期刊
CIRCULATION
卷 148, 期 24, 页码 1982-2004出版社
LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1161/CIR.0000000000001191
关键词
AHA Scientific Statements; cardiovascular diseases; heart failure; kidney diseases; metabolic syndrome; models, cardiovascular; risk assessment; social determinants of health
Cardiovascular-kidney-metabolic (CKM) syndrome is a novel concept defined by the American Heart Association, and there is a need to refine risk assessment strategies. The newly developed PREVENT equations are sex-specific and race-free risk prediction equations that estimate 10- and 30-year risk for total cardiovascular disease. These equations also consider clinical indicators and social determinants of health to enhance predictive utility.
Cardiovascular-kidney-metabolic (CKM) syndrome is a novel construct recently defined by the American Heart Association in response to the high prevalence of metabolic and kidney disease. Epidemiological data demonstrate higher absolute risk of both atherosclerotic cardiovascular disease (CVD) and heart failure as an individual progresses from CKM stage 0 to stage 3, but optimal strategies for risk assessment need to be refined. Absolute risk assessment with the goal to match type and intensity of interventions with predicted risk and expected treatment benefit remains the cornerstone of primary prevention. Given the growing number of therapies in our armamentarium that simultaneously address all 3 CKM axes, novel risk prediction equations are needed that incorporate predictors and outcomes relevant to the CKM context. This should also include social determinants of health, which are key upstream drivers of CVD, to more equitably estimate and address risk. This scientific statement summarizes the background, rationale, and clinical implications for the newly developed sex-specific, race-free risk equations: PREVENT (AHA Predicting Risk of CVD Events). The PREVENT equations enable 10- and 30-year risk estimates for total CVD (composite of atherosclerotic CVD and heart failure), include estimated glomerular filtration rate as a predictor, and adjust for competing risk of non-CVD death among adults 30 to 79 years of age. Additional models accommodate enhanced predictive utility with the addition of CKM factors when clinically indicated for measurement (urine albumin-to-creatinine ratio and hemoglobin A1c) or social determinants of health (social deprivation index) when available. Approaches to implement risk-based prevention using PREVENT across various settings are discussed.
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