Electronic Medical Record Risk Modeling of Cardiovascular Outcomes Among Patients with Type 2 Diabetes.

ABSTRACT:

Introduction

Increased utilization of electronic health records (EHR) has enriched databases for creating risk models. We used machine learning techniques to develop an EHR-based risk model locally fitted to patients with type 2 diabetes mellitus (T2DM) for predicting cardiovascular disease.

Methods

This retrospective observational study was conducted within Ochsner Health, Louisiana, USA, between 2013-2017. Data analysis included 6245 patients who had two outpatient diagnoses of T2DM recorded on separate days or a diagnosis recorded during an inpatient encounter. Baseline clinical data were limited to 180 days before the index diagnosis. Cardiovascular outcomes were coronary heart disease (CHD), heart failure and stroke. Machine learning approaches were used to select predi

SUBMITTER: Hong D 

PROVIDER: S-EPMC8266923 | biostudies-literature | 2021 Jul

REPOSITORIES: biostudies-literature