CAMI-NSTEMI Score　― China Acute Myocardial Infarction Registry-Derived Novel Tool to Predict In-Hospital Death in Non-ST Segment Elevation Myocardial Infarction 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-hospi...

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Published in:Circulation Journal 2018/06/25, Vol.82(7), pp.1884-1891
Main Authors: Fu, Rui, Song, Chenxi, Yang, Jingang, Wang, Yan, Li, Bao, Xu, Haiyan, Gao, Xiaojin, Li, Wei, Liu, Jia, Dou, Kefei, Yang, Yuejin, on behalf of the CAMI Registry Study Group
Format: Article
Language:English
Subjects:
Aged
Aged, 80 and over
Area Under Curve
China
Hospital Mortality
Humans
In-hospital mortality
Logistic Models
Middle Aged
Myocardial Infarction - mortality
Non-ST Elevated Myocardial Infarction - diagnosis
Non-ST Elevated Myocardial Infarction - mortality
Non-ST segment elevation myocardial infarction
Predictive Value of Tests
Registries
Risk Assessment
Risk prediction
Score system
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Summary: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
ISSN:1346-9843
1347-4820
1347-4820
DOI:10.1253/circj.CJ-17-1078