Postendoscopy Care for Patients Presenting With Esophageal Food Bolus Impaction: A Population-Based Multicenter Cohort Study
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Bibliographic record
Abstract
INTRODUCTION: Esophageal food bolus impactions (FBI) are a common gastrointestinal emergency. Appropriate management includes not only index endoscopy for disimpaction but also medical follow-up and treatment for the underlying esophageal pathology. We evaluated the appropriateness of postendoscopy care for patients with FBI and assessed patient-related, physician-related, and system-related factors that may contribute to loss to follow-up. METHODS: We conducted a retrospective, population-based, multicenter cohort study of all adult patients undergoing endoscopy for FBI in the Calgary Health Zone, Canada, from 2016 to 2018. Appropriate postendoscopy care was defined by a composite of a clinical or endoscopic follow-up visit, appropriate investigations (e.g., manometry), or therapy (e.g., proton-pump inhibitors or endoscopic dilation). Predictors of inappropriate care were assessed using multivariable logistic regression. RESULTS: A total of 519 patients underwent endoscopy for FBI: 25.2% (131/519) did not receive appropriate postendoscopy care. Half of the patients (55.3%, 287/519) underwent follow-up endoscopy or attended clinic, and among this group, 22.3% (64/287) had a change in their initial diagnosis after follow-up, including 3 new cases of esophageal cancer. Patients in whom a suspected underlying esophageal pathology was not identified at the index endoscopy were 7-fold (adjusted odds ratio 7.28, 95% confidence interval 4.49-11.78, P < 0.001) more likely to receive inappropriate postendoscopy follow-up and treatment, even after adjusting for age, sex, rural residence, timing of endoscopy, weekend presentation, and endoscopic interventions. DISCUSSION: One-quarter of patients presenting with an FBI do not receive appropriate postendoscopy care. This is strongly associated with failure to identify a potential underlying pathology at index presentation.
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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) | 0.001 | 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 it