急性心肌梗死患者经皮冠状动脉介入术后发生造影剂相关急性肾损伤预测模型的构建

Construction of a predictive model for contrast⁃associated acute kidney injury after percutaneous coronary intervention in patients with acute myocardial infarction

目的:分析急性心肌梗死(AMI)患者经皮冠状动脉介入(PCI)术后发生造影剂相关急性肾损伤(CAAKI)的危险因素,并建立风险预测模型。方法:回顾性分析2013年12月—2019年2月在武汉大学中南医院住院明确诊断为AMI并接受PCI术的348例患者的临床资料,根据是否发生CA-AKI分组。采用二元Logistic回归分析进行危险因素分析,建立回归方程,构建列线图模型,并对预测模型的预测价值进行评估。结果:348例患者CAAKI发生率为8.33%。Logistic回归分析结果显示,白细胞计数、血清磷、LVEF<50%是AMI患者PCI术后发生CA-AKI的独立危险因素(P<0.05)。预测模型其ROC曲线下面积为0.742 (95%CI:0.655~0.829,P<0.001),Hosmer-Lemeshow检验预测模型拟合效果:χ2=12.356,P=0.136,校正曲线显示其预测可能性平均绝对误差为0.022,具有良好的区分度和准确性。结论:白细胞计数、血清磷、LVEF<50%是AMI患者PCI术后发生CA-AKI的独立危险因素。本研究得出的风险预测模型可早期预测CA-AKI的发生,为临床决策提供帮助。

Objective:To analyze the risk factors of contrast⁃associated acute kidney injury(CA⁃AKI)in pa⁃tients with acute myocardial infarction(AMI)after percutaneous coronary intervention(PCI)and estab⁃lish a risk prediction model.Methods::A retrospective analysis was performed on 348 AMI patients in Zhongnan Hospital of Wuhan University from December 2013 to February 2019 and underwent PCI.They were grouped according to whether CA⁃AKI occurred.We used the binary logistic regression analysis to analyze the risk factors and established the regression equation,then constructed the nomo⁃graph model,and evaluated the predictive value of the prediction model.Results::The incidence of CA⁃AKI in 348 patients was 8.33%.Logistic regression analysis showed that white blood cell count,serum phosphorus,and LVEF<50%were independent risk factors for CA⁃AKI in AMI patients af⁃ter PCI(P<0.05).The area under the ROC curve of the prediction model was 0.742(95%CI:0.655⁃0.829,P<0.001)and chi⁃square for the fit of the model was 12.356(P=0.136).The calibration curve showed that the average absolute error of prediction possibility was 0.022,indicating a better discrimination and accuracy of the prediction model.Conclusion::White blood cell count,serum phos⁃phorus,and LVEF<50%were independent risk factors for CA⁃AKI in AMI patients after PCI.The risk prediction model obtained in this study can predict the occurrence of CA⁃AKI early and provide help for clinical decision⁃making.