Cardiovascular disease and stroke risk assessment in patients with chronic kidney disease using integration of estimated glomerular filtration rate, ultrasonic image phenotypes, and artificial intelligence: a narrative review.

Cardiovascular disease and stroke risk assessment in patients with chronic kidney disease using integration of estimated glomerular filtration rate, ultrasonic image phenotypes, and artificial intelligence: a narrative review. Int Angiol. 2020 Nov 25;: Authors: Jamthikar AD, Puvvula A, Gupta D, Johri AM, Nambi V, Khanna NN, Saba L, Mavrogeni S, Laird JR, Pareek G, Miner M, Sfikakis P, Protogerou A, Kitas GD, Nicolaides A, Sharma AM, Viswanathan V, Rathore VS, Kolluri R, Bhatt DL, Suri JS Abstract Chronic kidney disease (CKD) and cardiovascular disease (CVD) together result in an enormous burden on global healthcare. The estimated glomerular filtration rate (eGFR) is a well-established biomarker of CKD and is associated with adverse cardiac events. This review highlights the link between eGFR reduction and that of atherosclerosis progression, which increases the risk of adverse cardiovascular events. In general, CVD risk assessments are performed using conventional risk prediction models. However, since these conventional models were developed for a specific cohort with a unique risk profile and further these models do not consider atherosclerotic plaque-based phenotypes, therefore, such models can either underestimate or overestimate the risk of CVD events. This review examines the approaches used for CVD risk assessments in CKD patients using the concept of integrated risk factors. An integrated risk factor approach is one that comb...
Source: International Angiology - Category: Cardiology Tags: Int Angiol Source Type: research