Probabilistic Modeling of Cytomegalovirus Infection Under Consensus Clinical Management Guidelines
Bibliographic record
Abstract
BACKGROUND: Cytomegalovirus (CMV) is the most common viral pathogen after renal transplantation and remains a major therapeutic challenge with important clinical and economic implications from both direct and indirect consequences of infection. METHODS: This 5-year study modeled the relationship between CMV infection and biopsy-proven graft rejection, graft loss, or death after renal transplantation in an inception cohort using Canadian consensus guidelines for CMV management as a component of a detailed cost-analysis of viral infection. RESULTS: Probabilities of CMV viremia and syndrome/disease among 270 sequential graft recipients were 0.27 and 0.09, respectively; 91% of cases occurred in the first 6 months. Probability of CMV infection as the first event was 0.29, with a probability of subsequent biopsy-proven acute rejection (BPAR) of 0.05 (mean: 62+/-26 days, range: 32-85 days), whereas the probability of BPAR as the first event was 0.18, with a probability of subsequent CMV infection of 0.38 (mean: 63+/-31, range: 27-119 days). Probability of freedom from both CMV infection and BPAR throughout the period of observation was 0.53. Time-dependent Cox analysis showed that neither donor/recipient CMV risk stratum nor CMV infection influenced the risks of BPAR (P=0.24; P=0.74) or of graft loss or death (P=0.26; P=0.34). In contrast, BPAR significantly increased the risk of both subsequent CMV infection (hazard ratio=1.77, P=0.03) and of graft loss or death (hazard ratio=8.31, P<0.0001). CONCLUSIONS: Although current antiviral therapy seems to mitigate the reported deleterious effects of CMV infection on BPAR or graft survival, BPAR remains a significantly risk factor for both CMV infection and functional graft survival.
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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) | 0.000 | 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".