The Diagnostic Challenge of a False-Positive Cryptococcal Antigen in Chronic Meningitis with Suspected Indolent CNS B-Cell Lymphoproliferative Neoplasm
Bibliographic record
Abstract
A 47-year-old woman presented with a two-year history of progressive visual symptoms and headaches. Lumbar puncture revealed lymphocytic pleocytosis, elevated protein, low glucose, and a CSF CrAg titer of 1:256. She was treated empirically for cryptococcal meningitis with amphotericin B, flucytosine, and fluconazole for 15 months. Her symptoms persisted, and repeated CSF and serum CrAg, fungal cultures, and an extensive infectious workup were negative. CSF flow cytometry eventually demonstrated a monoclonal B-cell population suggestive of a lymphoproliferative process. Imaging, including MRI and PET scans, did not reveal systemic disease. A ventriculoperitoneal (VP) shunt was placed for symptom management. This case emphasizes the limitations of CrAg testing and the potential for false positives. It underscores the need for integrating clinical, laboratory, and imaging data when evaluating chronic meningitis.
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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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".