COVID-19 Pneumonia or Hypereosinophilic Syndrome?
Bibliographic record
Abstract
Hypereosinophilic syndromes (HESs) are a group of disorders characterized by pathological proliferation of eosinophils. Diagnostic criteria include eosinophil count of 1,500/mm 3 or higher, presence of organ involvement and exclusion of other causes of eosinophilia for at least 6 months. A 69-year-old male patient was referred to the pandemic clinic with a preliminary diagnosis of coronavirus disease 2019 (COVID-19) with fever and dyspnea. Computed tomography (CT) was compatible with COVID-19, nasopharyngeal swab polymerase chain reaction (PCR) was negative for two times. He had 20,000/mm 3 eosinophilia and retrospective examinations showed that he have had eosinophilia for more than 1 year. Platelet-derived growth factor receptor alpha ( PDGFRa ) resulted positively. After starting parenteral methylprednisolone with a dose of 1 mg/kg, he was discharged with oral maintenance therapy. In outpatient follow-up, it was observed that eosinophilic pneumonia completely regressed. HES may occur with multiple system and organ involvement and findings. In the differential diagnosis of patients presenting with heart failure, pulmonary involvement and eosinophilia, HES must definitely be considered. J Med Cases. 2020;11(12):400-402 doi: https://doi.org/10.14740/jmc3587
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".