Cardiovascular Risk Based on ASCVD and KDIGO Categories in Chinese Adults: A Nationwide, Population-Based, Prospective Cohort Study
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Published:2021-03-04
Issue:4
Volume:32
Page:927-937
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ISSN:1046-6673
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Container-title:Journal of the American Society of Nephrology
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language:en
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Short-container-title:JASN
Author:
Xu Yu, Li Mian, Qin Guijun, Lu Jieli, Yan Li, Xu Min, Wang Tiange, Zhao Zhiyun, Dai Meng, Zhang Di, Wan Qin, Huo Yanan, Chen Lulu, Shi Lixin, Hu Ruying, Tang Xulei, Su Qing, Yu Xuefeng, Qin Yingfen, Chen Gang, Gao Zhengnan, Wang Guixia, Shen Feixia, Luo Zuojie, Chen Li, Chen Yuhong, Zhang Yinfei, Liu Chao, Wang Youmin, Wu Shengli, Yang Tao, Li Qiang, Bi YufangORCID, Zhao Jiajun, Mu Yiming, Wang Weiqing, Ning Guang,
Abstract
BackgroundThe Kidney Disease Improving Global Outcomes (KDIGO) clinical practice guideline used eGFR and urinary albumin-creatinine ratio (ACR) to categorize risks for CKD prognosis. The utility of KDIGO’s stratification of major CVD risks and predictive ability beyond traditional CVD risk prediction scores are unknown.MethodsTo evaluate CVD risks on the basis of ACR and eGFR (individually, together, and in combination using the KDIGO risk categories) and with the atherosclerotic cardiovascular disease (ASCVD) score, we studied 115,366 participants in the China Cardiometabolic Disease and Cancer Cohort study. Participants (aged ≥40 years and without a history of cardiovascular disease) were examined prospectively for major CVD events, including nonfatal myocardial infarction, nonfatal stroke, and cardiovascular death.ResultsDuring 415,111 person-years of follow-up, 2866 major CVD events occurred. Incidence rates and multivariable-adjusted hazard ratios of CVD events increased significantly across the KDIGO risk categories in ASCVD risk strata (all P values for log-rank test and most P values for trend in Cox regression analysis <0.01). Increases in c statistic for CVD risk prediction were 0.01 (0.01 to 0.02) in the overall study population and 0.03 (0.01 to 0.04) in participants with diabetes, after adding eGFR and log(ACR) to a model including the ASCVD risk score. In addition, adding eGFR and log(ACR) to a model with the ASCVD score resulted in significantly improved reclassification of CVD risks (net reclassification improvements, 4.78%; 95% confidence interval, 3.03% to 6.41%).ConclusionsUrinary ACR and eGFR (individually, together, and in combination using KDIGO risk categories) may be important nontraditional risk factors in stratifying and predicting major CVD events in the Chinese population.
Funder
National Key R&D Program of China National Natural Science Foundation of China Shanghai Municipal Government Shanghai Shenkang Hospital Development Center Shanghai Jiaotong University School of Medicine Ruijin Hospital
Publisher
American Society of Nephrology (ASN)
Subject
Nephrology,General Medicine
Cited by
10 articles.
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