Multivariate prediction of major adverse cardiac events after 9914 percutaneous coronary interventions in the north west of England
Multivariate prediction of major adverse cardiac events after 9914 percutaneous coronary interventions in the north west of England
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DOI：
10.1136/hrt.2005.066415
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发表时间：
2006-05-01
期刊：
影响因子：
5.7
通讯作者：
Stables, RH
中科院分区：
文献类型：
--
作者：
Grayson, AD;Moore, RK;Stables, RH
目的：利用西北心脏干预质量改进计划（NWQIP） PCI Registry建立经皮冠状动脉介入治疗（PCI）后主要心脏不良事件（MACE）的多变量预测模型。环境：所有NHS中心在英格兰西北部开展成人pci。方法：回顾性分析2001年8月1日至2003年12月31日连续9914例成人PCI患者的前瞻性资料。采用正向逐步技术进行多变量logistic回归分析，以确定MACE的独立危险因素。计算受试者工作特征（ROC）曲线下面积和Hosmer-Lemeshow拟合优度统计量，分别评估模型的性能和校准。利用自举重采样技术对统计模型进行了内部验证。主要观察指标：MACE：住院死亡率、Q波心肌梗死、急诊冠状动脉搭桥手术、脑血管意外。结果：与MACE发生风险增加相关的独立变量为高龄、女性、脑血管疾病、心源性休克、优先级以及PCI期间左主干或移植物病变的治疗。MACE预测概率的ROC曲线为0.76，具有较好的判别能力。预测方程经过了很好的校准，可以很好地预测所有级别的风险。自举表明，估计是稳定的。结论：建立了PCI术后MACE的同期多变量预测模型。NWQIP工具允许计算MACE风险，允许对医院和运营商之间的绩效进行有意义的风险调整比较。
Objective: To develop a multivariate prediction model for major adverse cardiac events (MACE) after percutaneous coronary interventions (PCIs) by using the North West Quality Improvement Programme in Cardiac Interventions (NWQIP) PCI Registry.Setting: All NHS centres undertaking adult PCIs in north west England.Methods: Retrospective analysis of prospectively collected data on 9914 consecutive patients undergoing adult PCI between 1 August 2001 and 31 December 2003. A multivariate logistic regression analysis was undertaken, with the forward stepwise technique, to identify independent risk factors for MACE. The area under the receiver operating characteristic (ROC) curve and the Hosmer-Lemeshow goodness of fit statistic were calculated to assess the performance and calibration of the model, respectively. The statistical model was internally validated by using the technique of bootstrap resampling.Main outcome measures: MACE, which were in-hospital mortality, Q wave myocardial infarction, emergency coronary artery bypass graft surgery, and cerebrovascular accidents. Results: Independent variables identified with an increased risk of developing MACE were advanced age, female sex, cerebrovascular disease, cardiogenic shock, priority, and treatment of the left main stem or graft lesions during PCI. The ROC curve for the predicted probability of MACE was 0.76, indicating a good discrimination power. The prediction equation was well calibrated, predicting well at all levels of risk. Bootstrapping showed that estimates were stable.Conclusions: A contemporaneous multivariate prediction model for MACE after PCI was developed. The NWQIP tool allows calculation of the risk of MACE permitting meaningful risk adjusted comparisons of performance between hospitals and operators.