Rui Fu1,2, Chenxi Song1,2, Jingang Yang1,2, Yan Wang3, Bao Li4, Haiyan Xu1,2, Xiaojin Gao1,2, Wei Li1,2, Jia Liu1,2, Kefei Dou1,2, Yuejin Yang1,2. 1. State Key Laboratory of Cardiovascular Disease, Department of Cardiology, Cardiovascular Institute, Fuwai Hospital. 2. National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences & Peking Union Medical College. 3. Xiamen Cardiovascular Hospital, Xiamen University. 4. Shanxi Province Cardiovascular Hospital.
Abstract
BACKGROUND: Accurate risk stratification of non-ST segment elevation myocardial infarction (NSTEMI) patients is important due to great variability in mortality risk, but, to date, no prediction model has been available. The aim of this study was therefore to establish a risk score to predict in-hospital mortality risk in NSTEMI patients.Methods and Results: We enrolled 5,775 patients diagnosed with NSTEMI from the China Acute Myocardial Infarction (CAMI) registry and extracted relevant data. Patients were divided into a derivation cohort (n=4,332) to develop a multivariable logistic regression risk prediction model, and a validation cohort (n=1,443) to test the model. Eleven variables independently predicted in-hospital mortality and were included in the model: age, body mass index, systolic blood pressure, Killip classification, cardiac arrest, electrocardiogram ST-segment depression, serum creatinine, white blood cells, smoking status, previous angina, and previous percutaneous coronary intervention. In the derivation cohort, the area under curve (AUC) for the CAMI-NSTEMI risk model and score was 0.81 and 0.79, respectively. In the validation cohort, the score also showed good discrimination (AUC, 0.86). Diagnostic performance of CAMI-NSTEMI risk score was superior to that of the GRACE risk score (AUC, 0.81 vs. 0.72; P<0.01). CONCLUSIONS: The CAMI-NSTEMI score is able to accurately predict the risk of in-hospital mortality in NSTEMI patients.
BACKGROUND: Accurate risk stratification of non-ST segment elevation myocardial infarction (NSTEMI) patients is important due to great variability in mortality risk, but, to date, no prediction model has been available. The aim of this study was therefore to establish a risk score to predict in-hospital mortality risk in NSTEMI patients.Methods and Results: We enrolled 5,775 patients diagnosed with NSTEMI from the China Acute Myocardial Infarction (CAMI) registry and extracted relevant data. Patients were divided into a derivation cohort (n=4,332) to develop a multivariable logistic regression risk prediction model, and a validation cohort (n=1,443) to test the model. Eleven variables independently predicted in-hospital mortality and were included in the model: age, body mass index, systolic blood pressure, Killip classification, cardiac arrest, electrocardiogram ST-segment depression, serum creatinine, white blood cells, smoking status, previous angina, and previous percutaneous coronary intervention. In the derivation cohort, the area under curve (AUC) for the CAMI-NSTEMI risk model and score was 0.81 and 0.79, respectively. In the validation cohort, the score also showed good discrimination (AUC, 0.86). Diagnostic performance of CAMI-NSTEMI risk score was superior to that of the GRACE risk score (AUC, 0.81 vs. 0.72; P<0.01). CONCLUSIONS: The CAMI-NSTEMI score is able to accurately predict the risk of in-hospital mortality in NSTEMI patients.