Division of General Internal Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY, USA.
Center for Global Health, Weill Cornell Medicine, New York, NY, USA.
BMC Public Health. 2022 Mar 19;22(1):549. doi: 10.1186/s12889-022-12963-x.
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.
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.
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 (χ = 1416, p value < 0.001). Statin eligibility also varied widely.
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.
clinicaltrials.gov NCT03892265 .
心血管疾病（CVD）在中低收入国家（LMICs）迅速增加。通过针对高危人群进行一级预防和危险因素治疗，准确的风险评估对于降低CVD 的过早发生至关重要。现有的 CVD 风险预测模型是基于高收入国家人群的主要是白种人风险概况建立的，尚未在 LMIC 人群中进行评估。我们旨在比较六种现有的 CVD 风险预测模型，以预测 10 年 CVD 风险，并确定海地高危人群，以进行有针对性的预防和治疗。
我们使用了海地 CVD 队列研究中的横断面数据，包括 1345 名年龄≥40 岁、无已知 CVD 病史且资料完整的成年人。比较了六种 CVD 风险预测模型：合并队列方程（PCE）、更新队列调整后的 PCE、Framingham CVD 血脂、Framingham CVD 体重指数（BMI）、世界卫生组织（WHO）血脂和 WHO BMI。在临床检查期间测量了风险因素。主要结局是连续的和分类的 10 年 CVD 风险。次要结局是他汀类药物的适用性。
60%为女性，66.8%的人每天收入≤1 美元，52.9%患有高血压，14.9%患有高胆固醇血症，7.8%患有糖尿病，4.0%为当前吸烟者，2.5%为 HIV 阳性。预测的 10 年 CVD 风险范围从调整后的 PCE 中的 3.6%（IQR 1.7-8.2）到 Framingham-BMI 中的 9.6%（IQR 4.9-18.0），Spearman 秩相关系数范围从 0.86 到 0.98。使用特定模型的阈值将队列分类为高危的比例范围从使用 WHO-BMI 模型的 1.8%到 PCE 模型的 41.4%（χ²=1416，p 值<0.001）。他汀类药物的适用性也有很大差异。
在海地 CVD 队列中，使用现有的模型确定为高危和他汀类药物适用的比例存在很大差异，这导致根据所选择的预测模型，治疗建议和公共卫生影响也有很大差异。需要为中低收入国家设计和验证 CVD 风险预测工具，其中包括当地相关的风险因素。
clinicaltrials.gov NCT03892265 。
