The accuracy of predicting cardiovascular death based on one compared to several albuminuria values

Albuminuria is a well-documented predictor of cardiovascular (CV) mortality. However, day-to-day variability is substantial, and there is no consensus on the number of urine samples required for risk prediction. To resolve this we followed 9158 adults from the population-based Nord-Trøndelag Health Study for 13 years (Second HUNT Study). The predictive performance of models for CV death based on Framingham variables plus 1 versus 3 albumin-creatinine ratio (ACR) was assessed in participants who provided 3 urine samples. There was no improvement in discrimination, calibration, or reclassification when using ACR as a continuous variable. Difference in Akaike information criterion indicated an uncertain improvement in overall fit for the model with the mean of 3 urine samples. Criterion analyses on dichotomized albuminuria information sustained 1 sample as sufficient for ACR levels down to 1.7 mg/mmol. At lower levels, models with 3 samples had a better overall fit. Likewise, in survival analyses, 1 sample was enough to show a significant association to CV mortality for ACR levels above 1.7 mg/mmol (adjusted hazard ratio 1.37; 95% CI 1.15-1.63). For lower ACR levels, 2 or 3 positive urine samples were needed for significance. Thus, multiple urine sampling did not improve CV death prediction when using ACR as a continuous variable. For cutoff ACR levels of 1.0 mg/mmol or less, additional urine samples were required, and associations were stronger with increasing number of samples.