ArticleClinical epidemiology2020
Estimation of Cardiovascular Risk from Self-Reported Knowledge of Risk Factors: Insights from the Minnesota Heart Survey.
Article in Clinical epidemiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.
- Cardiovascular disease risk communication and prevention: a meta-analysis.European heart journal · 2024Pooled it
- Aspirin Use for Secondary Prevention Amid Negative Messaging in Patients With Cardiovascular Disease.JAMA network open · 2026Article
- Performance of non-laboratory Framingham risk scores using self-reported data for remote cardiovascular risk assessment.Scientific reports · 2025Article
- Resource Efficient Screening for Primary Prevention of Coronary Heart Disease: A Proof-of-Concept Test in the MESA Cohort.Journal of the American Heart Association · 2025Article
- A digital tool for self-reporting cardiovascular risk factors: The RADICAL study.International journal of cardiology. Cardiovascular risk and prevention · 2025Article
- Population cessation of aspirin use for the prevention of cardiovascular disease.American journal of preventive cardiology · 2025Article
- Rationale, design, and participant characteristics of the FAITH! Heart Health+ study: An exploration of the influence of the social determinants of health, stress, and structural racism on African American cardiovascular health.Contemporary clinical trials · 2024Article
- Self-Report Tool for Identification of Individuals With Coronary Atherosclerosis: The Swedish CardioPulmonary BioImage Study.Journal of the American Heart Association · 2024Article
- Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort.The international journal of cardiovascular imaging · 2024Article
- A cost-effective, machine learning-driven approach for screening arterial functional aging in a large-scale Chinese population.Frontiers in public health · 2024Article
- Personalized Breast Cancer Screening: A Risk Prediction Model Based on Women Attending BreastScreen Norway.Cancers · 2023Article
- Association of a Community Population and Clinic Education Intervention Program With Guideline-Based Aspirin Use for Primary Prevention of Cardiovascular Disease: A Nonrandomized Controlled Trial.JAMA network open · 2022Article
- Association of Cardiovascular Disease Risk Factors With Sociodemographic Characteristics and Health Beliefs Among a Community-Based Sample of African American Adults in Minnesota.Mayo Clinic proceedings · 2022Article
- Role of artificial intelligence in cardiovascular risk prediction and outcomes: comparison of machine-learning and conventional statistical approaches for the analysis of carotid ultrasound features and intra-plaque neovascularization.The international journal of cardiovascular imaging · 2021Article
- Low-dose aspirin for primary prevention of cardiovascular disease: Trends in use patterns among African American adults in Minnesota, 2015-2019.Preventive medicine · 2021Article
- A community-based group randomized trial to increase aspirin use for primary prevention of cardiovascular disease: Study protocol and baseline results for the "Ask About Aspirin" initiative.Contemporary clinical trials communications · 2021Article
- Aspirin Use and Misuse for the Primary Prevention of Cardiovascular Diseases.American journal of preventive medicine · 2021Article
- Physical and Psychological Factors Associated with Poor Self-Reported Health Status in Older Adults with Falls.International journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundCost-effective primary prevention of cardiovascular disease (CVD) relies on accuracy of risk assessment. Current risk scores require clinical and laboratory measures, are expensive and are often difficult to apply in the population setting.
objectiveThis study sought to estimate CVD risk from individuals' knowledge of their own CVD risk factors and compare it to the risk calculated from measured risk factors.
methodsUsing the ACC/AHA Pooled Cohort Risk Equations (PCE), we calculated 10-year CVD risk for 9856 primary prevention individuals aged 40-79 in the Minnesota Heart Survey (MHS). Using log-linear regression models, we estimated PCE risk from the individual's self-reported knowledge of four dichotomous risk factors: hypertension, hypercholesterolemia, diabetes, and smoking. Age was included in all models, and models were developed separately in women and men. Model performance was assessed internally using leave-one-out cross-validation.
resultsThe median measured PCE CVD risk in women was 2.1% (IQR: 0.8-5.6%), and in men was 6.3% (3.1-13.0%). Using the newly developed equations, the median estimated risk was 2.2% (0.9-5.8%) in women, and 6.9% (3.2-13.1%) in men. Using a threshold of 7.5% to categorize low and high risk, the novel risk calculation gave an accuracy of 95% for women and 87% for men compared to the measured PCE risk. The negative predictive value was 97% for women and 91% in men.
conclusionSelf-reported knowledge of risk may be useful in the identification of individuals at low risk for CV events, however, should always be followed up with measurement of risk factors if symptoms or history suggest CVD.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.