基于LASSO-logistic回归构建脑出血术后下肢静脉血栓的风险预测模型
A risk prediction model for lower limb venous thrombosis after cerebral hemorrhage surgery based on LASSO-logistic regression
郝广志 1董玉书 1张冰莹 1孙琳琳 1高阳 1熊剑1
作者信息
- 1. 北部战区总医院神经外科,辽宁 沈阳 110016
- 折叠
摘要
目的 基于LASSO-logistic回归筛选脑出血(intracerebral hemorrhage,ICH)患者术后下肢静脉血栓发生的危险因素并构建临床预测模型.方法 选取2023年2月至2024年 4月北部战区总医院收治的768例自发性脑出血患者,根据1∶1比例随机分为训练集和验证集.在训练集病例中通过Lasso回归和单因素logistic回归筛选导致脑出血术后静脉血栓形成的可疑危险因素,通过多因素逐步logistic回归确定独立危险因素并构建模型.绘制列线图进行可视化展示,计算受试者工作特征(receiver operation characteristic,ROC)曲线下面积、绘制校准图对构建的模型进行评估,通过临床决策曲线分析(decision curve analysis,DCA)评价模型临床应用价值.结果 ICH后静脉血栓的发生与年龄、糖尿病、格拉斯哥昏迷量表(Glasgow Coma Scale,GCS)评分、血液纤维蛋白原含量相关(P<0.05),与血压、性别、饮酒、吸烟、和手术方式无关(P>0.05).模型的ROC曲线下面积为0.840(95%CI:0.773-0.907).校准曲线一致性良好、Hosmer-Lemeshow拟合优度检验χ2=9.596(P=0.384),表明该模型具有良好的区分度和校准度.DCA中,阈值概率在0.02和0.80之间预测模型具有良好的净获益.结论 高龄(>60岁)、糖尿病、GCS评分低、血液中纤维蛋白原含量(>4 g/L)为自发性脑出血术后下肢静脉血栓发生的独立影响因素,依此构建的预测模型具有良好临床应用价值.
Abstract
Objective To construct a clinical prediction model on the risk factors of postoperative venous thrombosis in patients with intracerebral hemorrhage(ICH)based on LASSO-logistic regression.Methods A total of 768 patients with spontaneous cerebral hemorrhage admitted to the General Hospital of the Northern Theater Command from February 2023 to April 2024 were selected and randomly divided into the training set and the verification set according to the 1:1 ratio.Lasso regression and univariate logistic regression were used in the training set of cases to search for suspected risk factors leading to venous thrombosis after intracerebral hemorrhage.Independent risk factors were determined by multivariate logistic regression and a prediction model on such rick factors was constructed.Nomogram was drawn for visual display,the area under ROC curve was calculated,calibration chart was drawn to evaluate the constructed model,and clinical application value of the model was evaluated by clinical decision curve analysis(DCA).Results The incidence of post-ICH venous thrombosis was correlated with age,diabetes,GCS score and blood fibrinogen content(P<0.05),rather than blood pressure,sex,drinking,smoking,and operation mode(P>0.05).The area under ROC curve of the model was 0.840(95%CI:0.773-0.907).The good consistency of calibration curves and the Hosmer-Lemeshow goodness of fit test(χ2=9.596,P=0.384)showed that the model had good differentiation and calibration.The threshold probability in DCA was between 0.02 and 0.80,which indicated that the model had a good net benefit.Conclusion Advanced age(>60),diabetes mellitus,low GCS score,and fibrinogen(>4 g/L)are independent influencing factors for the occurrence of lower extremity venous thrombosis after spontaneous intracerebral hemorrhage.The prediction model based on these factors has good clinical application value.
关键词
自发性脑出血/静脉血栓/Lasso回归/诺莫图Key words
Spontaneous cerebral hemorrhage/Venous thrombosis/Lasso regression/Nomogram引用本文复制引用
出版年
2024
NETL
NSTL
万方数据