a-Klotho in Relation to Calcification in the Coronary Arteries and Aortic Valve in Patients With Chronic Kidney Disease

Overview

To define the correlation of the levels of a-Klotho with the severity of vascular calcification in the coronary arteries and aortic valve.

Vascular calcification is a well-defined risk factor for cardiovascular disease and a-Klotho has been suggested to be an implicating factor in the process of vascular calcification, particularly in patients with chronic kidney disease (CKD). With this study the investigators will examine the possible correlation of the levels of secreted a-Klotho with the severity of vascular calcification in the coronary arteries and aortic valve in patients with CKD at different stages of CKD. More precisely, a-Klotho was measured in 30 patients with end-stage renal disease under intermittent regular hemodialysis and 30 outpatients with stable CKD stage III (estimated glomerular filtration rate between 30 and 59 mL/min/1.73\^2). Participants in both groups were eligible only if stable for at least the last 3 months pre-enrollment. Calcification will be calculated using the well-established Agatston score after submitting all patients to multi-slice computed tomography. Continuous variables will be described as median (25th-75th percentile) and categorical variables as N (%). Variables will be compared between groups using the non-parametric Mann-Whitney U test for continuous and Fisher's exact test for categorical variables. Bivariate correlations of a-Klotho levels with clinical variables and calcification scores using the Spearman correlation coefficient will be examined. Identification of a-Klotho determinants, log-transformation of a-Klotho levels was done because of log-normal distribution and stepwise linear regression was used, with probability to remove the variable\>0.1. Identification of determinants of coronary and aortic calcification was done via log-transformation of the corresponding calcium scores, (a value of 0 was assumed; log-transformed-1 for absent calcium) and, stepwise linear regression was used as above. Because of the small sample size, all regression estimates, and confidence intervals were calculated with re-sampling so that robust variable selection and stable estimates can be ensured.

Conditions

Interventions

Eligibility

Outcomes