Geographic differences in disease expression of cryptococcosis in solid organ transplant recipients in the United States.
Bibliographic record
Abstract
BACKGROUND: Whether there are geographic differences in clinical presentation of cryptococcosis in solid organ transplant (SOT) recipients in the United States (US) is not known. MATERIAL/METHODS: Patients comprised a cohort of 120 SOT recipients from US transplant centers who fulfilled the EORTC/MSG criteria for cryptococcal disease. RESULTS: Central nervous system, pulmonary, and cutaneous cryptococcal disease were observed in 51% (61/120), 64% (77/120), and 15% (18/120) of the patients, respectively. Cutaneous disease was documented in 9% (3/32) of the patients from South Atlantic region, 19% (6/32) from Mid Atlantic, 26% (6/23) from Southern, 7% (2/29) from Midwestern, and in 1 of 4 patients from the Northwestern region of the US. When controlled for age, immunosuppressive regimen, type of transplant, and renal failure at baseline, patients from the Southern compared with other regions of the US were significantly more likely to have cutaneous cryptococcal disease (OR 3.8, 95% CI 1.1-14, P=0.045). CONCLUSIONS: Post-transplant cryptococcosis is more likely to present with cutaneous disease in the Southern region compared with other regions in the US. This predilection for cutaneous cryptococcosis could not be explained on the basis of differences in immunosuppression or the type of transplant. Whether our findings are related to strain-related variations in characteristics of the yeast or other transplant variables remains to be determined.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".