Cryptococcus Pneumonia Complicating Churg-Strauss Syndrome
Bibliographic record
Abstract
Crytpococcus neoformans usually infects individuals who are HIV-infected or immunosuppressed for other reasons and clinically presents as meningoencephalitis, pneumonia or disseminated disease. We describe a 57-year-old man with history of asthma, allergic rhinosinusitis, nasal polyps and chronic receipt of low dose steroids who presented to the emergency department with fever, dry cough, respiratory distress and hematuria. His laboratory studies showed leukocytosis and eosinophilia with a negative HIV antibody test. CT scan of the chest showed right lower lobe patchy opacities. The patient deteriorated during hospitalization, developed hemoptysis and hypoxia, and was electively intubated. Repeat CT scan of the chest showed diffuse alveolar and interstitial opacities with mediastinal lymphadenopathy. The cytoplasmic anti-neutrophil cytoplasmic antibody (C-ANCA) was markedly elevated and the patient was diagnosed with Churg-Strauss Syndrome (CSS). Culture of bronchoalveolar lavage fluid yielded growth of Cryptococcus neoformans . The patient responded well to treatment with cyclophosphamide, corticosteroids, plasmapharesis and fluconazole. This case highlights the possibility that Cryptococcus neoformans can either infect or colonize patients who are immunosuppressed, including those with CSS. doi: http://dx.doi.org/10.4021/jmc755w
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".