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Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease

Nature Reviews Nephrology volume 18, pages 696–707 (2022)Cite this article

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Abstract

Chronic kidney disease (CKD) is defined by a low glomerular filtration rate or high albuminuria, and affects 15–20% of adults globally. CKD increases the risk of various adverse outcomes, but cardiovascular disease (CVD) is of particular relevance because it is the leading cause of death in this clinical population. CKD is associated with several CVD outcomes, including coronary heart disease, stroke, peripheral artery disease, arrhythmias, heart failure and venous thrombosis. Notably, CKD is particularly strongly associated with severe CVD outcomes such as CVD mortality, heart failure and lower extremity amputations. This broad impact of CKD on the cardiovascular system probably reflects the involvement of several pathophysiological mechanisms that link CKD to CVD development — shared risk factors (for example, diabetes and hypertension), changes in bone mineral metabolism, anaemia, volume overload, inflammation and the presence of uraemic toxins. Understanding the status of CKD is crucial for appropriate CVD risk prediction in CKD populations. However, major clinical guidelines are not consistent in their incorporation of CKD measures for CVD risk prediction. Mitigating CVD risk in patients with CKD effectively requires multidisciplinary care that involves nephrologists, cardiologists and other health professionals, as well as further work to address current research and implementation gaps.

Key points

  • Chronic kidney disease (CKD) affects 15–20% of adults globally and increases the risk of various cardiovascular disease (CVD) outcomes (for example, coronary disease, stroke, peripheral artery disease, arrhythmias and heart failure).

  • The broad impact of CKD on the cardiovascular system reflects several pathophysiological mechanisms that link CKD to CVD — shared risk factors (for example, hypertension and diabetes), altered bone mineral metabolism, anaemia, volume overload and the presence of uraemic toxins.

  • Major clinical guidelines are inconsistent with regard to the incorporation of CKD measures for CVD risk prediction. A new approach — ‘CKD Add-on’ — enables the integration of CKD measures into major CVD prediction models.

  • A few new therapies, such as sodium–glucose co-transporter 2 inhibitors, can prevent CVD in CKD populations, but mitigating the risk of CVD in patients with CKD effectively requires multidisciplinary care involving nephrologists, cardiologists and other health care professionals.

  • Many studies have clarified different aspects of the CKD–CVD relationship, but several implementation gaps still need to be addressed, including issues related to widespread albuminuria screening, inadequate implementation of guideline-directed medical therapies, and affordable and equitable access to evidence-based medications.

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Fig. 1: KDIGO CKD stages and risk of CVD mortality.
Fig. 2: Major pathophysiological mechanisms linking CKD to CVD subtypes.

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Authors and Affiliations

  1. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA

    Kunihiro Matsushita & Shoshana H. Ballew

  2. Welch Center for Prevention, Epidemiology, and Clinical Research, Baltimore, MD, USA

    Kunihiro Matsushita & Shoshana H. Ballew

  3. Division of Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, USA

    Kunihiro Matsushita

  4. Department of Medicine, Queen Mary Hospital, The University of Hong Kong, Hong Kong Special Administrative Region, China

    Angela Yee-Moon Wang

  5. Departments of Physiology and Internal Medicine, Makerere University College of Health Sciences, Makerere University, Kampala, Uganda

    Robert Kalyesubula

  6. African Community Center for Social Sustainability (ACCESS), Nakaseke, Uganda

    Robert Kalyesubula

  7. Institute of Public Health, Charité Universitätsmedizin Berlin, Berlin, Germany

    Elke Schaeffner

  8. Department of Medicine, Indiana University School of Medicine and Veterans Affairs Medical Center, Indianapolis, IN, USA

    Rajiv Agarwal

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All authors researched data for the article, made substantial contributions to discussions of the content and wrote, drafted, reviewed or edited the manuscript before submission.

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Competing interests

K.M. received support from NIDDK (R01DK100446) during the submitted work, personal fees and research funding from Kyowa Kirin, and personal fees from Akebia and Fukuda Denshi outside of the submitted work. R.A. reports personal fees and nonfinancial support from Bayer Healthcare Pharmaceuticals Inc., Akebia Therapeutics, Boehringer Ingelheim, Eli Lilly and Vifor Pharma; he has received personal fees from Lexicon and Reata; he is a member of data safety monitoring committees for Vertex and Chinook; a member of steering committees of randomized trials for Akebia Therapeutics, Bayer, and Relypsa; and a member of adjudication committees for Bayer; he has served as associate editor of the American Journal of Nephrology and Nephrology Dialysis Transplantation and has been an author for UpToDate; and he has received research grants from the US NIH and US Veterans Affairs. The other authors declare no competing interests.

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Glossary

Eccentric LVH

A type of LVH that is characterized by a dilatated left ventricular chamber in addition to increased left ventricular mass.

Concentric LVH

A type of LVH that is characterized by a reduced left ventricular chamber owing to increased thickness of the left ventricular wall.

Concordance statistic

An indicator of risk discrimination; corresponds to the probability that the predicted risk is higher in a case than in a non-case.

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Matsushita, K., Ballew, S.H., Wang, A.YM. et al. Epidemiology and risk of cardiovascular disease in populations with chronic kidney disease. Nat Rev Nephrol 18, 696–707 (2022). https://doi.org/10.1038/s41581-022-00616-6

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