Risk factors for metabolic syndrome independently predict arterial stiffness and endothelial dysfunction in patients with chronic kidney disease and minimal comorbidity

OBJECTIVE: Metabolic syndrome (MS) is common in patients with chronic kidney disease (CKD), but its contribution to arterial stiffness and endothelial dysfunction in CKD is not well defined. We hypothesized that risk factors for MS would independently predict arterial stiffness and endothelial dysfunction in CKD patients. RESEARCH DESIGN AND METHODS: Risk factors for MS, carotid-femoral pulse wave velocity (CF-PWV) and flow-mediated dilation (FMD) as measures of arterial stiffness and endothelial dysfunction, respectively, were assessed in 113 minimally comorbid CKD patients and in 23 matched control subjects. RESULTS: CF-PWV correlated with systolic blood pressure (SBP), waist circumference, and plasma glucose (r(2) = 0.25, 0.09, and 0.09; P < 0.01 for all). FMD correlated with SBP (r(2) = 0.09; P < 0.01) and waist circumference (r(2) = 0.03; P < 0.05). CF-PWV increased progressively (r(2) = 0.07; P < 0.01) with increasing number of risk factors for MS. In multiple linear regression, SBP and waist circumference were independent determinants of CF-PWV, whereas only SBP predicted FMD. CONCLUSIONS: The number of MS risk factors is an important determinant of arterial stiffness in CKD patients irrespective of the degree of renal impairment. Although BP remains the major determinant of arterial stiffness and endothelial dysfunction, waist circumference independently predicts arterial stiffness. MS risk factors, particularly abdominal girth, are potential targets for future interventional studies in patients with CKD

Arterial stiffness &amp; Sri Lankan chronic kidney disease of unknown origin

Chronic kidney disease (CKD) is common and independently associated with cardiovascular disease (CVD). Arterial stiffness contributes to CVD risk in CKD. In many developing countries a considerable proportion of CKD remains unexplained, termed CKDu. We assessed arterial stiffness in subjects with Sri Lankan CKDu, in matched controls without CKD and in those with defined CKD. Aortic blood pressure (BP), pulse wave velocity (PWV) and augmentation index (AIx) were assessed in 130 subjects (50 with CKDu, 45 with CKD and 35 without CKD) using the validated TensioMed™ Arteriograph monitor. Brachial and aortic BP was lower in controls than in CKDu and CKD subjects but no different between CKDu and CKD. Controls had a lower PWV compared to subjects with CKDu and CKD. Despite equivalent BP and renal dysfunction, CKDu subjects had a lower PWV than those with CKD (8.7 ± 1.5 vs. 9.9 ± 2.2 m/s, p < 0.01). Excluding diabetes accentuated the differences in PWV seen between groups (controls vs. CKDu vs. CKD: 6.7 ± 0.9 vs. 8.7 ± 1.5 vs. 10.4 ± 1.5 m/s, p < 0.001 for all). Sri Lankan CKDu is associated with less arterial stiffening than defined causes of CKD. Whether this translates to lower cardiovascular morbidity and mortality long term is unclear and should be the focus of future studies

Determinants of arterial stiffness in chronic kidney disease stage 3

Background: Early chronic kidney disease (CKD) is associated with increased cardiovascular (CV) risk but underlying mechanisms remain uncertain. Arterial stiffness (AS) is associated with increased CV risk in advanced CKD, but it is unclear whether AS is relevant to CV disease (CVD) in early CKD. Study Design: Cross-sectional. Setting and participants: 1717 patients with previous estimated glomerular filtration rate (eGFR) 59–30 mL/min/1.73 m2; mean age 7369y, were recruited from 32 general practices in primary care. Outcomes: Increased arterial stiffness. Measurements: Medical history was obtained and participants underwent clinical assessment, urine and serum biochemistry testing. Carotid to femoral pulse wave velocity (PWV) was determined as a measure of AS, using a VicorderTM device. Results: Univariate analysis revealed significant correlations between PWV and risk factors for CVD including age (r = 0.456; p,0.001), mean arterial pressure (MAP) (r = 0.228; p,0.001), body mass index (r = 20.122; p,0.001), log urinary albumin to creatinine ratio (r = 0.124; p,0.001), Waist to Hip ratio (r = 0.124, p,0.001), eGFR (r = 20.074; p = 0.002), log high sensitivity c-reactive protein (r = 0.066; p = 0.006), HDL (r = 20.062; p = 0.01) and total cholesterol (r = 20.057; p = 0.02). PWV was higher in males (9.6 m/sec vs.10.3 m/sec; p,0.001), diabetics (9.8 m/sec vs. 10.3 m/sec; p,0.001), and those with previous CV events (CVE) (9.8 m/s vs. 10.3 m/sec; p,0.001). Multivariable analysis identified age, MAP and diabetes as strongest independent determinants of higher PWV (adjusted R2 = 0.29). An interactive term indicated that PWV increased to a greater extent with age in males versus females. Albuminuria was a weaker determinant of PWV and eGFR did not enter the model. Limitations: Data derived from one study visit, with absence of normal controls. Conclusion: In this cohort, age and traditional CV risk factors were the strongest determinants of AS. Albuminuria was a relatively weak determinant of AS and eGFR was not an independent determinant. Long-term follow-up will investigate AS as an independent risk factor for CVE in this cohort