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The CAMI-score: A Novel Tool derived From CAMI Registry to Predict In-hospital Death among Acute Myocardial Infarction Patients

机译:CAMI评分:从CAMI注册中心获得的一种新型工具可预测急性心肌梗死患者的院内死亡

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摘要

Risk stratification of patients with acute myocardial infarction (AMI) is of clinical significance. Although there are many existing risk scores, periodic update is required to reflect contemporary patient profile and management. The present study aims to develop a risk model to predict in-hospital death among contemporary AMI patients as soon as possible after admission. We included 23417 AMI patients from China Acute Myocardial Infarction (CAMI) registry from January 2013 to September 2014 and extracted relevant data. Patients were divided chronologically into a derivation cohort (n = 17563) to establish the multivariable logistic regression model and a validation cohort (n = 5854) to validate the risk score. Sixteen variables were identified as independent predictors of in-hospital death and were used to establish CAMI risk model and score: age, gender, body mass index, systolic blood pressure, heart rate, creatinine level, white blood cell count, serum potassium, serum sodium, ST-segment elevation on ECG, anterior wall involvement, cardiac arrest, Killip classification, medical history of hypertension, medical history of hyperlipidemia and smoking status. Area under curve value of CAMI risk model was 0.83 within the derivation cohort and 0.84 within the validation cohort. We developed and validated a risk score to predict in-hospital death risk among contemporary AMI patients.
机译:急性心肌梗死(AMI)患者的风险分层具有临床意义。尽管存在许多现有的风险评分,但需要定期更新以反映当代患者的状况和管理。本研究旨在建立一种风险模型,以预测入院后当代AMI患者的院内死亡。我们纳入了2013年1月至2014年9月来自中国急性心肌梗死(CAMI)登记册的23417例AMI患者,并提取了相关数据。按时间顺序将患者分为派生队列(n = 17563)以建立多变量logistic回归模型和验证队列(n = 5854)以验证风险评分。确定了16个变量作为院内死亡的独立预测因素,并用于建立CAMI风险模型和评分:年龄,性别,体重指数,收缩压,心率,肌酐水平,白细胞计数,血清钾,血清钠,心电图ST段抬高,前壁受累,心脏骤停,基利普分类,高血压病史,高脂血症病史和吸烟状况。 CAMI风险模型的曲线下面积在衍生队列中为0.83,在验证队列中为0.84。我们开发并验证了风险评分,以预测当代AMI患者的院内死亡风险。

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