Clinical management and burden of cytomegalovirus in D+/R-Kidney transplant recipients in Canada
Bibliographic record
Abstract
Purpose: To document prophylactic practices, infection patterns, and disease burden to inform strategies for CMV management in high-risk kidney transplant recipients. Methods: A retrospective cohort of 311 consecutive CMV D+/R- kidney recipients were enrolled from 7 Canadian programs over 4 years (2018-2021) to provide data on demographic, clinical, therapeutic and health resource use during the 1st year post-transplant. Results: Themedian age was 58 (46, 67) years, 69% were male, and 53% were White. Diabetes was the principal cause of kidney failure (19%). 208 (69%) received a deceased donor graft; 76 (24%) had ATG induction, and 84% had maintenance therapy with tacrolimus and MMF/MPA ± prednisone. All received antiviral prophylaxis, 90% with valganciclovir, for a median of 180 days. 106 (34%) developed CMV viremia (median peak viral load 14,224 IU/ml) at a median of 218 days, of whom 46 (43%) had CMV disease and 15 (14%) had recurrent infection. Myelotoxicity occurred in 121 (39%) patients at a median of 88 days, lasting a median of 30 days. Opportunistic infections occurred in 119 patients (38%) at a median of 53 days. 141 patients (45%) were hospitalized, 50 (16%) more than once. 20 patients (6%) had biopsy-confirmed rejection, and 293 (94%) were alive with a functioning graft at 1 year. Conclusion: Current prophylaxis strategies fail to prevent CMV infection in 34% of high-risk patients. Myelotoxicity, opportunistic infection, reduced immunosuppression, and hospitalization remain common and serious complications. More effective and less toxic personalized treatment strategies are required to minimize these risks and burdens.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".