Management of Esophageal Achalasia in Quebec
Bibliographic record
Abstract
BACKGROUND: Esophageal achalasia is a defective relaxation of the lower esophageal sphincter with a loss of esophageal peristalsis causing dysphagia. Treatment can be Heller myotomy, pneumatic balloon dilation, Botox injections, peroral endoscopic myotomy (POEM) or medical. The main objective of the study was to measure the extent of post-treatment dysphagia depending on the type of treatment. METHODS: This was a retrospective study conducted at the Centre Hospitalier de l'Universite de Montreal (CHUM) between 2011 and 2017. All patients with manometric diagnostic of achalasia in our department were included. Data were collected with the electronic health record and a standardized post-treatment telephone survey to evaluate the extent of dysphagia and the use of proton pump inhibitor (PPI). RESULTS: A total of 169 patients were included. The most frequent treatments were Heller myotomy (60%), Botox injection (18%) and endoscopic balloon dilation (16%). There was a significant difference in the management of patients treated at the CHUM and outside the CHUM for the frequency of pneumatic dilation (28 vs. 7%; P = 0.001) and Heller myotomy (49 vs. 69%; P = 0.02). An Eckardt score ≤ 3 was found in 80% of patients. No significant score difference was found between the CHUM and outside CHUM groups or between the different treatments. The post-treatment use of PPI was of 49% and was not significantly different depending on the site or the type of treatment. CONCLUSION: Heller myotomy stays the most frequent treatment, especially outside our tertiary center. The rate of post-treatment dysphagia is low no matter the treatment choice. The use of PPI stays frequent regardless of the management site or the type of treatment used.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".