摘要
目的:探讨三维斑点追踪成像(3D-STI)技术与血生化指标联合预测新型冠状病毒肺炎住院患者死亡的价值。方法:收集2022年11月至2023年2月确诊并住院治疗的165例新冠肺炎患者的入院资料。使用LASSO回归筛选影响新冠肺炎患者死亡的指标。按照7∶3的比例进行数据拆分,在训练集上使用5次10折交叉验证进行预测模型构建,并绘制列线图以供实际使用。通过ROC曲线下面积、准确度、灵敏度和特异度进行模型评估。在测试集上绘制DCA曲线,以判断模型在临床决策中的实际效益。结果:LASSO回归共筛选出5个关键变量包括主应变、纵向应变、白蛋白、血肌酐及乳酸脱氢酶用于模型构建。训练集包括115例患者,测试集包括50例患者,两组基线资料无差异。在训练集和测试集中,ROC曲线下面积分别为0.909和0.882,准确度为0.835(0.754,0.898)和0.840(0.709,0.928),灵敏度为0.739和0.800,特异度为0.960和0.900。临床决策曲线图显示该模型的潜在临床获益可观。结论:三维斑点追踪成像联合血生化指标构建的列线图模型在预测新冠肺炎住院患者死亡风险方面具有较高的临床应用价值,可指导不良结局的早期干预。
Objective To investigate the value of three-dimensional speckle tracking imaging(3D-STI)combined with blood biochemical indices in predicting death for hospitalized patients with COVID-19.Methods The admission data were collected from 165 patients with COVID-19 diagnosed and hospitalized from November 2022 to February 2023.LASSO re⁃gression was employed to screen the indicators affecting the death of patients with COVID-19.The data were divided into a training set and a test set at a ratio of 7:3,and the prediction model was built by five times of 10-fold cross-validation on the training set.The nomogram was established for prediction.The model was evaluated in terms of the area under the re⁃ceiver operating characteristic(ROC)curve,accuracy,sensitivity and specificity.The decision curve analysis(DCA)was performed on the test set to determine the actual benefits of the model in clinical decision-making.Results Five key varia⁃bles including global principal strain,global longitudinal strain,albumin,serum creatinine and lactate dehydrogenase were selected by LASSO regression for model construction.The training set and test set included 115 and 50 patients,respective⁃ly,with no difference in baseline data.The prediction on the training set and test set showed,the area under ROC curve of 0.909 and 0.882,the accuracy of 0.835(0.754,0.898)and 0.840(0.709,0.928),the sensitivity of 0.739 and 0.800,and the specificity of 0.960 and 0.900,respectively.The DCA results indicated that the prediction model had considerable potential clinical benefits.Conclusion The nomogram model constructed by three-dimensional spot tracking imaging com⁃bined with blood biochemical indices has a high value in predicting the risk of death in hospitalized patients with COVID-19,and can guide the early intervention of adverse outcomes.
作者
邓鑫淦
韩宇琛
严定芳
张文君
DENG Xin-gan;HAN Yu-chen;YAN Ding-fang;ZHANG Wen-jun(Department of Ultrasound,Taihe Hospital,Hubei University of Medicine,Shiyan,Hubei 442000,China;School of Public Health,Hubei University of Medicine,Shiyan,Hubei 442000,China)
出处
《湖北医药学院学报》
CAS
2024年第1期46-51,共6页
Journal of Hubei University of Medicine
关键词
三维斑点追踪成像
血生化指标
新冠肺炎
死亡预测
Three-dimensional speckle tracking imaging
Blood biochemical index
COVID-19
Prediction of death
