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Relationship between Arterial Stiffness and Renal Function Determined by Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) Equations in a Chinese Cohort Undergoing Health Examination
BACKGROUND: The association between arterial stiffness and cardiovascular risk in CKD and ESRD patients is well established. However, the relationship between renal function estimation and properties of large arteries is unclear due to the four different methods used to quantify glomerular filtratio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8938063/ https://www.ncbi.nlm.nih.gov/pubmed/35321070 http://dx.doi.org/10.1155/2022/8218053 |
Sumario: | BACKGROUND: The association between arterial stiffness and cardiovascular risk in CKD and ESRD patients is well established. However, the relationship between renal function estimation and properties of large arteries is unclear due to the four different methods used to quantify glomerular filtration. This study investigated the relationship between carotid-femoral pulse wave velocity (c-fPWV), as a measure of arterial stiffness, and accepted metrics of renal function. METHODS: This cross-sectional study was conducted in 431 health examination individuals in China, enrolled from January 2017 to June 2019. c-fPWV and blood pressure were measured, and blood samples were obtained for all participants. Four different methods were used to determine the estimated glomerular filtration rate (eGFR) as described by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) and Modification of Diet in Renal Disease (MDRD) equations: (i) CKD-EPI(SCr) formula based on SCr, (ii) CKD-EPI(CysC) formula based on CysC, (iii) CKD-EPI(SCr/CysC) formula based on Cr and CysC, and (iv) MDRD. RESULTS: Of all of the study participants (average age 53.1 ± 13.0 years, 68.1% male), 23.7% had diabetes mellitus and 66.6% had hypertension. The average eGFR values determined by the CKD-EPI(SCr), CKD-EPI(CysC), CKD-EPI(SCr/CysC), and MDRD equations were 91.9 ± 15.6, 86.8 ± 21.4, 89.6 ± 18.3, and 90.7 ± 16.6 ml/min/1.73m(2,) respectively. c-fPWV was significantly and negatively correlated with eGFR determined by CKD-EPI(SCr) (r = −0.336, P < 0.001), CKD-EPI(CysC) (r = −0.385, P < 0.001), CKD-EPI(SCr/CysC) (r = −0.378, P < 0.001), and MDRD (r = −0.219, P < .001) equations. After adjusting for confounding factors, c-fPWV remained significantly and negatively correlated with eGFR determined by the CKD-EPI(CysC) equation (β = −0.105, P = 0.042) and significantly and positively correlated with age (β = 0.349, P ≤ 0.01), systolic pressure (β = 0.276, P ≤ 0.01), and hypoglycemic drugs (β = 0.101, P = 0.019). CONCLUSION: In a health examination population in China, c-fPWV is negatively correlated with eGFR determined by four different equations; however, only the metric of eGFR determined by the equation for CKD-EPI(CysC) showed an independent relation with c-fPWV. |
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