WATERSHED INFARCTION DUE TO ACUTE HYPEREOSINOPHILIA
Bibliographic record
Abstract
Hypereosinophilia typically results from a parasitic, neoplastic, vasculitic, or allergic cause. However, when elevated blood eosinophil levels (≥1500/μL) persist beyond 6 months and show evidence of organ involvement (other than skin) without identifiable cause, the criteria for idiopathic hypereosinophilia are met. Idiopathic hypereosinophilia can affect multiple organ systems. Up to 65% of patients have neurologic manifestations, including peripheral neuropathy, encephalopathy, or thromboembolic infarction.1 Previously reported thromboembolic events have involved large, intracranial vessels2 and were attributed to the hyperviscous, hypercoaguable state, often accompanied by cardiac dysfunction. We report a patient with acute, severe hypereosinophilia complicated by extensive watershed infarction. Possible mechanistic causes include (1) local thrombus formation from a hyperviscous state or (2) distant microthromboemboli. ### Case report. A 16-year-old, previously healthy male was hospitalized after 2 weeks of cough and 4 days of fever. The initial examination revealed decreased air entry bilaterally. Blood work noted leukocytosis 77.4 × 109/L, with eosinophils 55.3 × 109/L, neutrophils 6.6 × 109/L, and no blasts. Hemoglobin was 115 g/L, and platelets were 154,000 × 109/L. His electrolytes, calcium, phosphorus, uric acid, and renal and liver function tests were normal. Neck and chest CT revealed lymph nodes (≤1.5 cm) and patchy “ground-glass” areas in the …
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".