Development and Validation of a Personalized, Sex-Specific Prediction Algorithm of Severe Atheromatosis in Middle-Aged Asymptomatic Individuals: The ILERVAS Study.

ABSTRACT:

Background

Although European guidelines recommend vascular ultrasound for the assessment of cardiovascular risk in low-to-moderate risk individuals, no algorithm properly identifies patients who could benefit from it. The aim of this study is to develop a sex-specific algorithm to identify those patients, especially women who are usually underdiagnosed.

Methods

Clinical, anthropometrical, and biochemical data were combined with a 12-territory vascular ultrasound to predict severe atheromatosis (SA: ≥ 3 territories with plaque). A Personalized Algorithm for Severe Atheromatosis Prediction (PASAP-ILERVAS) was obtained by machine learning. Models were trained in the ILERVAS cohort (n = 8,330; 51% women) and validated in the control subpopulation of the NEFRONA cohort (

SUBMITTER: Bermudez-Lopez M 

PROVIDER: S-EPMC9344070 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature