摘要
目的基于急诊实验室指标建立重型颅脑损伤(sTBI)患者早期死亡的个体化预警模型。方法回顾性分析2020年1月—2022年6月苏北人民医院急诊路径收治的249例sTBI患者的临床资料。基于患者急诊实验室指标,采用最小绝对收缩和选择算子(LASSO)算法,筛选sTBI早期死亡的最大相关特征,并进一步使用二元Logistic回归模型建立个体化急诊指标列线图。采用决策曲线分析,判断急诊实验室指标及其所构建的列线图的临床价值。结果LASSO算法所保留的急诊实验室预测指标的预测价值为:碱剩余的曲线下面积(AUC)为0.711,血红蛋白的AUC为0.718,凝血酶原时间的AUC为0.754,活化凝血酶原时间的AUC为0.804,纤维蛋白原的AUC为0.656,D-二聚体的AUC为0.804,输注浓缩红细胞的AUC为0.796。由上述7个实验室指标构建的列线图的预测能力高(AUC为0.975)。结论传统急诊实验室指标可实现对sTBI患者死亡的早期预测,由7个急诊实验室指标构建的列线图预测sTBI患者早期死亡的准确性较高。
Objective To establish an individualized warning model for predicting death in early stage in patients with severe traumatic brain injury(sTBI)based on emergency laboratory indicators.Methods Clinical materials of 249 sTBI patients treated through emergency pathway in Northern Jiangsu People′s Hospital from January 2020 to June 2022 were retrospectively analyzed.Based on the emergency laboratory indicators of the patients,the least absolute shrinkage and selection operator (LASSO)algorithm was used to screen the maximum correlation features of death in early stage of sTBI,and a binary Logistic regression model was furtherly used to establish an individualized emergency indicator line nomogram.The clinical values of the emergency laboratory indicators and the established line nomogram were evaluated by decision curve analysis.Results The predictive values of the emergency laboratory indicators retained by the LASSO algorithm were as follows:the area under the curve(AUC)for base excess was 0.711,AUC for hemoglobin was 0.718,AUC for prothrombin time was 0.754,AUC for activated partial thromboplastin time was 0.804,AUC for fibrinogen was 0.656,AUC for D-dimer was 0.804,and AUC for transfusion of concentrated red blood cells was 0.796.The predictive ability of the nomogram established by the above seven laboratory indicators was higher (AUC of 0.975).Conclusion The traditional emergency laboratory indicators can be used for early prediction of death in sTBI patients,and the accuracy of predicting death in early stage in sTBI patients by the nomogram established with the seven emergency laboratory indicators is high.
作者
赵霞
陆娟
王晓东
谈定玉
陆明峰
ZHAO Xia;LU Juan;WANG Xiaodong;TAN Dingyu;LU Mingfeng(Department of Emergency,Northern Jiangsu People′s Hospital of Jiangsu Province,Yangzhou,Jiangsu,225000;Neurological Intensive Care Unit,Northern Jiangsu People′s Hospital of Jiangsu Province,Yangzhou,Jiangsu,225000)
出处
《实用临床医药杂志》
2023年第13期37-42,共6页
Journal of Clinical Medicine in Practice
基金
江苏省医院协会医院管理创新研究课题计划(JSYGY-2-2020-730)
江苏省卫生应急研究所课题计划(JSWSYJ-20210801)。
关键词
重型颅脑损伤
急诊实验室指标
早期死亡
临床预测模型
severe traumatic brain injury
emergency laboratory indicators
death in early stage
clinical prediction model
