Identifying Predictors of Central Nervous System Disease in Solid Organ Transplant RecipientsWith Cryptococcosis
Bibliographic record
Abstract
BACKGROUND: Cerebrospinal fluid (CSF) analysis is often deferred in patients with cryptococcal disease, particularly in the absence of neurologic manifestations. We sought to determine whether a subset of solid organ transplant (SOT) recipients with high likelihood of central nervous system (CNS) disease could be identified in whom CSF analysis must be performed. METHODS: Patients comprised a multicenter cohort of SOT recipients with cryptococcosis. RESULTS: Of 129 (88%) of 146 SOT recipients with cryptococcosis who underwent CSF analysis, 80 (62%) had CNS disease. In the overall study population, abnormal mental status, time to onset of cryptococcosis more than 24 months posttransplantation (late-onset disease), serum cryptococcal antigen titer more than 1:64, and fungemia were independently associated with an increased risk of CNS disease. Of patients with abnormal mental status, 95% had CNS cryptococcosis. When only patients with normal mental status were considered, three predictors (serum antigen titer >1:64, fungemia, and late-onset disease) independently identified patients with CNS cryptococcosis; the risk of CNS disease was 14% if none, 39% if one, and 94% if two of the aforementioned predictors existed (chi for trend P<0.001). CONCLUSIONS: CSF analysis should be strongly considered in SOT recipients with cryptococcosis who have late-onset disease, fungemia, or serum cryptococcal antigen titer more than 1:64 even in the presence of normal mental status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".