A Canadian multicenter pediatric eosinophilic esophagitis cohort: Evidence for a nondilation approach to esophageal narrowing
Bibliographic record
Abstract
Objectives: Improving characterization of the narrowing phenotype in pediatric eosinophilic esophagitis (EoE). Methods: New pediatric EoE diagnoses from 2015 to 2018 were retrospectively identified in Vancouver (BC), Northern Alberta (AB), Hamilton (ON), and Nova Scotia (NS). Incidence rates were calculated using 2016 Federal census data. Clinical, endoscopic, and histologic data were gathered from diagnosis until the end of the follow-up period (fall 2019). Results: The incidence of EoE in patients less than 15 years old was 5.4 per 100,000 person-years. Of the 332 new diagnoses, 40 (12.0%) had endoscopically identified esophageal narrowing at diagnosis or during the follow-up period, with a subset of 11 (27.5% of narrowed cohort) patients undergoing mechanical esophageal dilation. The median age at diagnosis and median duration of symptoms were higher in the cohort with narrowing than those without. Patient-reported food bolus impaction and dysphagia were associated with esophageal narrowing. Trachealization was the endoscopic finding most commonly associated with esophageal narrowing. Of the 65 esophagogastroduodenoscopies performed in the follow-up of a known esophageal narrowing, 4 of the 31 (13%) had resolution of this finding post mechanical dilation, and 19 of the 39 (49%) had resolution of the narrowing after initiation of new medical or dietary treatments (without dilation). Conclusions: mechanical dilation.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".