Development and Validation of a Prediction Model for Atrial Fibrillation Using Electronic Health Records.

ABSTRACT:

Objectives

This study sought to determine whether the risk of atrial fibrillation AF can be estimated accurately by using routinely ascertained features in the electronic health record (EHR) and whether AF risk is associated with stroke.

Background

Early diagnosis of AF and treatment with anticoagulation may prevent strokes.

Methods

Using a multi-institutional EHR, this study identified 412,085 individuals 45 to 95 years of age without prevalent AF between 2000 and 2014. A prediction model was derived and validated for 5-year AF risk by using split-sample validation and model performance was compared with other methods of AF risk assessment.

Results

Within 5 years, 14,334 individuals developed AF. In the derivation sample (7,216 AF events of 206,042 total), the

SUBMITTER: Hulme OL 

PROVIDER: S-EPMC6884135 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature