首页> 外文期刊>Circulation journal >CAMI-NSTEMI Score ― China Acute Myocardial Infarction Registry-Derived Novel Tool to Predict In-Hospital Death in Non-ST Segment Elevation Myocardial Infarction Patients ―
【24h】

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

机译:CAMI-NSTEMI评分―中国急性心肌梗死注册中心推出的新型工具,可预测非ST段抬高型心肌梗死患者的院内死亡―

获取原文
           

摘要

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 Conclusions: The CAMI-NSTEMI score is able to accurately predict the risk of in-hospital mortality in NSTEMI patients.
机译:背景:由于死亡风险的巨大差异,非ST段抬高型心肌梗死(NSTEMI)患者的准确风险分层非常重要,但是迄今为止,尚无可用的预测模型。因此,本研究的目的是建立风险评分,以预测NSTEMI患者的院内死亡风险。方法和结果:我们从中国急性心肌梗死(CAMI)注册表中招募了5,775名被诊断为NSTEMI的患者,并提取了相关数据。将患者分为派生队列(n = 4,332)以开发多变量logistic回归风险预测模型,以及验证队列(n = 1,443)以测试模型。该模型包括11个独立预测院内死亡率的变量:年龄,体重指数,收缩压,基利分类,心脏骤停,心电图ST段压低,血清肌酐,白细胞,吸烟状态,以前的心绞痛,和以前的经皮冠状动脉介入治疗。在派生队列中,CAMI-NSTEMI风险模型的曲线下面积(AUC)和得分分别为0.81和0.79。在验证队列中,分数也显示出良好的区分度(AUC,0.86)。 CAMI-NSTEMI风险评分的诊断性能优于GRACE风险评分(AUC,0.81 vs. 0.72; P结论):CAMI-NSTEMI评分能够准确预测NSTEMI患者住院死亡的风险。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号