Comparison of Three Atherosclerotic Cardiovascular Disease Risk Scores With and Without Coronary Calcium for Predicting Revascularization and Major Adverse Coronary Events in Symptomatic Patients Undergoing Positron Emission Tomography-Stress Testing.

The American journal of cardiology(2019)

引用 10|浏览44
暂无评分
摘要
Atherosclerotic cardiovascular disease (ASCVD) is the most important cause of morbidity and mortality nationally and internationally. Improving ASCVD risk prediction is a high clinical priority. We sought to determine which of 3 ASCVD risk scores best predicts the need for revascularization and incident major adverse coronary events (MACE) in symptomatic patients at low-to-intermediate primary ASCVD risk referred for regadenoson-stress positron emission tomography (PET). Risk scores included the standard ASCVD pooled cohort equation (PCE), the multiethnic study of atherosclerosis (MESA) risk equation, and the coronary artery calcium score (CACS), obtained by PET. All qualifying patients in our institution at primary ASCVD risk referred for PET-stress tests in whom PCE, MESA, and CAC scores could be calculated were studied. CACS categories were: 0, 1 to 10, 11 to 299, 300 to 999, and 1000+. MESA and PCE scores were divided into quartiles. Logistic regression modeling was used to predict clinical/PET-driven early revascularization (within 90 days) and 1-year MACE (death, myocardial infarction, or any-time revascularization). A total of 981 patients (54% men, age 67 ± 10 years) qualified and were studied. Scores including CAC (MESA, CACS) performed better than PCE for predicting overall 1-year MACE (MESA p <0.001, CACS p = 0.012 vs PCE), which was driven by early revascularization. In conclusion, in a large population of patients at primary ASCVD risk referred for PET-stress testing, risk scores including CAC (CACS, MESA), which better predicted early revascularization and 1-year MACE, may be particularly useful in primary coronary risk assessment when considering whom to refer for PET-stress testing.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要