首页> 外文期刊>Circulation journal >Comparison of predictability of future cardiovascular events between chronic kidney disease (CKD) stage based on CKD epidemiology collaboration equation and that based on modification of diet in renal disease equation in the Japanese general population - Iwate Kenco study -
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Comparison of predictability of future cardiovascular events between chronic kidney disease (CKD) stage based on CKD epidemiology collaboration equation and that based on modification of diet in renal disease equation in the Japanese general population - Iwate Kenco study -

机译:在日本普通人群中,基于CKD流行病学协作方程的慢性肾脏病(CKD)期与基于饮食调整的肾脏疾病方程之间的未来心血管事件的可预测性比较-岩手研科研究-

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Background:Whether estimated glomerular filtration rate (eGFR) calculated using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) Study equation (eGFRCKDEPI) improves risk prediction compared to that calculated using the Modification of Diet in Renal Disease (MDRD) study equation (eGFRMDRD) has not been examined in a prospective study in Japanese people. Methods and Results:Participants (n=24,560) were divided into 4 stages (1, ≥90; 2, 60-89 (reference); 3a, 45-59; -2) according to eGFRCKDEPI or eGFRMDRD. Endpoints were all-cause death, myocardial infarction (MI) and stroke. Area under the receiver operating characteristic curves (95% confidence intervals) for predicting all-cause death, MI and stroke by eGFRCKDEPI vs. eGFRMDRD were 0.680 (0.662-0.697) vs. 0.582 (0.562-0.602); 0.718 (0.665-0.771) vs. 0.642 (0.581-0.703); and 0.656 (0.636-0.676) vs. 0.576 (0.553-0.599), respectively. Multivariate-adjusted Cox regression and Poisson regression analysis results were similar for adjusted incidence rates and adjusted hazard ratios in each corresponding stage between the 2 models and no differences were found in model assessment parameters. Net reclassification improvement (NRI) for predicting all-cause death, MI and stroke were estimated to be 6.7% (P0.001), -1.89% (P=0.029) and -0.20% (P=0.421), respectively. Conclusions:Better discrimination was achieved using eGFRCKDEPI than eGFRMDRD on univariate analysis. NRI analysis indicated that the use of eGFRCKDEPI instead of eGFRMDRD offered a significant improvement in reclassification of death risk.
机译:背景:与使用慢性肾脏病饮食研究(MDRD)研究方程式(eGFRMDRD)计算得出的估计值相比,使用慢性肾脏病流行病学协作(CKD-EPI)研究方程式(eGFRCKDEPI)计算得出的估计肾小球滤过率(eGFR)是否可以提高风险预测。 )尚未在日本人的前瞻性研究中进行过检查。方法和结果:根据eGFRCKDEPI或eGFRMDRD将参与者(n = 24,560)分为4个阶段(1,≥90; 2、60-89(参考); 3a,45-59; -2)。终点是全因死亡,心肌梗塞(MI)和中风。通过eGFRCKDEPI与eGFRMDRD预测全因死亡,心梗和中风的接收器工作特征曲线下的面积(95%置信区间)为0.680(0.662-0.697)对0.582(0.562-0.602); 0.718(0.665-0.771)对0.642(0.581-0.703);和0.656(0.636-0.676)对0.576(0.553-0.599)。在两个模型之间的每个对应阶段中,调整后的发生率和调整后的危险比的多变量调整后的Cox回归和Poisson回归分析结果相似,并且模型评估参数之间没有差异。预测全因死亡,心梗和卒中的净重分类改善(NRI)分别为6.7%(P <0.001),-1.89%(P = 0.029)和-0.20%(P = 0.421)。结论:在单变量分析中,使用eGFRCKDEPI比使用eGFRMDRD可以更好地进行区分。 NRI分析表明,使用eGFRCKDEPI代替eGFRMDRD可以大大改善死亡风险的重新分类。

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