Microalbuminuria post‐renal transplantation: relation to cardiovascular risk factors and C‐reactive protein
Bibliographic record
Abstract
Microalbuminuria predicts graft loss and all-cause mortality in renal transplant recipients. In the general population, it clusters with both traditional cardiovascular risk factors and elevated C-reactive protein (CRP). Our objective was to define the relationship between microalbuminuria and these risk factors in stable renal transplant recipients. We identified 222 stable recipients who were minimum two months post-transplant and provided three urine albumin-to-creatinine ratio (ACR) measurements, excluding those with recent illness and proteinuria. Microalbuminuria was defined as averaged ACR > or =2.0 in men and 2.8 mg/mmol in women (Canadian Diabetes Association 2003). Risk factors associated with microalbuminuria were determined by multivariate logistic regression analysis. Averaged ACR correlated to CRP (R = 0.21, p = 0.001). Prevalence of microalbuminuria was 48% (108/222). Patients with microalbuminuria had higher CRP (7.01 +/- 8 vs. 3.21 +/- 3 mg/L, p < 0.0001) and systolic BP (129 +/- 17 vs. 123 +/- 12 mmHg, p = 0.004). Microalbuminuria was associated with increasing CRP [odds ratio 1.129 per 1 mg/L (95% CI 1.058-1.204), p = 0.0002], SBP [1.248 per 10 mmHg (1.023-1.522), p = 0.029] and smoking [1.938 (1.023-3.672), p = 0.042]. Post-transplant microalbuminuria is prevalent and is associated with elevated CRP, elevated BP, and smoking. Its relationship to these factors suggests it may be an indicator of graft and patient health.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".