Yu Xu1, Mian Li1, Guijun Qin2, Jieli Lu3, Li Yan4, Min Xu1, Tiange Wang1, Zhiyun Zhao1, Meng Dai1, Di Zhang1, Qin Wan5, Yanan Huo6, Lulu Chen7, Lixin Shi8, Ruying Hu9, Xulei Tang10, Qing Su11, Xuefeng Yu12, Yingfen Qin, Gang Chen13, Zhengnan Gao14, Guixia Wang15, Feixia Shen16, Zuojie Luo17, Li Chen18, Yuhong Chen1, Yinfei Zhang19, Chao Liu20, Youmin Wang21, Shengli Wu22, Tao Yang23, Qiang Li24, Yufang Bi1, Jiajun Zhao25, Yiming Mu26, Weiqing Wang3, Guang Ning1. 1. Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China. 2. Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China. 3. Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China wqingw61@163.com. 4. Department of Endocrine and Metabolic Diseases, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China. 5. Department of Endocrine and Metabolic Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou, China. 6. Department of Endocrine and Metabolic Diseases, Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China. 7. Department of Endocrine and Metabolic Diseases, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 8. Department of Endocrine and Metabolic Diseases, Affiliated Hospital of Guiyang Medical College, Guiyang, China. 9. Section of Chronic and Noncommunicable Disease Control and Prevention, Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China. 10. Department of Endocrine and Metabolic Diseases, The First Hospital of Lanzhou University, Lanzhou, China. 11. Department of Endocrine and Metabolic Diseases, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China. 12. Department of Endocrine and Metabolic Diseases, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China. 13. Department of Endocrine and Metabolic Diseases, Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China. 14. Department of Endocrine and Metabolic Diseases, Dalian Municipal Central Hospital, Dalian, China. 15. Department of Endocrine and Metabolic Diseases, The First Hospital of Jilin University, Changchun, China. 16. Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 17. Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Guangxi Medical University, Nanning, China. 18. Department of Endocrine and Metabolic Diseases, Qilu Hospital of Shandong University, Jinan, China. 19. Department of Endocrine and Metabolic Diseases, Central Hospital of Shanghai Jiading District, Shanghai, China. 20. Department of Endocrine and Metabolic Diseases, Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China. 21. Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Anhui Medical University, Hefei, China. 22. Department of Endocrine and Metabolic Diseases, Karamay Municipal People's Hospital, Xinjiang, China. 23. Department of Endocrine and Metabolic Diseases, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 24. Department of Endocrine and Metabolic Diseases, The Second Affiliated Hospital of Harbin Medical University, Harbin, China. 25. Department of Endocrine and Metabolic Diseases, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China. 26. Department of Endocrine and Metabolic Diseases, Chinese People's Liberation Army General Hospital, Beijing, China.
Abstract
BACKGROUND: The 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. METHODS: To 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. RESULTS: During 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%). CONCLUSIONS: Urinary 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.
BACKGROUND: The 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. METHODS: To 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. RESULTS: During 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%). CONCLUSIONS: Urinary 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.
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Authors: Andrew S Levey; Lesley A Stevens; Christopher H Schmid; Yaping Lucy Zhang; Alejandro F Castro; Harold I Feldman; John W Kusek; Paul Eggers; Frederick Van Lente; Tom Greene; Josef Coresh Journal: Ann Intern Med Date: 2009-05-05 Impact factor: 25.391
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