Pulmonary cryptococcosis in non-AIDS patients
Bibliographic record
Abstract
PURPOSE: To clarify the clinical features and imaging characteristics of non-AIDS patients with pulmonary cryptococcosis. METHODS: We retrospectively collected 15 HIV-negative patients with pathology-proved pulmonary cryptococcosis from Sep 1992 to Jan 2008. Their medical records and radiological data were reviewed and analyzed. RESULTS: Only one patient was asymptomatic.Thirteen patients were immunocompetent and two were immunosuppressed. Three patients had associated cryptococcosis meningitis. The most common radiographic abnormalities were multiple pulmonary nodules or masses, seen in 8 and 5 cases of patients respectively. 14 patients received specific therapy for Cryptococcus neoformans. Two patients died. In the 11 patients with isolated pulmonary cryptococcosis, treatment consisted of fluconazole alone (n=7), in combination with amphotericin B (n=2), and both 5-flucytosine and amphotericin B (n=2). For the other 2 patients with cryptococcosis meningitis, one was treated with amphotericin B alone and the other with fluconazole combined with amphotericin B and 5-flucytosine. CONCLUSIONS: Non-AIDS patients might also susceptible to cryptococcosis infection. Histological examination is the principal method of diagnosis. The most common CT findings are solitary or multiple nodules with or without cavitation in the subpleural areas of the lung.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".