Barr Elizabeth Lm, Reutens Anne, Magliano Dianna J, Wolfe Rory, Lu Zhong X, Sikaris Ken A, Tanamas Stephanie K, Atkins Robert, Chadban Steve, Shaw Jonathan E, Polkinghorne Kevan R
Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
Menzies School of Health Research, Darwin, Northern Territory, Australia.
Nephrology (Carlton). 2017 Mar;22(3):243-250. doi: 10.1111/nep.12759.
Uncertainties about the role of cystatin C-based estimated glomerular filtration rate (eGFR) in the prediction of cardiovascular disease (CVD) beyond traditional CVD risk factors remain. We assessed contributions of eGFR to CVD and mortality in the general population.
Using 14 year follow-up data on 9353 adults without a reported history of CVD from the Australian Diabetes, Obesity and Lifestyle study, we assessed the contributions of eGFR (assessed by cystatin C (eGFR ) and serum creatinine (eGFR ) and albuminuria (uACR) to total and CVD mortality.
After adjusting for age, sex, CVD risk factors and uACR, compared with an eGFR >90 mL/min per 1.73 m , eGFR <60 mL/min per 1.73 m was associated with 56% and 73% increases in the risks for all-cause and CVD mortality, respectively. The respective changes for the c-statistic when eGFR was added to a risk prediction model were 0.003 (95% confidence interval: 0.001 to 0.005) and 0.002 (95% confidence interval: -0.001 to 0.006). The net proportion of non-events assigned a lower-risk category significantly improved with the addition of eGFR (non-event net reclassification index eGFR : 1.0% and eGFR : 1.5%) for all-cause mortality, but for CVD mortality, improvements were only significant when eGFR was combined with uACR. The net proportion of events assigned a higher-risk category was not significantly improved.
In our community-based cohort, reduced eGFR was associated with all-cause and CVD mortality. The addition of chronic kidney disease measures to risk prediction models improved overall risk stratification among those at low risk as opposed to those at high baseline risk of mortality.
基于胱抑素C的估算肾小球滤过率(eGFR)在预测心血管疾病(CVD)方面,超出传统CVD危险因素的作用仍存在不确定性。我们评估了eGFR对一般人群中CVD和死亡率的影响。
利用澳大利亚糖尿病、肥胖与生活方式研究中9353名无CVD病史成年人的14年随访数据,我们评估了eGFR(通过胱抑素C评估的eGFR和血清肌酐评估的eGFR)及蛋白尿(uACR)对全因死亡率和CVD死亡率的影响。
在调整年龄、性别、CVD危险因素和uACR后,与eGFR>90 ml/min per 1.73 m²相比,eGFR<60 ml/min per 1.73 m²分别使全因死亡率和CVD死亡率风险增加56%和73%。将eGFR添加到风险预测模型时,c统计量的相应变化分别为0.003(95%置信区间:0.001至0.005)和0.002(95%置信区间:-0.001至0.006)。添加eGFR后,被归为低风险类别的非事件净比例显著改善(全因死亡率的非事件净重新分类指数eGFR:1.0%,eGFR:1.5%);但对于CVD死亡率,仅当eGFR与uACR联合时改善才显著。被归为高风险类别的事件净比例未显著改善。
在我们基于社区的队列中,eGFR降低与全因死亡率和CVD死亡率相关。在风险预测模型中添加慢性肾脏病指标可改善低风险人群而非高基线死亡风险人群的总体风险分层。