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.

doi:10.23736/S0392-9590.20.04538-1

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Article

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.

International angiology : a journal of the International Union of Angiology - 1 Apr 2021

Jamthikar Ankush D, Puvvula Anudeep, Gupta Deep, Johri Amer M, Nambi Vijay, Khanna Narendra N, Saba Luca, Mavrogeni Sophie, Laird John R, Pareek Gyan, Miner Martin, Sfikakis Petros P, Protogerou Athanasios, Kitas George D, Nicolaides Andrew, Sharma Aditya M, Viswanathan Vijay, Rathore Vijay S, Kolluri Raghu, Bhatt Deepak L, Suri Jasjit S

Abstract excerpt

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...

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PMID: 33236868
DOI: 10.23736/S0392-9590.20.04538-1

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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