Clinical predictors of achalasia
Bibliographic record
Abstract
Limited access to esophageal manometry (EM) may delay identification and treatment of patients with achalasia. In order to assess predictors to fast-track patients for manometric confirmation of achalasia, we compared the clinical, radiographic, and endoscopic characteristics of achalasia patients to patients with functional dysphagia without manometric features of achalasia (controls). Patients referred for esophageal manometry to assess functional dysphagia prospectively identified over a 12-month period were asked to participate in this study. The Achalasia Symptom Questionnaire (ASQ), a structured 11-question survey (score: 0-best, 67-worst), was completed by all consenting patients. ASQ scores, esophago-gastro-duodenoscopy and upper gastro-intestinal (UGI) contrast study findings were compared between patents with subsequently confirmed achalasia and those in whom achalasia was excluded by EM. Univariate logistic regression identified predictors that were tested by multivariate logistic regression to generate the model. Of the 803 EM performed over this 12-month period, 95 patients were referred specifically to assess functional dysphagia. Of these, 50 were confirmed to have achalasia, and 45 had dysphagia without manometric evidence for achalasia and hence comprised the control group. ASQ scores were higher in achalasia patients (37+/-13 versus 23+/-10). Endoscopy and/or contrast esophagogram reports were available in 92% achalasia patients and 80% controls. Significant predictors for achalasia identified on univariate logistic regression included ASQ score, abnormal findings on endoscopy, and contrast UGI study. Using multivariate logistic regression, we were able to accurately predict the probability of achalasia to be P where P=ey/(1+ey) and y=5.6+(0.089xASQ)+(2.088xEGD)+(3.083xUGI), e=exponential constant 2.7182, esophagogastroduodenoscopy (EGD) and UGI=0 if normal and 1 if abnormal. Dropping the predictor ASQ, the formula changes to y=-2.7+(1.987xEGD)+(2.861xUGI). Using only noninvasive investigations (i.e. eliminating EGD), the formula changes to y=-4.9653+(0.0951xASQ)+(3.4312xUGI). The probability of achalasia can be calculated in patients with functional dysphagia based on clinical, endoscopic, and radiographic findings allowing for a prioritization of EM studies.
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How this classification was reachedexpand
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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".