Systematic Review: Variability in Definitions of Fibrostenosis in Eosinophilic Oesophagitis
Bibliographic record
Abstract
BACKGROUND: Fibrostenosis is a serious complication of eosinophilic oesophagitis, but there is a lack of consensus regarding its definition and assessment. This poses a barrier in clinical care and research. AIM: To perform a systematic review to examine existing definitions and diagnostic methods of detection regarding fibrostenosis in eosinophilic oesophagitis. METHODS: We searched MEDLINE, Cochrane Library, EMBASE, Scopus, and Web of Science and included studies of paediatric and adult eosinophilic oesophagitis patients with fibrostenosis based on endoscopy, imaging, histopathology, functional studies, and biomarkers. We excluded studies with <10 patients. We chose fibrostenosis as the umbrella term, encompassing all definitions. RESULTS: We identified 230 studies. The four categories of fibrostenosis definitions were: (1) structural findings (stricture, rings, and/or narrowings) (n=204, 88.7%), (2) histology (n=85, 37.0%), (3) functional (functional lumen imaging probe) (n=15, 6.5%), and (4) biomarkers (n=7, 3.0%). Multiple definitions were used in 78 studies. Methods used to detect structural fibrostenosis included Eosinophilic Oesophagitis Endoscopic Reference Score fibrostenotic components, luminal diameter (endoscopy or imaging), need for dilation, and endoscopist or radiologist global impression. Methods used to detect histologic fibrostenosis included Eosinophilic Oesophagitis Histologic Scoring System lamina propria fibrosis, pathologist global impression, and basal zone hyperplasia. Methods used to detect functional fibrostenosis included distensibility and compliance. CONCLUSIONS: Significant variability exists in definitions and diagnostic methods of detection regarding fibrostenosis in eosinophilic oesophagitis. Lack of agreement hampers progress in further investigating this complication. Development of consensus criteria is necessary to provide clarity for clinical care and research.
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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 | 0.042 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.011 |
| Bibliometrics | 0.017 | 0.018 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".