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.
|Number of pages||8|
|Publication status||Published - 2019 Nov|
Bibliographical noteFunding Information:
This research was funded by the National Evidence-based Healthcare Collaborating Agency (NECA), South Korea (grant number NECA-C-15-009 ).
This research was funded by the National Evidence-based Healthcare Collaborating Agency (NECA), South Korea (grant number NECA-C-15-009).
© 2019 Elsevier B.V.
All Science Journal Classification (ASJC) codes
- Cardiology and Cardiovascular Medicine