In-Chang Hwang1, Heesun Lee2, Yeonyee E Yoon3, In-Soon Choi4, Hack-Lyoung Kim5, Hyuk-Jae Chang6, Ja Youn Lee7, Jin A Choi7, Hyo Jeong Kim7, Goo-Yeong Cho1, Jun-Bean Park8, Seung-Pyo Lee8, Hyung-Kwan Kim8, Yong-Jin Kim8, Dae-Won Sohn8. 1. Department of Cardiology, Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam, Gyeonggi, South Korea; Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea. 2. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Healthcare System Gangnam Center, Seoul National University Hospital, Seoul, South Korea. 3. Department of Cardiology, Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam, Gyeonggi, South Korea; Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea. Electronic address: yeonyeeyoon@snubh.org. 4. National Evidence-Based Healthcare Collaborating Agency, Seoul, South Korea. Electronic address: ischoi@neca.re.kr. 5. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Division of Cardiology, Department of Internal Medicine, Boramae Medical Center, Seoul, South Korea. 6. Division of Cardiology, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, South Korea. 7. National Evidence-Based Healthcare Collaborating Agency, Seoul, South Korea. 8. Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Cardiovascular Center and Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea.
Abstract
BACKGROUND AND AIMS: Given the potential benefit of medical therapy in patients with non-obstructive coronary artery disease (CAD), there is a need for risk stratification and treatment strategy for these patients. We aimed to develop a risk prediction model for non-obstructive CAD patients for risk stratification and guidance of statin and aspirin therapy. METHODS: From a cohort of consecutive patients who underwent coronary computed tomography angiography (CCTA) (n = 25,087), we identified patients with non-obstructive CAD of 1-49% diameter-stenosis (n = 6243) and developed a risk prediction model for 5-year occurrence of a composite of all-cause mortality, myocardial infarction, and late coronary revascularization using a derivation cohort (n = 4391). RESULTS: Age, sex, hypertension, diabetes, anemia, C-reactive protein, and the extent of non-obstructive CAD were incorporated in the prediction model (risk score 0-13, C-index = 0.716). Patients were categorized into 4 groups; risk score of 0-3 (low-risk), 4-6 (intermediate-risk), 7-9 (high-risk), and ≥10 (very high-risk). Patients with very high-risk demonstrated unfavorable outcome comparable to patients with obstructive CAD. The low-risk group exhibited favorable outcome similar to those with no CAD. While statin therapy was associated with better outcomes in high- or very high-risk group (hazard ratio, 0.62; 95% confidence interval, 0.39-0.96; p = 0.033), aspirin use was associated with an increased risk in low-risk group (hazard ratio, 2.57; 95% confidence interval, 1.34-4.90; p = 0.004). CONCLUSIONS: A dedicated risk scoring system for non-obstructive CAD using clinical factors and CCTA findings accurately predicted prognosis. According to our risk prediction model, statin therapy can be beneficial for high-risk patients, whereas aspirin can be harmful for low-risk patients.
BACKGROUND AND AIMS: Given the potential benefit of medical therapy in patients with non-obstructive coronary artery disease (CAD), there is a need for risk stratification and treatment strategy for these patients. We aimed to develop a risk prediction model for non-obstructive CADpatients for risk stratification and guidance of statin and aspirin therapy. METHODS: From a cohort of consecutive patients who underwent coronary computed tomography angiography (CCTA) (n = 25,087), we identified patients with non-obstructive CAD of 1-49% diameter-stenosis (n = 6243) and developed a risk prediction model for 5-year occurrence of a composite of all-cause mortality, myocardial infarction, and late coronary revascularization using a derivation cohort (n = 4391). RESULTS: Age, sex, hypertension, diabetes, anemia, C-reactive protein, and the extent of non-obstructive CAD were incorporated in the prediction model (risk score 0-13, C-index = 0.716). Patients were categorized into 4 groups; risk score of 0-3 (low-risk), 4-6 (intermediate-risk), 7-9 (high-risk), and ≥10 (very high-risk). Patients with very high-risk demonstrated unfavorable outcome comparable to patients with obstructive CAD. The low-risk group exhibited favorable outcome similar to those with no CAD. While statin therapy was associated with better outcomes in high- or very high-risk group (hazard ratio, 0.62; 95% confidence interval, 0.39-0.96; p = 0.033), aspirin use was associated with an increased risk in low-risk group (hazard ratio, 2.57; 95% confidence interval, 1.34-4.90; p = 0.004). CONCLUSIONS: A dedicated risk scoring system for non-obstructive CAD using clinical factors and CCTA findings accurately predicted prognosis. According to our risk prediction model, statin therapy can be beneficial for high-risk patients, whereas aspirin can be harmful for low-risk patients.
Authors: Jana Taron; Borek Foldyna; Thomas Mayrhofer; Michael T Osborne; Nandini Meyersohn; Daniel O Bittner; Stefan B Puchner; Hamed Emami; Michael T Lu; Maros Ferencik; Neha J Pagidipati; Pamela S Douglas; Udo Hoffmann Journal: JACC Cardiovasc Imaging Date: 2021-04-14
Authors: Donghee Han; Daniel S Berman; Robert J H Miller; Daniele Andreini; Matthew J Budoff; Filippo Cademartiri; Kavitha Chinnaiyan; Jung Hyun Choi; Edoardo Conte; Hugo Marques; Pedro de Araújo Gonçalves; Ilan Gottlieb; Martin Hadamitzky; Jonathon Leipsic; Erica Maffei; Gianluca Pontone; Sangshoon Shin; Yong-Jin Kim; Byoung Kwon Lee; Eun Ju Chun; Ji Min Sung; Sang-Eun Lee; Renu Virmani; Habib Samady; Peter Stone; Jagat Narula; Jeroen J Bax; Leslee J Shaw; Fay Y Lin; James K Min; Hyuk-Jae Chang Journal: JAMA Netw Open Date: 2020-07-01
Authors: Caroline A Berge; Ingeborg Eskerud; Elise B Almeland; Terje H Larsen; Eva R Pedersen; Svein Rotevatn; Mai Tone Lønnebakken Journal: PLoS One Date: 2022-01-21 Impact factor: 3.240