Risk factors for late‐onset cytomegalovirus disease in donor seropositive/recipient seronegative kidney transplant recipients who receive antiviral prophylaxis
Bibliographic record
Abstract
A.A. Boudreault, H. Xie, R.M. Rakita, J.D. Scott, C.L. Davis, M. Boeckh, A.P. Limaye. Risk factors for late‐onset cytomegalovirus disease in donor seropositive/recipient seronegative kidney transplant recipients who receive antiviral prophylaxis. Transpl Infect Dis 2011: 13: 244–249. All rights reserved Background. Cytomegalovirus (CMV) disease occurs frequently after cessation of antiviral prophylaxis in CMV‐seronegative kidney transplant recipients from seropositive donors (D+R−), and the risk factors are incompletely defined. Method. We retrospectively assessed the incidence, clinical features, and risk factors for CMV disease in a cohort of D+R− kidney transplant recipients who received antiviral prophylaxis at a single US transplant center using descriptive statistics and Cox proportional hazards models. Results. CMV disease developed in 29 of 113 (26%) D+R− patients at a median of 185 days (interquartile range 116–231 days) post transplant, including CMV syndrome (66%) and tissue invasive disease (34%). The incidence of CMV disease was higher in patients who underwent re‐transplantation (57% vs. 24%) and this factor was independently associated with a higher risk of CMV disease in multivariable analysis (hazard ratio, 4.02; 95% confidence interval, 1.3–13; P =0.016). Other demographic and transplant variables were not independently associated with a risk of late‐onset CMV disease. Conclusions. Despite a comprehensive analysis of patient and transplant variables, only re‐transplantation was identified as a risk factor for CMV disease in D+R− kidney transplant recipients who received antiviral prophylaxis, but had limited clinical predictive value. The development of novel laboratory markers to identify patients at greatest risk for CMV disease should be a priority for future studies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".