Risk Factors for Late-Onset Cytomegalovirus Infection or Disease in Kidney Transplant Recipients
Bibliographic record
Abstract
BACKGROUND: CMV-D+/R- serostatus is the only well-established risk factor for late-onset cytomegalovirus (CMV) infection/disease (i.e., incident CMV infection/disease after cessation of prophylactic antiviral therapy). This study aimed to explore other potential risk factors for late-onset CMV infection/disease in kidney transplant recipients. METHODS: We conducted a retrospective cohort study of 641 kidney transplant recipients in Toronto, Canada, from January 1, 2003, to December 31, 2010. The cumulative incidence of late-onset CMV infection/disease was assessed using the Kaplan-Meier product-limit method. Potential risk factors for late-onset CMV infection/disease were examined using Cox proportional hazards regression models. RESULTS: Cumulative incidence estimates for CMV infection/disease after prophylaxis cessation in D+/R- versus D+/R+ versus D-/R+ patients were 26.2% versus 7.4% versus 3.1% at 6 months and 30.0% versus 7.7% versus 3.7% at 1 year, respectively. D+/R- serostatus (vs. R+ serostatus) and an estimated glomerular filtration rate of less than 45 mL/min (vs. ≥ 60 mL/min) at prophylaxis cessation were independently associated with late-onset CMV infection/disease (hazard ratio, 4.04 [95% confidence interval, 2.39-6.83]; and hazard ratio, 2.03 [95% confidence interval, 1.07-3.88], respectively). CONCLUSIONS: Patients with lower estimated glomerular filtration rate at prophylaxis cessation may be at an increased risk of late-onset CMV infection/disease and should be considered for more intensive CMV viral load monitoring, particularly within the first year after prophylaxis cessation.
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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 | 0.000 | 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 | 0.001 |
| 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".