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作 者:张春霞 李翔 孟晓静[1] 冯英璞[1] 周立民[1] ZHANG Chunxia;LI Xiang;MENG Xiaojing;FENG Yingpu;ZHOU Limin(Cerebrovascular Disease Hospital,Henan Provincial People′s Hospital,Henan 450003 China)
出 处:《全科护理》2022年第35期4902-4907,共6页Chinese General Practice Nursing
基 金:河南省卫生健康委员会河南省医学科技攻关计划省部共建项目和软科学项目,编号:SBGJ202003008;河南省卫生健康委员会河南省医学科技攻关计划省部共建项目,编号:SBGJ202102009。
摘 要:目的:构建重型颅脑损伤(sTBI)病人下肢深静脉血栓(LDVT)形成的风险预测模型,并评价预测效能。方法:选取2019年11月—2021年6月河南省人民医院神经外科重症监护室(ICU)收治的218例sTBI病人,分为建模组155例和验证组63例。利用Logistic回归构建LDVT风险预测模型,采用Hosmer-Lemeshow和ROC曲线下面积分别检验模型的拟合优度及预测效果。应用外部验证法检验模型的灵敏度、特异度和一致性。结果:最终纳入高血糖(OR=6.252)、多发伤(OR=7.066)、血管活性药(OR=10.307)、入住科室第7天血浆D-二聚体水平(OR=6.352)和肺部感染(OR=8.120)5个危险因素构建风险预测模型。Hosmer-Lemeshow检验P=0.807,ROC曲线下面积为0.900,约登指数为0.655,灵敏度为0.722,特异度为0.933。外部验证结果显示,灵敏度为0.615,特异度为0.880,准确率为82.5%。结论:基于sTBI病人临床资料构建的LDVT风险预测模型预测效能较好,可操作性强,适用于临床实际,为临床医护人员及时对高危病人采取预防性诊疗和护理提供参考。Objective:To construct a risk prediction model for the formation of lower extremity deep vein thrombosis(LDVT)in patients with severe traumatic brain injury(sTBI),and to evaluate the prediction performance.Methods:A total of 218 sTBI patients admitted to the Neurosurgery Intensive Care Unit(ICU)of Henan Provincial People′s Hospital from November 2019 to June 2021 were selected and divided into a modeling group of 155 cases and a verification group of 63 cases.The LDVT risk prediction model was constructed by Logistic regression,and the goodness of fit and prediction effect of the model were tested by Hosmer-Lemeshow and the area under the ROC curve,respectively.The sensitivity,specificity and consistency of the model were tested by external validation method.Results:This study finally included hyperglycemia(OR=6.252),multiple injuries(OR=7.066),vasoactive drugs(OR=10.307),plasma D-dimer level on the 7th day after entering the department(OR=6.352)and pulmonary infection(OR=8.120)5 risk factors for establishing a risk prediction model.Hosmer-Lemeshow test P=0.807,the area under the ROC curve was 0.900,the Youden index was 0.655,the sensitivity was 0.722,and the specificity was 0.933.The results of external validation showed that the sensitivity was 0.615,the specificity was 0.880,and the accuracy rate was 82.5%.Conclusions:The LDVT risk prediction model based on the clinical data of sTBI patients has good prediction efficiency,strong operability,and is applicable to clinical practice,providing reference for clinical medical staff to timely take preventive diagnosis and care for high-risk patients.
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