Cardiovascular disease is a major complication of chronic kidney disease, even in its early stages. Accurate risk prediction models are important in identifying high-risk individuals and improving prognosis in CKD patients.
As one of the main complications of chronic kidney disease (CKD), the incidence of cardiovascular disease (CVD) in CKD patients is high. CVD risk is markedly increased even at early stages of CKD, and CVD deaths account for half of all known causes of mortality in end-stage renal disease (ESRD) patients. The alarming rate of CVD in CKD patients demands accurate risk prediction to identify individuals at greater risk and therefore needing intensive surveillance and treatment in order to improve their prognosis. Since the CVD risk prediction models used in general population did not perform well in CKD patients, novel CVD risk biomarkers and improved risk predictive models adapted to CKD are receiving increasing attention in recent years. In this article, we review the applicability and performance of some of the available cardiovascular risk prediction tools in CKD.
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