Comparison of cystatin C- and creatinine-based estimated glomerular filtration rate to predict coronary heart disease risk in Japanese patients with obesity and diabetes.
The aim of this study is to determine which indicator of chronic kidney disease most closely correlates with 10-year Framingham coronary heart disease (CHD) risk among serum creatinine, serum cystatin C (S-CysC), urine albumin-creatinine ratio (UACR), estimated creatinine-based GFRs (eGFRcre), and estimated CysC-based GFRs (eGFRcys) in patients with obesity and diabetes. Serum creatinine, S-CysC, UACR, and cardio-ankle vascular index (CAVI) were examined in 468 outpatients with obesity and type 2 diabetes, free of severe renal dysfunction or previous history of cardiovascular disease, as a cross-sectional survey using baseline data from the multi-centered Japan Diabetes and Obesity Study. S-CysC and eGFRcys had significantly stronger correlations with the 10-year Framingham CHD risk than serum creatinine, eGFRcre, and UACR (creatinine, ρ = 0.318; S-CysC, ρ = 0.497; UACR, ρ = 0.174; eGFRcre, ρ = -0.291; eGFRcys, ρ = -0.521; P < 0.01 by Fisher's z-test). S-CysC and eGFRcys had significantly stronger correlations with CAVI than serum creatinine, eGFRcre, and UACR (creatinine, ρ = 0.198; S-CysC, ρ = 0.383; UACR, ρ = 0.183; eGFRcre, ρ = -0.302; eGFRcys, ρ = -0.444; P < 0.05 by Fisher's z-test). The receiver operating characteristic curves to distinguish the high-risk patients for CHD revealed significantly larger areas under the curve of S-CysC and eGFRcys than those of serum creatinine, UACR, and eGFRcre (serum creatinine, 0.64; S-CysC, 0.75; UACR, 0.56; eGFRcre, 0.63; eGFRcys, 0.76; P < 0.01). The data suggested that eGFRcys can be more predictive of the 10-year CHD risk than eGFRcre in Japanese patients with obesity and diabetes.
Diabetes Center, National Hospital Organization Kyoto Medical Center, Kyoto 612-8555, Japan.
Ryo
R
Ito
Hajime
H
Yamakage
Kazuhiko
K
Kotani
Hiromichi
H
Wada
Sumire
S
Otani
Kazuya
K
Yonezawa
Atsushi
A
Ogo
Taiichiro
T
Okajima
Masahiro
M
Adachi
Rika
R
Araki
Kazuro
K
Yoshida
Miho
M
Saito
Tadasu
T
Nagaoka
Tetsushi
T
Toyonaga
Tsuyoshi
T
Tanaka
Tsutomu
T
Yamada
Itsuro
I
Ota
Mariko
M
Oishi
Fumiko
F
Miyanaga
Akira
A
Shimatsu
Noriko
N
Satoh-Asahara
D000328:Adult; D015415:Biomarkers / Q000097:blood / Q000652:urine; D015992:Body Mass Index; D015331:Cohort Studies; D003327:Coronary Disease / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology*; D003404:Creatinine / Q000097:blood / Q000652:urine; D003430:Cross-Sectional Studies; D055316:Cystatin C / Q000097:blood*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000150:complications* / Q000652:urine; D003925:Diabetic Angiopathies / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology; D058065:Diabetic Cardiomyopathies / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology*; D003928:Diabetic Nephropathies / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology*; D042241:Early Diagnosis; D005919:Glomerular Filtration Rate; D006306:Health Surveys; D006801:Humans; D007564:Japan / Q000453:epidemiology; D009765:Obesity / Q000150:complications*; D011237:Predictive Value of Tests; D011446:Prospective Studies; D051436:Renal Insufficiency, Chronic / Q000150:complications / Q000175:diagnosis / Q000453:epidemiology*; D012307:Risk Factors; D012680:Sensitivity and Specificity
D015415:Biomarkers; C525030:CST3 protein, human; D055316:Cystatin C; D003404:Creatinine