Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), Cardiology Section, VA Boston Healthcare System, 1400 VFW Parkway, West Roxbury, Boston, MA, 02132, USA.
BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
ESC Heart Fail. 2021 Dec;8(6):4893-4903. doi: 10.1002/ehf2.13429. Epub 2021 Sep 16.
This study aims to develop the first race-specific and sex-specific risk prediction models for heart failure with preserved (HFpEF) and reduced ejection fraction (HFrEF).
We created a cohort of 1.8 million individuals who had an outpatient clinic visit between 2002 and 2007 within the Veterans Affairs (VA) Healthcare System and obtained information on HFpEF, HFrEF, and several risk factors from electronic health records (EHR). Variables were selected for the risk prediction models in a 'derivation cohort' that consisted of individuals with baseline date in 2002, 2003, or 2004 using a forward stepwise selection based on a change in C-index threshold. Discrimination and calibration were assessed in the remaining participants (internal 'validation cohort'). A total of 66 831 individuals developed HFpEF, and 92 233 developed HFrEF (52 679 and 71 463 in the derivation cohort) over a median of 11.1 years of follow-up. The HFpEF risk prediction model included age, diabetes, BMI, COPD, previous MI, antihypertensive treatment, SBP, smoking status, atrial fibrillation, and estimated glomerular filtration rate (eGFR), while the HFrEF model additionally included previous CAD. For the HFpEF model, C-indices were 0.74 (SE = 0.002) for white men, 0.76 (0.005) for black men, 0.79 (0.015) for white women, and 0.77 (0.026) for black women, compared with 0.72 (0.002), 0.72 (0.004), 0.77 (0.017), and 0.75 (0.028), respectively, for the HFrEF model. These risk prediction models were generally well calibrated in each race-specific and sex-specific stratum of the validation cohort.
Our race-specific and sex-specific risk prediction models, which used easily obtainable clinical variables, can be a useful tool to implement preventive strategies or subtype-specific prevention trials in the nine million users of the VA healthcare system and the general population after external validation.
本研究旨在开发首个针对心力衰竭射血分数保留型（HFpEF）和降低型（HFrEF）的种族特异性和性别特异性风险预测模型。
我们创建了一个包含 180 万人的队列，这些人在 2002 年至 2007 年期间在退伍军人事务部（VA）医疗保健系统中进行了门诊就诊，并从电子健康记录（EHR）中获得了 HFpEF、HFrEF 和几个风险因素的信息。在包含 2002 年、2003 年或 2004 年基线日期的个体的“推导队列”中，使用基于 C 指数阈值变化的逐步向前选择来选择变量，用于风险预测模型。在其余参与者（内部“验证队列”）中评估了区分度和校准度。在中位随访 11.1 年期间，共有 66831 人发生 HFpEF，92233 人发生 HFrEF（推导队列中分别为 52679 人和 71463 人）。HFpEF 风险预测模型包括年龄、糖尿病、BMI、COPD、既往 MI、抗高血压治疗、SBP、吸烟状况、房颤和估计肾小球滤过率（eGFR），而 HFrEF 模型还包括既往 CAD。对于 HFpEF 模型，白人男性的 C 指数为 0.74（SE=0.002），黑人男性为 0.76（0.005），白人女性为 0.79（0.015），黑人女性为 0.77（0.026），而 HFrEF 模型分别为 0.72（0.002）、0.72（0.004）、0.77（0.017）和 0.75（0.028）。这些风险预测模型在验证队列的每个种族特异性和性别特异性亚组中通常具有良好的校准度。
我们的种族特异性和性别特异性风险预测模型使用了易于获得的临床变量，可以作为 VA 医疗保健系统的 900 万用户和一般人群实施预防策略或亚型特异性预防试验的有用工具，需进一步进行外部验证。
