Publication Date
9-1-2021
Journal
American Journal of Preventive Cardiology
DOI
10.1016/j.ajpc.2021.100187
PMID
34611633
PMCID
PMC8387292
PubMedCentral® Posted Date
4-27-2021
PubMedCentral® Full Text Version
Post-print
Published Open-Access
yes
Keywords
Cholesterol, Lipid, ASCVD, Secondary prevention
Abstract
OBJECTIVE: The 2018 American Heart Association/American College of Cardiology (AHA/ACC) Blood Cholesterol Guideline recommendation to classify patients with atherosclerotic cardiovascular disease (ASCVD) as very high-risk (VHR) vs not-VHR (NVHR) has important implications for escalation of medical therapy. We aimed to define the prevalence and clinical characteristics of these two groups within a large multi-state healthcare system and develop a simpler means to assist clinicians in identifying VHR patients using classification and regression tree (CART) analysis.
METHODS: We performed a retrospective analysis of all patients in a 28-hospital US healthcare system in 2018. ICD-10 codes were used to define the ASCVD population. Per the AHA/ACC Guideline, VHR status was defined by ≥2 major ASCVD events or 1 major ASCVD event and ≥2 high-risk conditions. CART analysis was performed on training and validation datasets. A random forest model was used to verify results.
RESULTS: Of 180,669 ASCVD patients identified, 58% were VHR. Among patients with a history of myocardial infarction (MI) or recent acute coronary syndrome (ACS), 99% and 96% were classified as VHR, respectively. Both CART and random forest models identified recent ACS, ischemic stroke, hypertension, peripheral artery disease, history of MI, and age as the most important predictors of VHR status. Using five rules identified by CART analysis, fewer than 50% of risk factors were required to assign VHR status.
CONCLUSION: CART analysis helped to streamline the identification of VHR patients based on a limited number of rules and risk factors. This approach may help improve clinical decision making by simplifying ASCVD risk assessment at the point of care. Further validation is needed, however, in more diverse populations.
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Cardiology Commons, Cardiovascular Diseases Commons, Emergency Medicine Commons, Medical Sciences Commons
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