A simplified approach to identification of risk status in patients with atherosclerotic cardiovascular disease
© 2021 The Authors. Published by Elsevier B.V..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:7 |
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| Enthalten in: |
American journal of preventive cardiology - 7(2021) vom: 17. Sept., Seite 100187 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sajja, Aparna [VerfasserIn] |
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| Anmerkungen: |
Date Revised 07.11.2023 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.ajpc.2021.100187 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM331528312 |
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| 245 | 1 | 2 | |a A simplified approach to identification of risk status in patients with atherosclerotic cardiovascular disease |
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| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a © 2021 The Authors. Published by Elsevier B.V. | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a ASCVD | |
| 650 | 4 | |a Cholesterol | |
| 650 | 4 | |a Lipid | |
| 650 | 4 | |a Secondary prevention | |
| 700 | 1 | |a Li, Hsin-Fang |e verfasserin |4 aut | |
| 700 | 1 | |a Spinelli, Kateri J |e verfasserin |4 aut | |
| 700 | 1 | |a Ali, Amir |e verfasserin |4 aut | |
| 700 | 1 | |a Virani, Salim S |e verfasserin |4 aut | |
| 700 | 1 | |a Martin, Seth S |e verfasserin |4 aut | |
| 700 | 1 | |a Gluckman, Ty J |e verfasserin |4 aut | |
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