Chronic kidney disease measures for cardiovascular risk prediction
Graphical abstract
Introduction
Chronic kidney disease (CKD) affects 15–20% of adults in many countries around the world and causes various complications [1]. As a consequence, the 2019 Global Burden of Disease study ranked CKD as the 12th leading risk factor impacting disability-adjusted life-years [2]. Cardiovascular disease (CVD) is recognized as one of the most important complication of CKD, as well as a leading cause of death in patients with CKD. Of note, CKD has been associated with many CVD subtypes, especially severe ones like heart failure, independent of potential confounders such as diabetes and hypertension.
Despite a huge body of evidence demonstrating the excess risk of CVD in patients with CKD, there is no consensus in major clinical guidelines as to how to incorporate CKD for the risk prediction of CVD. This can result in inconsistent practice among healthcare providers and suboptimal management of CVD risk in persons with CKD. Importantly, unlike some novel biomarkers, measures of CKD (e.g., serum creatinine) are often evaluated in clinical practice. Thus, this is a critical missed opportunity to appropriately refine predicted risk with readily available information and personalize prevention therapies according to CKD status.
In this review, we provide an overview of the CVD subtypes that have been linked to CKD, major pathophysiological mechanisms, and the current situation regarding CKD as a predictor of CVD in major clinical guidelines. Then, we will introduce the novel concept of a “CKD Add-on”, which allows the incorporation of CKD into existing risk prediction models, and conclude with the implications of taking into account CKD in the management of CVD risk.
Section snippets
Definition and staging of CKD
Current guidelines define CKD as an abnormality detected through pathology, imaging, or assessment of blood and urine tests. Glomerular filtration rate (GFR) and albuminuria are often the two key components to define and stage CKD. Indeed, the Kidney Disease Improving Global Outcomes (KDIGO) guideline classifies CKD by level of GFR (stage G1-G5) and level of albuminuria (stage A1-A3) (Fig. 1) [3]. This classification is based on graded risk increases in each of these categories for major
CKD as a risk factor of CVD: epidemiological perspectives
As expressed by the term “cardiorenal syndrome,” a close link between kidney and heart has been long recognized. However, the impact of CKD on the cardiovascular system is far beyond heart disease. Indeed, a number of CVD outcomes have been linked to CKD: coronary heart disease, heart failure, atrial fibrillation, sudden cardiac death, stroke, abdominal aortic aneurysm, peripheral artery disease, and venous thrombosis (Fig. 2) [1,18,19,[22], [23], [24], [25], [26], [27]]. This multifaceted
Mechanisms behind the increased risk of CVD in CKD
Although pathophysiological pathways linking CKD to CVD risk have not been fully understood, several mechanisms such as shared risk factors between CKD and CVD, volume overload, bone-mineral metabolism disorder, uremic toxins, anemia, inflammation, and oxidative stress play a role. The key mechanisms may vary according to CKD stages (e.g., shared risk factors playing a major role at milder stages and uremic toxins at more severe stages). There are several previous review articles providing an
Inconsistency in major clinical guidelines for primary prevention
Guidelines are inconsistent in terms of incorporation of CKD measures into risk prediction. The 2018 American Heart Association/American Colloge of Cardiology (AHA/ACC) Cholesterol Guideline recommends the use of the Pooled Cohort Equation (PCE) for prediction of the 10-year risk of developing atherosclerotic CVD (ASCVD) [90]. This equation uses traditional cardiovascular risk factors but does not include CKD measures. Nonetheless, this guideline acknowledges GFR 15–59 ml/min/1.73 m2 as a
Clinical implications of including CKD for CVD risk prediction
As mentioned above, risk prediction is central for personalized and targeted preventive therapy. Indeed, CVD risk prediction is recommended for guiding lipid and blood pressure control [90,110]. The need for optimal risk prediction for both primary and secondary prevention of CVD is higher than ever, given the availability of new effective but expensive medications [[111], [112], [113]]. Of those, SGLT2 (sodium-glucose contraporter type 2) inhibitors are particularly relevant to patients with
Summary
CKD affects a substantial proportion of the adult population world-wide and there is growing evidence, from observational studies as well as examinations of pathological mechanisms, of the increased CVD risk in persons with CKD. While major guidelines recognize this excess risk, the incorporation of CKD measures into recommended risk prediction tools is not yet established. Markers of CKD are collected in routine clinical care, although it is notable that there is less awareness of the
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: K.M. received funding and personal fee from Kyowa Kirin and personal fee from Akebia and Fukuda Denshi outside of the submitted work.
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These authors contributed equally as first authors.