The Cost of Achalasia: Quantifying the Effect of Symptomatic Disease on Patient Cost Burden, Treatment Time, and Work Productivity
Bibliographic record
Abstract
INTRODUCTION: Although the incidence of achalasia is low, the burden of suffering is high because it is a chronic incurable disease that predominantly affects young persons. This article aims to describe the impact of achalasia on health-related quality of life, patient cost burden, time dedicated to treatment, and work productivity. METHODS: Consecutive patients enrolled in a clinical trial comparing laparoscopic myotomy with pneumatic dilatation from 4 sites across Canada (whose clinical and manometric diagnosis was confirmed) were studied using standardized patient-reported outcomes instruments, including the Achalasia Severity Questionnaire (ASQ), the Medical Outcomes Study 36-item Short Form Questionnaire (SF-36), and the Gastrointestinal Disease-Specific Quality of Life (GIQLI) questionnaire. The authors also measured health care utilization. RESULTS: Questionnaires were completed by 54 patients (median age = 53.5 years; range = 25-78 years; 50.0% male). Patients had been experiencing symptoms for a mean of 4.5 years (standard deviation = 6.1), and 42.6% were on medication for symptom relief. Among them, 74.1% reported that their disease limited their lifestyle. Patients spent an average of CAD$30.70 a month on medication; 37.0% reported that their disease interfered with their work, and patients missed an average of 10.2 days per 6 months. Patients also spent an average of CAD$24.30 on transportation to and from each clinical appointment. CONCLUSION: Achalasia substantially limits the lifestyle of patients with the disease. It also implies a financial burden of care for patients and leads to decreased work productivity.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".