Efficacy of Low Dose Chemoprophylaxis for Coccidioidomycosis Infection in Liver Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: Coccidioidomycosis (CM) infections among transplant recipients result in significant morbidity and mortality. The goal of our study was to establish the efficacy of low dose (LD) versus standard dose (LD, 50 mg daily) fluconazole in preventing CM infection. METHODS: This was a retrospective study utilizing electronic medical records of liver transplant recipients at the University of Arizona. The primary end point was post-transplant CM status, such as infection, complications and survival. RESULTS: We detected a statistically significant correlation between positive pre-transplant status and positive post-transplant status (hazards ratio: 8.25 (95% confidence interval: 1.028 - 66.192)). There was a trend towards improved survival in patients who had a positive post-transplant CM status in the SD group versus LD group (90.9% versus 81.3%), although not statistically significant. CONCLUSION: The risk of CM infection among transplant recipients in the absence of prophylaxis is associated with high morbidity and mortality. We currently use SD fluconazole as universal prophylaxis in all transplant recipients despite not establishing statistical significance between LD and SD. We believe that the survival trend detected may have not reached statistical significance due to low power impact. Since the standardization of SD prophylaxis at our institution, we have not diagnosed further new post-transplant CM infections.
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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 | 0.002 | 0.004 |
| 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 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".