Cryptococcal meningitis complicating sarcoidosis
Bibliographic record
Abstract
BACKGROUND: Cryptococcal meningitis is an uncommon but severe complication of sarcoidosis. METHODS: We present 2 patients with cryptococcal meningitis complicating sarcoidosis and compared findings with 38 cases reported in the literature. RESULTS: When analyzing our patients and 38 cases reported in the literature, we found that median age of sarcoidosis patients with cryptococcal meningitis was 39 years (range 30-48); 27 of 33 reported cases (82%) had a history of sarcoidosis. Only 16 of 40 patients (40%) received immunomodulating therapy at the time of diagnosis of cryptococcal meningitis. The diagnosis of cryptococcal meningitis was delayed in 17 of 40 patients (43%), mainly because of the initial suspicion of neurosarcoidosis. Cerebrospinal fluid (CSF) examination showed mildly elevated white blood cell count (range 23-129/mm). Twenty-nine of 32 cases (91%) had a positive CSF culture for Cryptococcus neoformans and 25 of 27 cases (93%) had a positive CSF C neoformans antigen test. CD4 counts were low in all patients in whom counts were performed (84-228/mL). Twelve patients had an unfavorable outcome (32%), of which 7 died (19%) and 24 patients (65%) had a favorable outcome. The rate of unfavorable outcome in patients with a delayed diagnosis was 7 of 17 (41%) compared to 5 of 28 (21%) in patients in whom diagnosis was not delayed. CONCLUSION: Cryptococcal meningitis is a rare but life-threatening complication of sarcoidosis. Patients were often initially misdiagnosed as neurosarcoidosis, which resulted in considerable treatment delay and worse outcome. CSF cryptococcal antigen tests are advised in patients with sarcoidosis and meningitis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".