基于Rotterdam CT评分及凝血功能指标的创伤性颅脑损伤预后预测模型的构建与验证

Construction and validation of prognosis prediction model of traumatic brain injury based on Rotterdam CT score and coagulation function index

目的探究基于鹿特丹(Rotterdam)CT评分、凝血功能指标的创伤性颅脑损伤(TBI)预后预测模型的构建与验证。方法选取安徽省第二人民医院灵璧医院神经外科自2020年1月至2022年1月收治的108例TBI患者为研究对象,所有患者入院24 h内均行CT影像检查与鹿特丹(Rotterdam)CT评分,同时予以凝血功能指标检测,根据治疗后6个月GOS评分将患者分为预后良好组(4~5分)和预后不良组(1~3分),采用二元Logistic回归分析筛选TBI患者预后的独立影响因素,并基于Rotterdam CT评分、凝血功能指标[凝血酶原时间(PT)、活化部分凝血活酶时间(APTT)、D-二聚体(D-D)]构建TBI预后的预测模型,建立受试者工作特征(ROC)曲线评估模型的预测效能。同时收集我院2019年1~12月收治的46例TBI患者的临床资料作为验证集,验证预测模型的准确性。结果108例患者中,预后良好组73例,预后不良组35例。预后不良组患者病情重型、合并低血氧、Rotterdam CT评分和凝血功能指标(PT、APTT、D-D)均高于预后良好组,差异均有统计学意义(P<0.05)。Logistic回归分析显示病情、Rotterdam CT评分、PT、D-D是TBI患者预后不良的独立影响因素(P<0.05)。TBI预后不良预测模型Y=3.078×Rotterdam评分CT评分-0.847×PT+1.211×D-D-1.672×病情严重程度-3.195。该预测模型预测预后不良的敏感度为0.886,特异度为0.836,约登指数为0.722,界值为0.262,曲线下面积为0.937。采用Hanley&McNeil法对预测模型与验证曲线比较检验发现,2个模型ROC曲线的AUC比较差异无统计学意义(P<0.05)。结论对于TBI患者,采用基于Rotterdam CT评分、凝血功能指标的预测模型有较好准确性,值得推广。

Objective To explore the construction and validation of a prediction model for the prognosis of traumatic brain injury(TBI)based on Rotterdam CT score and coagulation function indicators.Methods A total of 108 TBI patients admitted to Neurosurgery Department of Lingbi Hospital of the Second People's Hospital of Anhui Province from January 2020 to January 2022 were selected as the study objects.CT image examination and Rotterdam CT score were performed on all patients within 24 h of admission,and coagulation function index was also detected.Based on the GOS score at 6 months after treatment,patients were divided into a good prognosis group(4-5 score)and a poor prognosis group(1-3 score).Binary Logistic regression analysis was used to screen the independent factors influencing the prognosis of TBI patients,and a prediction model of TBI prognosis was constructed based on Rotterdam CT score and coagulation function index[prothrombin time(PT),activated partial thromboplastin time(APTT),D-dimer(D-D)].Receiver operating characteristic(ROC)curve was established to evaluate the predictive efficiency of the model.At the same time,the clinical data of 46 TBI patients admitted to our hospital from January to December 2019 were collected as a validation set to verify the accuracy of the prediction model.Results Among 108 patients,there were 73 patients in the good prognosis group and 35 patients in the poor prognosis group.The severity of the disease,combined hypoxemia,Rotterdam CT score,and coagulation function indicators(PT,APTT,D-D)in the poor prognosis group were higher than those in the good prognosis group,with statistical significance(P<0.05).Logistic regression analysis showed that disease condition,Rotterdam CT score,PT,and D-D were independent influencing factors for poor prognosis in TBI patients(P<0.05).The predictive model for poor prognosis of TBI is Y=3.078×Rotterdam score CT score-0.847×PT+1.211×D-1.672×severity severity of the disease-3.195.The prediction model predicted poor prognosis with 0.886 sensitivity,0.836 specificity,0.722 Jorden index,0.262 cut-off value and 0.937 area under curve.The Hanley&McNeil method was used to compare the predictive model and the validation curve,and it was found that there was no statistically significant difference in the AUC comparison of the ROC curves between the two models(P<0.05).Conclusion For patients with TBI,the prediction model based on Rotterdam CT score and coagulation function has good accuracy and is worthy of promotion.