1] Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway [2] Division of Nephrology, Department of Medicine, St Olav University Hospital, Trondheim, Norway.
1] Department of Cancer Research and Molecular Medicine, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway [2] Department of Internal Medicine, Levanger Hospital, Health Trust Nord-Trøndelag, Levanger, Norway [3] HUNT Research Centre, Faculty of Medicine, Norwegian University of Science and Technology, Levanger, Norway.
Kidney Int. 2014 Jun;85(6):1421-8. doi: 10.1038/ki.2013.500. Epub 2013 Dec 18.
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.
尿白蛋白是心血管（CV）死亡率的一个有充分记录的预测因子。然而，其日间变化幅度较大，对于风险预测所需的尿液样本数量尚无共识。为了解决这一问题，我们对来自基于人群的挪威特隆赫姆健康研究（第二 HUNT 研究）的 9158 名成年人进行了 13 年的随访。在提供了 3 份尿液样本的参与者中，评估了基于弗雷明汉变量加 1 个或 3 个白蛋白-肌酐比值（ACR）的 CV 死亡预测模型的预测性能。当将 ACR 用作连续变量时，对模型的区分度、校准度或重新分类均无改善。Akaike 信息准则的差异表明，使用 3 份尿液样本的模型整体拟合度不确定有所提高。对二分类白蛋白尿信息的标准分析表明，对于 ACR 水平低于 1.7mg/mmol 的情况，1 个样本就足够了。在较低水平下，具有 3 个样本的模型具有更好的整体拟合度。同样，在生存分析中，对于 ACR 水平高于 1.7mg/mmol 的情况，1 个样本就足以显示与 CV 死亡率的显著相关性（调整后的危险比为 1.37；95%CI 为 1.15-1.63）。对于较低的 ACR 水平，需要 2 或 3 个阳性尿液样本才能达到显著性。因此，当将 ACR 用作连续变量时，多次尿液采样并不能改善 CV 死亡预测。对于 ACR 水平为 1.0mg/mmol 或更低的切点，需要额外的尿液样本，并且随着样本数量的增加，相关性更强。
