Evaluating the Prognostic Implication of the Collins Histology Scoring System in a Pediatric Eastern Ontario Population With Eosinophilic Esophagitis
Bibliographic record
Abstract
INTRODUCTION: Collins et al developed a histology scoring system (EoE HSS) to assess multiple pathologic features. The aim of this study is to identify if the EoE HSS can better detect endoscopic and symptom improvement vs the Peak Eosinophilic Count (PEC). METHODS: A retrospective chart review was performed for patients during 2014-2016. All patients ≤18 years old with a diagnosis of EoE and whose records included initial and follow-up upper gastrointestinal endoscopies were included. Severity and extent of endoscopic features were scored using 8 parameters, from normal to maximum change for each location of the esophageal biopsy. RESULTS: Forty patients with EoE were included in the study, of which 35 (87.5%) patients demonstrated symptom and 25 (62.5%) endoscopic improvement at the time of follow-up. In the proximal esophagus, the EoE HSS outperformed the change in eosinophil count of the Children's Hospital of Eastern Ontario (CHEO) practice in predicting endoscopic improvement by 16.8% when examining the change in grade and 17.1% when examining the change in stage scores. CONCLUSIONS: At our institution, adoption of the EoE HSS in assessing biopsies of EoE patients might be warranted, compared to the traditional practice. However, a bigger sample size may give a more robust difference in all locations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".