ArticleBMC public health2022
Comparing six cardiovascular risk prediction models in Haiti: implications for identifying high-risk individuals for primary prevention.
Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03892265 (A Longitudinal Cohort Study to Evaluate Cardiovascular Risk Factors and Disease in Haiti), which is not on this map. Cited by 4 papers.
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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.
A Longitudinal Cohort Study to Evaluate Cardiovascular Risk Factors and Disease in Haiti
Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- The Role of Artificial Intelligence in Cardiovascular Disease Risk Prediction: An Updated Review on Current Understanding and Future Research.Current cardiology reviews · 2025Review
- Exploring the Current Tools in Cardiovascular Risk Assessment in the Middle East and the Need for Region-Specific Models - A Scoping Review.Therapeutics and clinical risk management · 2025Review
- Analysis Using Various Models on the Effect of Metabolic Surgery on Cardiovascular Disease Risk in the Chinese Population with Obesity.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Validation of the general Framingham Risk Score (FRS), SCORE2, revised PCE and WHO CVD risk scores in an Asian population.The Lancet regional health. Western Pacific · 2023Article
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
Abstract
backgroundCardiovascular diseases (CVD) are rapidly increasing in low-middle income countries (LMICs). Accurate risk assessment is essential to reduce premature CVD by targeting primary prevention and risk factor treatment among high-risk groups. Available CVD risk prediction models are built on predominantly Caucasian risk profiles from high-income country populations, and have not been evaluated in LMIC populations. We aimed to compare six existing models for predicted 10-year risk of CVD and identify high-risk groups for targeted prevention and treatment in Haiti.
methodsWe used cross-sectional data within the Haiti CVD Cohort Study, including 1345 adults ≥ 40 years without known history of CVD and with complete data. Six CVD risk prediction models were compared: pooled cohort equations (PCE), adjusted PCE with updated cohorts, Framingham CVD Lipids, Framingham CVD Body Mass Index (BMI), WHO Lipids, and WHO BMI. Risk factors were measured during clinical exams. Primary outcome was continuous and categorical predicted 10-year CVD risk. Secondary outcome was statin eligibility.
resultsSixty percent were female, 66.8% lived on a daily income of ≤ 1 USD, 52.9% had hypertension, 14.9% had hypercholesterolemia, 7.8% had diabetes mellitus, 4.0% were current smokers, and 2.5% had HIV. Predicted 10-year CVD risk ranged from 3.6% in adjusted PCE (IQR 1.7-8.2) to 9.6% in Framingham-BMI (IQR 4.9-18.0), and Spearman rank correlation coefficients ranged from 0.86 to 0.98. The percent of the cohort categorized as high risk using model specific thresholds ranged from 1.8% using the WHO-BMI model to 41.4% in the PCE model (χ
conclusionsIn the Haiti CVD Cohort, there was substantial variation in the proportion identified as high-risk and statin eligible using existing models, leading to very different treatment recommendations and public health implications depending on which prediction model is chosen. There is a need to design and validate CVD risk prediction tools for low-middle income countries that include locally relevant risk factors.
trial registrationclinicaltrials.gov NCT03892265 .
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