Phenomapping-Derived Tool to Individualize the Effect of Canagliflozin on Cardiovascular Risk in Type 2 Diabetes.

ABSTRACT:

Objective

Sodium-glucose cotransporter 2 (SGLT2) inhibitors have well-documented cardioprotective effects but are underused, partly because of high cost. We aimed to develop a machine learning-based decision support tool to individualize the atherosclerotic cardiovascular disease (ASCVD) benefit of canagliflozin in type 2 diabetes.

Research design and methods

We constructed a topological representation of the Canagliflozin Cardiovascular Assessment Study (CANVAS) using 75 baseline variables collected from 4,327 patients with type 2 diabetes randomly assigned 1:1:1 to one of two canagliflozin doses (n = 2,886) or placebo (n = 1,441). Within each patient's 5% neighborhood, we calculated age- and sex-adjusted risk estimates for major adverse cardiovascular events (MACEs). An ex

SUBMITTER: Oikonomou EK 

PROVIDER: S-EPMC9016734 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature