ArticleJournal of the American Heart Association2023
Social Determinants, Cardiovascular Disease, and Health Care Cost: A Nationwide Study in the United States Using Machine Learning.
Article in Journal of the American Heart Association, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Low income and health literacy: a systematic scoping review.Archives of public health = Archives belges de sante publique · 2025Pooled it
- Prediction of Prevalent Cardiovascular Disease Using Social, Environmental, and Behavioral Factors: A Vital Conditions Framework Approach.Chronic diseases and translational medicine · 2026Article
- Prevalence and determinants of multimorbidity in older Chinese adults: a nationwide cross-sectional study using CLASS data.BMC geriatrics · 2026Article
- Machine Learning Models to Evaluate County-Level Incidence of Diagnosed Diabetes and Sociodemographic Factors.American journal of medicine open · 2026Article
- Bridging the Gap: Multidisciplinary Decision Making to Address Systemic Barriers in Cardiovascular Care.Current cardiology reports · 2026Review
- A social determinants-based county-level cardiovascular mortality index to identify high-risk counties in the USA.BMC medicine · 2025Article
- CVD Mortality Disparities with Risk Factor Associations Across U.S. Counties.Healthcare (Basel, Switzerland) · 2025Article
- Lipid Control and Social Determinants: Their Association With LDL and Non-HDL Cholesterol Goals in Older Adults-A Population-Based Study.Clinical cardiology · 2025Article
- LncRNA-mRNA co-expression network in the mechanism of butylphthalide treatment for ischemic stroke.BMC neurology · 2025Article
- A Global Perspective on Socioeconomic Determinants of Cardiovascular Health.The Canadian journal of cardiology · 2025Review
- The effect of sociodemographic, socioeconomic, and health factors on healthcare utilization in cardiovascular patients in Serbia: a part of National Health Survey.Frontiers in public health · 2025Article
- A proposed model using glycation metrics and circulating biomarkers for the prevention of cardiovascular disease.Frontiers in medicine · 2025Article
- Socioeconomic status as a potential mediator of arterial aging in marginalized ethnic and racial groups: current understandings and future directions.Journal of applied physiology (Bethesda, Md. : 1985) · 2024Review
- Epigenetics of Early Cardiometabolic Disease: Mechanisms and Precision Medicine.Circulation research · 2023Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Background Existing studies on cardiovascular diseases (CVDs) often focus on individual-level behavioral risk factors, but research examining social determinants is limited. This study applies a novel machine learning approach to identify the key predictors of county-level care costs and prevalence of CVDs (including atrial fibrillation, acute myocardial infarction, congestive heart failure, and ischemic heart disease). Methods and Results We applied the extreme gradient boosting machine learning approach to a total of 3137 counties. Data are from the
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Registered trials
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 Socratic graph.