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中华神经创伤外科电子杂志

中华神经创伤外科电子杂志 ›› 2023, Vol. 09 ›› Issue (06) : 343 -349. doi: 10.3877/cma.j.issn.2095-9141.2023.06.005

临床研究

凝血指标对中型创伤性脑损伤患者进展性出血性损伤的预测能力
王如海†(), 曹祥记, 王绅, 张敏, 韩超, 于强, 胡海成, 李习珍   
  1. 236000　阜阳，阜阳师范大学附属第二医院神经外科
    315336　宁波市杭州湾医院神经外科
    236112　阜阳，安徽医科大学附属阜阳医院检验科
  • 收稿日期:2023-02-14 出版日期:2023-12-15
  • 通信作者: 王如海

Predictive ability of coagulation tests for progressive hemorrhagic injury in patients with moderate traumatic brain injury

Ruhai Wang†(), Xiangji Cao, Shen Wang, Min Zhang, Chao Han, Qiang Yu, Haicheng Hu, Xizhen Li   

  1. Department of Neurosurgery, the Second Affiliated Hospital of Fuyang Normal University, Fuyang 236000, China
    Department of Neurosurgery, Ningbo Hangzhou Bay Hospital, Ningbo 315336, China
    Department of Clinical Laboratory, Fuyang Hospital of Anhui Medical University, Fuyang 236112, China
  • Received:2023-02-14 Published:2023-12-15
  • Corresponding author: Ruhai Wang
  • Supported by:
    Foundation of Fuyang Health Commission(FY2021-081, FY2023-019)
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王如海, 曹祥记, 王绅, 张敏, 韩超, 于强, 胡海成, 李习珍. 凝血指标对中型创伤性脑损伤患者进展性出血性损伤的预测能力[J]. 中华神经创伤外科电子杂志, 2023, 09(06): 343-349.

Ruhai Wang, Xiangji Cao, Shen Wang, Min Zhang, Chao Han, Qiang Yu, Haicheng Hu, Xizhen Li. Predictive ability of coagulation tests for progressive hemorrhagic injury in patients with moderate traumatic brain injury[J]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2023, 09(06): 343-349.

目的

探讨凝血指标对中型创伤性脑损伤（mTBI）患者进展性出血性损伤（PHI）的预测价值。

方法

回顾性分析2018年1月至2023年6月阜阳师范大学附属第二医院神经外科收治的270例mTBI患者的临床资料。根据mTBI患者伤后72 h内是否发生PHI将患者分为PHI组和非PHI组。根据是否纳入凝血指标分别构建3个PHI预测模型：模型1包括mTBI患者一般资料及影像学资料等标准变量；模型2基于模型1标准变量基础上添加凝血指标；模型3仅包括凝血指标。通过单因素及多因素Logistic回归分析，评估mTBI患者发生PHI的独立影响因素。使用受试者特征工作（ROC）曲线及曲线下面积（AUC）评价不同预测模型对PHI的预测能力。使用bootstrap法对预测模型进行内部验证。

结果

270例mTBI患者中，43例发生PHI，PHI发生率为15.9%。PHI组与非PHI组首次CT扫描时间、入院GCS评分、颅骨骨折、创伤性脑内血肿、创伤性硬膜外血肿、纤维蛋白原（FIB）、D-二聚体比较，差异有统计学意义（P<0.05）。多因素Logistic回归分析显示，首次CT扫描时间、入院GCS评分、创伤性脑内血肿、FIB、D-二聚体是PHI发生的独立影响因素。3种预测模型对比显示，模型2（AUC=0.908，95%CI：0.868~0.940）较模型1（AUC=0.848，95%CI：0.800~0.889）和模型3（AUC=0.805，95%CI：0.752~0.850）具有更好的预测能力。

结论

凝血指标作为mTBI患者发生PHI的独立影响因素，对PHI具有较好的预测能力。

关键词: 凝血指标, 中型创伤性脑损伤, 进展性出血性损伤, 预测能力
Objective

To explore the predictive ability of coagulation tests for progressive hemorrhagic injury (PHI) in patients with moderate traumatic brain injury (mTBI).

Methods

Clinical data of 270 patients with mTBI admitted to Neurosurgery Department of the Second Affiliated Hospital of Fuyang Normal University from January 2018 to June 2023 were retrospectively analyzed. The mTBI patients were divided into PHI group and non-PHI group deponding on whether PHI occurred within 72 h after injury. Three prediction models for PHI were constructed according to whether coagulation tests was included. Model 1 included standard variables such as general data and imaging data of mTBI patients; Model 2 added coagulation tests based on standard variable of model one; Model 3 included only coagulation indicators. Independent influencing factors for PHI in mTBI patients were revealed by univariate and multivariate Logistic regression analysis. Receiver operating characteristic (ROC) curve and area under curve (AUC) were used to evaluate the ability of different predictive models for PHI. Internal validation of the prediction models was used by bootstrap analysis.

Results

Among 270 mTBI patients, 43 cases developed PHI, and the incidence of PHI was 15.9%. There was statistically significant difference in the first CT scan time, GCS score on admission, skull fracture, traumatic intracerebral hematoma, traumatic epidural hematoma, fibrinogen (FIB) and D-dimer between the two groups (P<0.05). Multivariate Logistic regression analysis showed that the first CT scan time, GCS score on admission, traumatic intracerebral hematoma, FIB, D-dimer were independent risk factors for PHI. Comparison of 3 prediction models showed that Model 2 (AUC=0.908, 95%CI: 0.868-0.940) has better predictive ability than Model 1 (AUC=0.848, 95%CI: 0.800-0.889) and Model 3 (AUC=0.805, 95%CI: 0.752-0.850).

Conclusion

As an independent influencing factor for PHI in patients with mTBI, coagulation tests has a good ability to predict the occurrence of PHI.

Key words: Coagulation tests, Moderate traumatic brain injury, Progressive hemorrhagic injury, Predictive ability
表1 mTBI患者临床特征及相关因素的比较
Tab.1 Comparison of clinical features and related factors in mTBI patients
项目 PHI组（n=43） 非PHI组（n=227） χ2/t/Z值 P值
性别[例（%）]     0.001 0.977
男 27（62.8） 142（62.6）    
女 16（37.2） 85（37.4）    
年龄（岁，±s） 59.7±13.7 59.0±14.8 0.281 0.779
致伤原因[例（%）]     0.146 0.930
交通伤 18（41.9） 97（42.7）    
摔跌 10（23.2） 47（20.7）    
其他 15（34.9） 83（36.6）    
基础疾病[例（%）]        
高血压 12（27.9） 62（27.3） 0.006 0.936
糖尿病 5（11.6） 29（12.8） 0.043 0.835
院前呕吐[例（%）] 33（76.7） 151（66.5） 1.741 0.187
首次CT扫描时间[h，M（Q1，Q3）] 1.0（0.8，2.0） 2.1（1.4，2.8） -6.616 <0.001
入院GCS评分（分，±s） 11.1±1.2 11.7±0.7 -3.202 0.002
创伤性脑损伤类型[例（%）]      
颅骨骨折 32（74.4） 125（55.31） 5.564 0.018
颅底骨折 11（25.6） 68（30.0） 0.334 0.563
脑挫伤 40（93.0） 208（91.6） 0.094 0.759
创伤性硬膜外血肿 15（34.9） 37（16.3） 8.029 0.005
创伤性硬膜下血肿 37（86.0） 165（72.7） 3.424 0.064
创伤性脑内血肿 15（34.9） 28（12.3） 13.728 <0.001
创伤性蛛网膜下腔出血 38（88.4） 205（90.3） 0.151 0.698
实验室检查指标[M（Q1，Q3）]      
血小板计数（×109/L） 187.0（143.0，242.0） 183.0（152.0，223.0） -0.075 0.941
血清总钙浓度（mmol/L） 2.2（2.1，2.3） 2.2（2.1，2.3） -0.649 0.516
TT（s） 16.8（15.4，18.8） 16.9（15.3，18.3） -0.453 0.651
PT（s） 12.0（11.0，13.3） 11.7（11.0，12.4） -1.801 0.072
INR 1.0（1.0，1.1） 1.0（0.9，1.1） -1.802 0.072
APTT（s） 25.2（22.9，31.2） 25.0（23.0，27.5） -1.237 0.216
FIB（g/L） 2.1（1.6，2.6） 2.8（2.3，3.3） -4.967 <0.001
D-二聚体（mg/L） 17.4（7.8，45.2） 4.8（2.1，11.8） -5.394 <0.001
表2 mTBI患者PHI的多因素Logistic回归分析
Tab.2 Multivariate Logistic regression analysis of PHI in mTBI patients
因素 回归系数 标准误 Wald's χ2 OR值 95%CI P值
首次CT扫描时间 -1.575 0.423 13.849 0.207 0.090~0.474 <0.001
入院GCS评分 -0.614 0.267 5.303 0.541 0.321~0.913 0.021
颅骨骨折 -0.608 0.531 1.313 0.544 0.192~1.541 0.252
创伤性脑内血肿 -1.886 0.664 8.079 0.152 0.041~0.557 0.004
创伤性硬膜外血肿 -0.804 0.551 3.131 0.448 0.152~1.317 0.144
FIB -1.502 0.384 15.311 0.223 0.105~0.472 <0.001
D-二聚体 0.038 0.012 10.340 1.039 1.015~1.064 0.001
图1 影响因素对mTBI患者发生PHI预测能力的ROC曲线分析
Fig.1 ROC curve analysis of the predictive value of influencing factors on the occurrence of PHI in mTBI patients
表3 影响因素预测PHI的ROC曲线结果
Tab.3 ROC curve results for predicting PHI based on influencing factors
因素 曲线下面积 截断值 灵敏度（%） 特异度（%） 95%CI P值
首次CT扫描时间（h） 0.818 2.0 95.3 53.7 0.766~0.862 <0.001
入院GCS评分（分） 0.623 10.0 34.9 92.5 0.563~0.681 0.018
创伤性脑内血肿 0.613 - 34.9 87.7 0.552~0.671 0.026
纤维蛋白原（g/L） 0.739 2.4 69.8 69.2 0.682~0.790 <0.001
D-二聚体（mg/L） 0.760 10.4 67.4 74.4 0.704~0.809 <0.001
图2 3个预测模型对PHI预测能力的ROC曲线分析
Fig.2 ROC curve analysis of three prediction models for the prediction ability of PHI
图3 3种预测模型对PHI的预测验证结果A：模型1；B：模型2；C：模型3
Fig.3 Verification results of three prediction models for PHI prediction
表4 3个预测模型的ROC曲线结果
Tab.4 ROC curve results of three prediction models
因素 曲线下面积 敏感度（%） 特异度（%） 95%CI P值
模型1 0.848 72.1 85.5 0.800~0.889 <0.001
模型2 0.908 88.4 78.4 0.868~0.940 <0.001
模型3 0.805 67.4 84.6 0.752~0.850 <0.001
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