摘要
目的探讨通过使用高斯过程模型(GPM)和超声心动图参数建立的风险预测模型对慢性左室收缩功能减低(LVSD)心衰患者进行1年再入院风险评估的临床价值。方法收集并整理慢性LVSD患者290例,以1年内再入院为本研究终点。所有患者行常规超声心动图检查,并收集二尖瓣反流、三尖瓣反流、胸腔积液、心包积液、肺动脉收缩压、左心室内径及左室射血分数等参数数据。将290例患者随机分为70%训练数据和30%测试数据,使用机器学习算法对训练数据集进行信息交互分析,评估各项参数的重要性,并融合多超声参数建立GPM预测系统模型。随后利用GPM风险预测系统模型对测试数据集患者1年内再入院风险进行分析,将所有患者纳入超声心动图参数积分系统(超声积分系统)进行预测,最后通过受试者工作特征曲线(ROC)对两种方法进行分析比较。结果利用GPM信息交互分析各项超声心动图参数的权重分别为:二尖瓣反流23.64%,三尖瓣反流22.09%,胸腔积液16.18%,心包积液14.36%,肺动脉收缩压9.04%,左心室内径8.86%,左室射血分数5.83%。基于GPM的风险预测系统与超声积分系统的受试者工作特征曲线下面积(AUC)分别为83.10%(95%CI:0.797~0.864)和70.60%(95%CI:0.647~0.765)。结论基于超声心动图参数的高斯过程模型能够很好的预测LVSD患者1年再入院风险,并优于超声参数积分系统。
Objective To explore the predictive value of a 1-year readmission risk assessment for patients with chronic left ventricular systolic function(LVSD)by using a Gaussian process model(GPM)and echocardiographic parameters.Methods A total of 290 patients with chronic LVSD were collected,and re-hospitalization within one year was the end point of the study.All patients underwent routine echocardiography to collect data including mitral regurgitation,tricuspid regurgitation,pleural effusion,pericardial effusion,pulmonary artery systolic pressure,left ventricular diameter and left ventricular ejection fraction.The 290 patients were randomly divided into 70%training group(modeling group)and 30%testing group(prediction group).The information interaction analysis on the training dataset was carried out with machine learning algorithms.The importance of each parameter was evaluated,and echocardiographic parameters were merged to establish GPM.Subsequently,the readmission risk of the testing dataset was analyzed using GPM.In addition,the risk of all patients was predicted with the echocardiography parameter scoring system.Finally the two methods were compared with receiver operating characteristic(ROC)curve.Results GPM information interaction analysis showed the weights of echocardiographic parameters were:mitral regurgitation 23.64%,tricuspid regurgitation 22.09%,pleural effusion 16.18%,pericardial effusion 14.36%,pulmonary artery contraction pressure 9.04%,left ventricular diameter 8.86%,and left ventricular ejection fraction 5.83%.Based on GPM and echocardiography parameter scoring system,the area under the ROC curve(AUC)was 83.10%(95%CI:0.797-0.864),70.60%(95%CI:0.647-0.765),respectively.Conclusion GPM based on echocardiographic parameters can well predict the readmission risk of LVSD patients within one year,and it is superior to echocardiography parameter scoring system.
作者
张传备
李方
翟春晓
余永明
舒明雷
王艺丹
徐良栋
郝恩魁
ZHANG Chuanbei;LI Fang;ZHAI Chunxiao;YU Yongming;SHU Minglei;WANG Yidan;XU Liangdong;HAO Enkui(Clinical Medical College of Weifang Medical College,Weifang 261000,Shandong,China;Department of Health,Jinan Central Hospital,Jinan 250012,Shandong,China;Department of Cardiology,Shandong Provincial Qianfoshan Hospital,Jinan 250012,Shandong,China;School of Control Science and Materials,Shandong University,Jinan 250012,Shandong,China;National Supercomputer Center in Jinan,Jinan 250012,Shandong,China;Emergency Department,Dezhou People's Hospital,Dezhou 253000,Shandong,China)
出处
《山东大学学报（医学版）》
CAS
北大核心
2020年第6期28-33,共6页
Journal of Shandong University:Health Sciences
基金
2014年山东省科技发展计划(2014GSF118187)。
关键词
左室功能减低
高斯过程模型
超声心动图
1年再入院率
Left ventricular systolic dysfunction
Gaussian Process Model
Echocardiography
One-year readmission rate
