Article

Development and validation of decision rules models to stratify coronary artery disease, diabetes, and hypertension risk in preventive care: cohort study of returning UK Biobank participants

2021-03-03

Abstract excerpt

<h4>Background</h4> A wide range of predictive models exist that predict risk of common lifestyle conditions. However, these have not focused on identifying pre-clinical higher risk groups that would benefit from lifestyle interventions and do not include genetic risk scores. <h4>Objective</h4> To develop, validate, and compare the performance of three decision rule algorithms including biomarkers, physical measur...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: 18e38544-2565-58eb-b32f-f9b31dc6a551
DOI: 10.1101/2021.03.01.21252657

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

Development and validation of decision rules models to stratify coronary artery disease, diabetes, and hypertension risk in preventive care: cohort study of returning UK Biobank participantsDOI 10.1101/2021.03.01.21252657Read

Development and validation of a next-gen health stratification engine to determine risk for multiple cardiovascular diseasesSemantic proximity Read

Actionable absolute risk prediction of atherosclerotic cardiovascular disease: a behavior-management approach based on data from 464,547 UK Biobank participantsSemantic proximity Read

Distribution of cardiovascular disease risk based on the updated 2023 guideline-recommended Australian cardiovascular disease risk algorithm and comparison with the 2012 algorithmSemantic proximity Read

A systematic framework for assessing the clinical impact of polygenic risk scoresSemantic proximity Read

Cardiovascular risk scores for primary prevention: head-to-head validation of 16 established and contemporary modelsSemantic proximity Read

Comparative Validation of ASCVD, Framingham Risk Score, Globorisk, and PREVENT for 10-Year Cardiovascular Risk Prediction in the UK BiobankSemantic proximity Read

Using machine learning to evaluate the value of genetic liabilities in classification of hypertension within the UK BiobankSemantic proximity Read

Use of polygenic risk scores and other molecular markers to enhance cardiovascular risk prediction: prospective cohort study and modelling analysisSemantic proximity Read

Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes.Semantic proximity Read

Prediction of coronary heart disease risk integrating polygenic risk scores and wearablesSemantic proximity Read

Associations of Combined Genetic and Lifestyle Risks With Incident Cardiovascular Disease and Diabetes in the UK Biobank Study.Semantic proximity Read

Identifying and ranking novel independent features for cardiovascular disease prediction in people with type 2 diabetesSemantic proximity Read