Related Experiment Video
Updated: Sep 29, 2025
Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis
Published on: September 26, 2018
Comparing six cardiovascular risk prediction models in Haiti: implications for identifying high-risk individuals for
Lily D Yan1,2, Jean Lookens Pierre3, Vanessa Rouzier4,3
1Division of General Internal Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA. liy9032@med.cornell.edu.
Insights
Existing cardiovascular disease (CVD) risk models vary widely when applied to Haitian populations, impacting prevention strategies. New, locally relevant risk prediction tools are needed for low-middle income countries.
Area of Science:
- Cardiology
- Public Health
- Epidemiology
Background:
- Cardiovascular diseases (CVD) are a growing concern in low-middle income countries (LMICs).
- Accurate CVD risk assessment is crucial for effective primary prevention and treatment targeting.
- Existing risk prediction models are primarily based on high-income country populations and may not be suitable for LMICs.
Purpose of the Study:
- To compare the performance of six established CVD risk prediction models in a Haitian population.
- To identify high-risk individuals for targeted CVD prevention and treatment in Haiti.
- To assess the implications of model selection on public health strategies.
Main Methods:
- Cross-sectional analysis of 1345 adults (≥40 years) from the Haiti CVD Cohort Study.
- Comparison of six CVD risk prediction models: Pooled Cohort Equations (PCE), adjusted PCE, Framingham (Lipids and BMI), and WHO (Lipids and BMI).
- Evaluation of predicted 10-year CVD risk and statin eligibility based on measured risk factors.
Main Results:
- Significant variation in predicted 10-year CVD risk (3.6% to 9.6%) and high-risk categorization (1.8% to 41.4%) across the models.
- High correlation (0.86-0.98) between models, but substantial differences in clinical recommendations.
- Wide disparities in statin eligibility depending on the model used.
Conclusions:
- Existing CVD risk prediction models show substantial variability in identifying high-risk individuals in Haiti.
- The choice of CVD risk model significantly impacts treatment recommendations and public health outcomes.
- There is a critical need for developing and validating CVD risk prediction tools tailored to LMIC populations, incorporating local risk factors.
Background:
Cardiovascular 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.
Methods:
We 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.
Results:
Sixty 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 (χ2 = 1416, p value < 0.001). Statin eligibility also varied widely.
Conclusions:
In 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 Registration:
clinicaltrials.gov NCT03892265 .
Related Concept Videos
01:26Coronary Artery Disease IV: Preventive Measures
01:20Blood Studies for Cardiovascular System I: Cardiac Biomarkers
The essential diagnostic tools for detecting myocardial necrosis and monitoring individuals suspected of having acute coronary syndrome (ACS) include:
Troponins
Troponins, particularly cardiac troponins I and T, are the most precise and sensitive markers of myocardial injury. They are detectable within 4-6 hours of myocardial injury and remain...
01:19Blood Studies for Cardiovascular System II: CRP, Hcy, and Cardiac Natriuretic Peptide Markers
These markers indicate stress or strain on the heart muscle:
Natriuretic Peptides (BNP)
Cardiac myocytes produce these hormones in response to ventricular stretching...
01:10Pre-Procedural Guidelines for Assessing Blood Pressure
01:12Hazard Ratio
For example, in a clinical trial...
01:25Blood Studies for Cardiovascular System III: Serum Lipid Profile
Serum lipids are fats and fatty substances in the blood and are crucial for various bodily functions, including energy storage, cellular structure, and hormone production. Serum lipids consist of cholesterol, triglycerides, and phospholipids.
Cholesterol is a soft, fat-like substance found in all body cells. It is crucial for producing hormones, vitamin D, and substances that aid...