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首页> 外文期刊>BMC Nephrology >Predictive value of spot versus 24-hour measures of proteinuria for death, end-stage kidney disease or chronic kidney disease progression
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Predictive value of spot versus 24-hour measures of proteinuria for death, end-stage kidney disease or chronic kidney disease progression

机译:现货与24小时蛋白尿对死亡,终末期肾脏疾病或慢性肾脏疾病进展的预测价值

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Proteinuria is well recognised as a marker of chronic kidney disease (CKD), as a risk factor for progression of CKD among those with known CKD, and as a risk factor for cardiovascular events and death among both the general and CKD populations. Which measure of proteinuria is most predictive of renal events remains uncertain. We conducted a prospective study with 144 proteinuric CKD and kidney transplant recipients attending an outpatient clinic of a tertiary care hospital in Australia. We concurrently collected morning spot urine protein-to-creatinine ratio (UPCR), albumin-to-creatinine ratio (UACR) and 24-h urinary protein excretion (24-UPE) from each participant at baseline. The primary outcome was a composite of death, ESKD or >?30% decline in eGFR over 5-years. Secondary outcomes were each component of the composite outcome. For each proteinuria measure, we performed a Cox Proportional Hazards model and calculated the Harrell’s C-statistic and Akaike’s Information Criterion (AIC). After a mean follow-up of 5?years (range 4.4–6), 85 (59%) patients met the primary composite outcome including 23 deaths (16%). The multivariable analysis showed strong evidence of an association between each log-transformed proteinuria measurement and the primary composite outcome. [Log-UPCR 1.31 (95% CI 1.18–1.63), log-UACR 1.27 (1.11–1.45) and log-24-UPE 1.43 (1.20–1.71)]. The C-Statistic were similar for all three measures of proteinuria [UPCR: 0.74 (95% CI: 0.69–0.80), UACR: 0.75 (0.69–0.81), 24-UPE: 0.75 (0.69–0.81)] as were the models’ AIC (671, 668 and 665 respectively). For secondary outcomes, no proteinuria measure was significantly associated with death alone ([log-UPCR?=?1.18 (0.96–1.84), log-UACR?=?1.19 (1.00–1.55), log-24-UPE?=?1.19 (0.83–1.71)], whilst UACR and 24-UPE demonstrated marginally better association with ESKD and >?30% decline in eGFR respectively. [For ESKD, adj log-UACR HR?=?1.33 (1.07–1.66). For >?30% decline in eGFR, log-24-UPE adj HR?=?1.54 (1.13–2.09)]. In patients with stable, non-nephrotic CKD, all three measures of proteinuria were similarly predictive of hard clinical endpoints, defined as a composite of death, ESKD and >?30% decline in eGFR. However, which measure best predicted the outcomes individually is less certain.
机译:蛋白尿被公认为是慢性肾脏疾病(CKD)的标志物,是已知患有CKD的人群中CKD进展的危险因素,也是普通人群和CKD人群中心血管事件和死亡的危险因素。哪种蛋白尿最能预测肾脏事件尚不确定。我们对144名蛋白尿性CKD和肾移植受者在澳大利亚一家三级医院的门诊进行了前瞻性研究。我们同时从基线时收集了每个参与者的晨间尿蛋白/肌酐比值(UPCR),白蛋白/肌酐比值(UACR)和24小时尿蛋白排泄量(24-UPE)。主要结果是死亡,ESKD或5年内eGFR下降≥30%的综合结果。次要结果是综合结果的每个组成部分。对于每种蛋白尿测量,我们执行了Cox比例危害模型,并计算了Harrell的C统计量和Akaike的信息标准(AIC)。在平均随访5年(范围4.4–6)之后,有85名(59%)患者达到了主要的综合结局,包括23例死亡(16%)。多变量分析显示了强有力的证据,证明每次对数转换的蛋白尿测量结果与主要复合结果之间存在关联。 [Log-UPCR 1.31(95%CI 1.18–1.63),log-UACR 1.27(1.11–1.45)和log-24-UPE 1.43(1.20–1.71)]。三种模型的蛋白尿的C统计量均相似[UPCR:0.74(95%CI:0.69–0.80),UACR:0.75(0.69–0.81),24-UPE:0.75(0.69–0.81)] AIC(分别为671、668和665)。对于次要结局,没有蛋白尿指标与单独死亡显着相关([log-UPCR?=?1.18(0.96-1.84),log-UACR?=?1.19(1.00-1.55),log-24-UPE?=?1.19 (0.83–1.71)],而UACR和24-UPE与ESKD的关联性稍好,eGFR分别下降> 30%[ESKD,ad-log log-UACR HR?= 1.33(1.07–1.66)。 eGFR降低30%,log-24-UPE调整HR≥1.54(1.13-2.09)]。在患有稳定,非肾病性CKD的患者中,所有三种蛋白尿指标均可以预测硬性临床终点,定义为死亡,ESKD和eGFR下降> 30%的综合结果,但是,哪种方法能最好地单独预测结局并不确定。

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