The Clinical Significance of Eosinophils in Ulcerative Colitis: A Systematic Review
Bibliographic record
Abstract
BACKGROUND AND AIMS: Ulcerative colitis [UC] is characterised by an unpredictable disease course and variable response to therapy. Recent studies suggest a role for eosinophils in both pathogenesis and predicting treatment response. The goal of this study was to determine the association between eosinophils and clinical outcomes in UC. METHODS: A systematic review of the literature from database inception to May 2021 was performed to identify all studies evaluating the relationship between eosinophils and/or eosinophil-derived proteins [EDPs] and clinical outcomes, such as disease activity, clinical relapse, severity of disease, and response to treatment. RESULTS: A total of 55 studies were identified. Of these, 34 studies evaluated the relationship between eosinophils in colonic tissue and outcomes and 15 in blood. Eighteen studies assessed the relationship between EDPs and outcomes. In 25 of 34 studies, a positive correlation between eosinophils and/or EDPs and disease activity was reported, three studies found a negative correlation, and nine studies found no correlation. Positive correlations between eosinophils and clinical relapse were shown in four of nine studies, and with disease outcome severity in five of seven studies. Four of 15 studies showed that subjects with higher eosinophil levels had a poor response to treatment. CONCLUSIONS: These findings suggest that higher eosinophil levels may be associated with increased disease activity and poorer clinical outcomes and response to therapy. Future studies are needed to determine whether a distinct eosinophil-rich UC phenotype exists and whether eosinophil-targeted therapy can alter the disease course.
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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 | 0.006 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.011 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".