Abstract
This study assessed the association of CD5L and soluble CD36 (sCD36) with the risk of a cardiovascular event (CVE), including CV death and all-cause mortality in CKD. We evaluated the association of CD5L and sCD36 with a predefined composite CV endpoint (unstable angina, myocardial infarction, transient ischemic attack, cerebrovascular accident, congestive heart failure, arrhythmia, peripheral arterial disease [PAD] or amputation by PAD, aortic aneurysm, or death from CV causes) and all-cause mortality using Cox proportional hazards regression, adjusted for CV risk factors. The analysis included 1,516 participants free from pre-existing CV disease followed up for 4 years. The median age was 62 years, 38.8% were female, and 26.8% had diabetes. There were 98 (6.5%) CVEs and 72 (4.8%) deaths, of which 26 (36.1%) were of CV origin. Higher baseline CD5L concentration was associated with increased risk of CVE (HR, 95% CI, 1.17, 1.0–1.36), and all-cause mortality (1.22, 1.01–1.48) after adjusting for age, sex, diabetes, systolic blood pressure, dyslipidemia, waist circumference, smoking, and CKD stage. sCD36 showed no association with adverse CV outcomes or mortality. Our study showed for the first time that higher concentrations of CD5L are associated with future CVE and all-cause mortality in individuals with CKD.
Highlights
Chronic kidney disease (CKD) is a well-known independent risk factor for premature cardiovascular disease (CVD) and death [1]
The etiology of CKD was diverse: in 21.2% of cases it was related to a vascular disease; in 15.7% to glomerular nephropathy; and in 14.6% to diabetic kidney disease
We evaluated whether the adjusted model including CD5 molecule-like (CD5L) and the traditional CV risk factors improved the prediction of CV events and mortality compared to the model without CD5L
Summary
Chronic kidney disease (CKD) is a well-known independent risk factor for premature cardiovascular disease (CVD) and death [1]. In individuals with CKD, cardiovascular (CV) events and mortality increase progressively with declining renal function and/or increasing albuminuria [1], with a 50% risk of CV mortality even before reaching end-stage renal disease [2]. CV events and mortality are only partially explained by the traditional risk factors of diabetes, dyslipidemia, hypertension, obesity, smoking, and gender. More recently described biomarkers have not improved the prediction of CV events in individuals with renal impairment [3,4,5,6,7]. The identification of novel and more efficient biomarkers for early CV risk prediction is essential to be able to implement optimal risk-reduction strategies to improve clinical outcomes
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