Impact of viral load kinetics and recurrent cytomegalovirus infection in kidney transplantation
Bibliographic record
Abstract
Background We have shown that viral load kinetics during the first cytomegalovirus (CMV) viremic episode are important predictors of kidney transplant failure. This article evaluates the incremental hazard of recurrent CMV viremia and of viral load kinetics on graft and patient survival. Methods This retrospective cohort study included 2,464 sequential kidney transplants performed between 2008 and 2018. Care was delivered according to a uniform provincial protocol, and patients were followed for up to 13 years with standardized therapy and continuous monitoring of clinical course, CMV infection, viral load kinetics, and graft and patient outcomes. Results 434/2,464 (17.6%) patients (age range: 2–80 years) developed CMV infection, of whom 67/434 (15.4%) had 150 episodes of recurrent infection. Mean cumulative CMV frequency reached an asymptote of 21% at 500 days, with the highest rate (43%) in D+/R-, and lowest (1%) in D-/R- risk groups. Multinomial adjusted regression described a composite risk phenotype that included increased age, non-Caucasian race, diabetes, D+/R- status, and delayed graft function (p<0.005). Median cumulative viral load kinetic values rose progressively with the number of viremic episodes, maximum viral load rising from 3.8–5.1 log10 IU/mL, mean duration of viremia from 15–116 days, and viral AUC from 56.1–492.9 log10 IU/mL*days in patients with multiple episodes of CMV viremia. Predicted probability of graft failure and death were closely related to the cumulative duration of viremia and total viral load, with respective survival values declining to 30% and 7% in patients with elevated viremic indices and defined composite risk phenotype. Conclusions Patients with a recurrent CMV viremia post-transplant are at exceptionally high risk of transplant failure as measured by graft loss or death, which is determined by both composite risk phenotype and CMV viral load kinetics. Conventional prophylaxis appears to be inadequate to protect these patients from recurrent infection and its serious consequences, and alternative treatment strategies, with continuous long-term monitoring and rapid, effective therapy, are vital to maximize transplant success.
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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 | 0.005 |
| 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 | 0.001 |
| 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".