Time-Varying Proteinuria and the Risk of Cardiovascular Disease and Graft Failure in Kidney Transplant Recipients
Bibliographic record
Abstract
Introduction: Proteinuria is recognized as an independent risk factor for cardiovascular disease in kidney transplant recipients, but previous studies have not considered the impact of changes in urine protein over time. Research Question and Design: We used time-dependent, multivariable Cox proportional hazards models in this observational cohort study of adult kidney transplant recipients to evaluate whether proteinuria measured by dipstick on random spot urine samples starting from 1-month post-transplant was associated with the risk of major adverse cardiac events and graft loss. Results: A total of 144 major adverse cardiac events, defined as acute myocardial infarction, cerebrovascular accident, revascularization, or all-cause mortality, were observed in 1106 patients over 5728.7 person-years. Any level of proteinuria greater or equal to trace resulted in a two-fold increase in the risk of major adverse cardiac events (hazard ratio 2.00 [95% confidence interval 1.41, 2.84]). This relationship was not found to be dose-dependent (hazard ratios of 2.98, 1.76, 1.63, and 1.54 for trace, 1+, 2+, and 3+ urine protein, respectively). There was an increased risk of graft failure with greater urine protein concentration (hazard ratios 2.22, 2.85, 6.41, and 19.71 for trace, 1+, 2+, and 3+, respectively). Conclusion: Urine protein is associated with major adverse cardiac events and graft loss in kidney transplant recipients. The role of interventions to reduce proteinuria on decreasing the risk of adverse cardiovascular and graft outcomes in kidney transplant recipients requires further study.
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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 | 0.000 | 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".