A multicenter, retrospective cohort study on the diagnosis, treatment and natural history of eosinophilic gastrointestinal disorders in the Netherlands
Bibliographic record
Abstract
Non-Eosinophilic Esophagitis Eosinophilic Gastrointestinal Diseases (non-EoE EGIDs) are poorly understood. Evaluate clinical manifestations, diagnostics and treatment of non-EoE EGIDs at four hospitals in the Netherlands from 1991 to 2019. For this retrospective cohort study, centralized nationwide network and registry for cyto- and histopathology in the Netherlands (PALGA) was used. Seventy patients consented to participate. Median duration of follow up was 26 months, and median age was 36 years. About 44% had eosinophilic colitis (EoC) and 30% had > 1 GI location (multisite EGID). Most patients (91%) had mucosal type, 6% muscular and 3% serosal EGID. Three patients (4%) did not have follow up. Relapsing remitting in 21% (14/67) patients, with most being multisite (43%; 9/21). Single flares in 57% and chronically symptomatic in 22% of population. Concomitant atopy was seen in 29%. Normal endoscopy results in 61%; ileum was commonly identified normal area. Partial or complete symptom improvement to treatment seen in 71%. Results of the longitudinal retrospective Dutch study do not show progression from single site to multisite EGID or change in EGID type. We conclude that identifying patients requires further research as majority of patients had normal endoscopy and vague abdominal symptoms.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".