Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model

Shao, Hui; Shi, Lizheng; Lin, Yilu; Fonseca, Vivian

doi:10.1016/j.jdiacomp.2022.108316

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Using modern risk engines and machine learning/artificial intelligence to predict diabetes complications: A focus on the BRAVO model

Author(s): Hui Shao , Lizheng Shi , Yilu Lin , Vivian Fonseca

Publication date Created: November 2022

Publication date (Print): November 2022

Journal: Journal of Diabetes and its Complications

Publisher: Elsevier BV

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Dapagliflozin and Cardiovascular Outcomes in Type 2 Diabetes

Stephen Wiviott, Itamar Raz, Marc Bonaca … (2018)

The cardiovascular safety profile of dapagliflozin, a selective inhibitor of sodium-glucose cotransporter 2 that promotes glucosuria in patients with type 2 diabetes, is undefined.

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Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial

Hertzel C Gerstein, Helen Colhoun, Gilles Dagenais … (2019)

Three different glucagon-like peptide-1 (GLP-1) receptor agonists reduce cardiovascular outcomes in people with type 2 diabetes at high cardiovascular risk with high glycated haemoglobin A1c (HbA1c) concentrations. We assessed the effect of the GLP-1 receptor agonist dulaglutide on major adverse cardiovascular events when added to the existing antihyperglycaemic regimens of individuals with type 2 diabetes with and without previous cardiovascular disease and a wide range of glycaemic control.