Refractory erythroderma in idiopathic hypereosinophilic syndrome: A case treated with mepolizumab and abrocitinib
Bibliographic record
Abstract
Chronic erythroderma with persistent hypereosinophilia presents significant diagnostic and therapeutic challenges. We report the case of a 26-year-old man with a 6-year history of refractory erythroderma and eosinophilia. Extensive workup excluded malignancy, autoimmune disease, and secondary causes of eosinophilia. Genetic testing revealed no pathogenic variants but identified a variant of uncertain significance in HTRA2. High-dose mepolizumab monotherapy significantly reduced eosinophil counts but yielded modest clinical improvement. The addition of abrocitinib, previously ineffective alone, led to rapid and sustained symptomatic and biochemical remission. The patient experienced marked improvement in pruritus, scaling, and quality of life; subsequent withdrawal of mepolizumab led to symptom recurrence. This case highlights the complexity of managing erythroderma with hypereosinophilia and suggests that eosinophilia may be a disease marker rather than the primary symptom driver. Combined targeting of eosinophils and broader cytokine pathways via anti-interleukin-5 and JAK1 inhibition may be necessary for effective disease control in refractory cases.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".