasia: Current therapeutic options
Bibliographic record
Abstract
Achalasia is an esophageal motor disorder characterized by impaired relaxation of the lower esophageal sphincter (LES) and absent peristalsis in the smooth muscle esophageal body. As a result, patients typically experience dysphagia, regurgitation, chest pain, and weight loss. Over the past 10-15 years, there has been a resurgence of interest in the evaluation of therapies for achalasia. Unfortunately, little progress in the development of effective pharmacological treatments has been made. Botulinum toxin injection provides some relief of symptoms in many patients but requires periodic reinjection that may provide progressively less benefit over time. There are now three well-established, safe, and effective therapies for the treatment of achalasia: pneumatic dilation (PD), laparoscopic Heller myotomy (LHM), and peroral endoscopic myotomy (POEM) which can lead to marked symptom improvement in most patients. Each treatment has a specific constellation of risks, benefits, and recurrence rate. The first-line treatment used will depend on patient preference, achalasia subtype, and local expertise. The recent impressive advances in both the art and science of achalasia therapy are explored with a comprehensive review of the various treatment modalities and comparative controlled clinical trials. In addition, key technical pearls of the procedural treatments are demonstrated.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".