Achalasia: incidence, prevalence and survival. A population‐based study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Studies of achalasia epidemiology are important as they often yield new insights into disease etiology. In this study, our objective was to carry out the first North American population-based study of achalasia epidemiology using a governmental administrative database. METHODS: All residents in the province of Alberta, Canada receive universal healthcare coverage as a benefit. The provincial health ministry, Alberta Health and Wellness, maintains a central stakeholder database of patient demographic information and physician billing claims. We defined an achalasia case as a billing claim submitted for the years 1996-2007 with an ICD-9-CM code of 530.0 or 530 and a Canadian Classification of Procedure treatment code of 54.92A (endoscopic balloon dilation) or 54.6 (esophagomyotomy). A preliminary validation study of the case definition demonstrated a sensitivity of 85% and specificity of 99% for known cases and controls. KEY RESULTS: A total of 463 achalasia cases were identified from 1995 to 2008 (59.6% males). Mean age at diagnosis was 53.1 years. In 2007, the achalasia incidence was 1.63/100,000 (95% CI 1.20, 2.06) and the prevalence was 10.82/100,000 (95% CI 9.70, 11.93). We observed a steady increase in the overall prevalence rate from 2.51/100,000 in 1996 to 10.82/100,000 in 2007. Survival of achalasia cases was significantly less than age-sex matched population controls (P < 0.0001). CONCLUSIONS & INFERENCES: Using a population-based approach, the incidence and prevalence of treated achalasia is 1.63/100,000 and 10.82/100,000, respectively. The disease appears to have a stable incidence but a rising prevalence. Survival of achalasia cases is significantly less than age-matched healthy controls.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it