Clinical Utility of Cytomegalovirus Viral Load Testing for Predicting CMV Disease in D+/R- Solid Organ Transplant Recipients
Bibliographic record
Abstract
Despite prophylaxis, cytomegalovirus (CMV) disease is common in donor seropositive (D+)/recipient seronegative (R-) transplant patients after cessation of prophylaxis. Early detection of CMV may allow for pre-emptive therapy to prevent active disease. The clinical utility of quantitative plasma viral load measurements for predicting CMV disease was determined in 364 D+/R- organ transplant patients receiving prophylaxis (100 d of valganciclovir or oral ganciclovir). Measurements were performed every 2 weeks until day 100 and at months 4, 4.5, 5, 6, 8 and 12 post-transplant. CMV disease occurred in 64 (17.6%) patients by 12 months. Using a positive cut-off value of >400 copies/mL, sensitivity was 38%, specificity 60%, positive predictive value 17%, and negative predictive value 82% for prediction of CMV disease. Therefore, routine monitoring would have predicted disease in only 24/64 (38%) patients. The test characteristics were not improved by changing the viral load cut-off point for defining a positive result. Similarly, single time point measures at the end of prophylaxis or month 4 had low sensitivity for disease prediction. Overall, regular CMV plasma viral load measurements were only of modest value in predicting CMV disease.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".