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中华神经创伤外科电子杂志 ›› 2021, Vol. 07 ›› Issue (02) : 75 -81. doi: 10.3877/cma.j.issn.2095-9141.2021.02.003

所属专题: 文献

颅脑创伤

颅脑外伤后无瞳孔散大患者行去骨瓣减压术后的早期结果及出院死亡率的预后相关因素分析
田润发1, 董金千1, 刘伟明1, 卢盛华1, 杨梦石1, 张斌1, 高飞1, 庄园1, 葛芊芊1, 徐晓健1, 牛非1, 刘佰运1,()   
  1. 1. 100070 北京市神经外科研究所中枢神经系统损伤研究北京市重点实验室和首都医科大学附属北京天坛医院神经外科
  • 收稿日期:2021-01-25 出版日期:2021-04-15
  • 通信作者: 刘佰运
  • 基金资助:
    国家自然科学基金(81801225,81771328)

Prognostic predictors of early outcome and discharge mortality in traumatic brain injury patients without fixed dilated pupil that underwent decompressive craniectomy treatment

Runfa Tian1, Jinqian Dong1, Weiming Liu1, Shenghua Lu1, Mengshi Yang1, Bin Zhang1, Fei Gao1, Yuan Zhuang1, Qianqian Ge1, Xiaojian Xu1, Fei Niu1, Baiyun Liu1,()   

  1. 1. Beijing Key Laboratory of Central Nervous System Injury and Department of Neurosurgery, Beijing Neurosurgical Institute and Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, China
  • Received:2021-01-25 Published:2021-04-15
  • Corresponding author: Baiyun Liu
引用本文:

田润发, 董金千, 刘伟明, 卢盛华, 杨梦石, 张斌, 高飞, 庄园, 葛芊芊, 徐晓健, 牛非, 刘佰运. 颅脑外伤后无瞳孔散大患者行去骨瓣减压术后的早期结果及出院死亡率的预后相关因素分析[J]. 中华神经创伤外科电子杂志, 2021, 07(02): 75-81.

Runfa Tian, Jinqian Dong, Weiming Liu, Shenghua Lu, Mengshi Yang, Bin Zhang, Fei Gao, Yuan Zhuang, Qianqian Ge, Xiaojian Xu, Fei Niu, Baiyun Liu. Prognostic predictors of early outcome and discharge mortality in traumatic brain injury patients without fixed dilated pupil that underwent decompressive craniectomy treatment[J]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2021, 07(02): 75-81.

目的

分析影响无瞳孔散大创伤性脑损伤(TBI)患者行去骨瓣减压术(DC)治疗的早期结果和出院死亡率的相关因素。

方法

回顾性分析自2011年7月至2017年6月于首都医科大学附属北京天坛医院神经外科接受DC治疗的167例无瞳孔散大的TBI患者,并对其进行了评估(13个变量)。通过单因素和多因素分析,寻找独立预测因子,建立预后回归方程和受试者工作特征(ROC)曲线,以预测TBI后行DC治疗的早期结果和出院死亡率。

结果

对于无瞳孔散大且接受DC治疗的TBI患者,年龄越小(P=0.047)、入院GCS评分越高(P=0.001)且住院期间未行气管切开术(P<0.001)与早期预后良好相关,而年龄越小(P=0.031)、瞳孔对光反射越灵敏(P=0.008)及行单侧去骨瓣减压术(P=0.011)与较低的出院死亡率相关。ROC曲线预测早期预后良好的敏感性为86.7%,特异性为48.9%;预测较低的出院死亡率时的敏感性为81.3%,特异性为48.7%。

结论

年龄越小、入院GCS越高且未行气管切开术等因素可作为评估早期良好预后的独立预测因素,而年龄越小、瞳孔对光反射灵敏及行单侧去骨瓣减压术的无瞳孔散大且接受DC治疗的TBI患者其出院死亡率较低。初步建立的多元Logistic回归方程在临床实践中也可尝试用于预测早期预后和出院死亡率。

Objective

To determine independent predictors and develop multivariate logistic regression equations to predict early outcome and discharge mortality in traumatic brain injury (TBI) patients without fixed dilated pupil that undergoing decompressive craniectomy (DC) treatment.

Methods

All 167 TBI patients without fixed dilated pupil that undergoing DC treatment in Neurotrauma ward of Department of Neurosurgery, Beijing Tiantan Hospital Affiliated to Capital Medical University was retrospectively evaluated between July 2011 and June 2017, and a total of 13 different variables were evaluated. The independent predictors, prognostic regression scoring equations and receiver-operating characteristic (ROC) curves were then developed to predict early outcome and discharge mortality after TBI by univariate and multiple logistic regression analysis.

Results

For TBI patients without fixed dilated pupil that underwent DC treatment, younger age (P=0.047), higher admission GCS score (P=0.001) and without tracheotomy (P<0.001) were associated with favorable early outcome, while younger age (P=0.031), sensitive to light reflection (P=0.008) and unilateral craniectomy (P=0.011) were associated with lower discharge mortality. The sensitivity and specificity of ROC curve in predicting early prognosis were 86.7% and 48.9% respectively; The sensitivity and specificity were 81.3% and 48.7% respectively in predicting the lower discharge mortality after TBI.

Conclusion

Younger age, higher admission GCS and without tracheotomy can be used as independent predictors in assessing the favorable early outcome, while younger age, sensitive to light reflection and unilateral craniectomy were associated with lower discharge mortality for TBI patients without fixed dilated pupil that underwent DC treatment, and the derived multivariate logistic equations are also clinically useful for predicting early outcome and discharge mortality in daily practice.

表1 167例患者的临床资料
表2 术后出院早期预后影响因素的单因素分析
项目 预后良好(n=75) 预后差(n=92) t/χ2 P
年龄(岁,±s 43.6±14.1 54.2±15.6 <0.001 <0.001
入院GCS评分(分,±s 7.17±2.93 6.85±2.34 0.008 <0.001
Marshall CT分级(分,±s 4.00±1.58 4.36±1.56 0.143 0.143
性别[例(%)]     0.714 0.712
  13(41.9) 18(58.1)    
  62(45.6) 74(54.4)    
受伤机制[例(%)]     0.494 0.795
  跌倒 31(46.3) 36(53.7)    
  交通事故 33(41.2) 47(58.8)    
  暴力打击 11(55.0) 9(45.0)    
既往史[例(%)]     0.006 0.010
  健康 36(52.2) 33(47.8)    
  吸烟 14(66.7) 7(33.3)    
  高血压 8(40.0) 12(60.0)    
  口服阿司匹林 2(14.3) 12(85.7)    
  糖尿病 2(16.7) 10(83.3)    
  低纤维蛋白原血症 3(27.3) 8(72.7)    
  其他 10(50.0) 10(50.0)    
合并伤[例(%)]     0.321 0.507
  53(44.5) 66(55.5)    
  骨折 21(50.0) 21(50.0)    
  肺挫伤 1(33.3) 2(66.7)    
  其他 0(0) 3(100)    
瞳孔对光反射[例(%)]     <0.001 0.019
  灵敏 24(49.0) 25(51.0)    
  迟钝 41(54.7) 34(45.3)    
  消失 10(23.3) 33(76.7)    
气管切开[例(%)]     <0.001 <0.001
  6(11.8) 45(88.2)    
  69(59.5) 47(40.5)    
受伤到手术的时间间隔[例(%)]     0.222 0.954
  ≤6 h 20(47.6) 22(52.4)    
  7~24 h 30(40.5) 44(59.5)    
  >24 h 25(49.0) 26(51.0)    
手术方式[例(%)]     0.255 0.063
  单侧DC 63(48.8) 66(51.2)    
  双侧DC 12(31.6) 26(68.4)    
表3 预测出院预后评分影响因素的多元Logistic回归模型
表4 术后出院死亡率影响因素的单因素分析
项目 存活(n=128) 死亡(n=39) t/χ2 P
年龄(岁,±s 47.3±15.5 56.4±15.3 0.002 0.002
入院GCS评分(分,±s 6.35±1.46 4.77±1.39 0.006 0.007
Marshall CT评分(分,±s 4.05±1.57 4.67±1.51 0.032 0.035
性别[例(%)]     0.417 0.409
  22(71.0) 9(29.0)    
  106(77.9) 30(22.1)    
受伤机制[例(%)]     0.869 0.995
  跌倒 52(77.6) 15(22.4)    
  交通事故 60(75.0) 20(25.0)    
  暴力打击 16(80.0) 4(20.0)    
既往史[例(%)]     0.074 0.194
  健康 54(78.3) 15(21.7)    
  吸烟 18(85.7) 3(14.3)    
  高血压 18(90.0) 2(10.0)    
  口服阿司匹林 8(57.1) 6(42.9)    
  糖尿病 9(75.0) 3(25.0)    
  低纤维蛋白原血症 5(45.5) 6(54.5)    
  其他 16(80.0) 4(20.0)    
合并伤[例(%)]     0.935 0.836
  91(76.5) 28(23.5)    
  骨折 33(78.6) 9(21.4)    
  肺挫伤 2(66.7) 1(33.3)    
  其他 2(66.7) 1(33.3)    
瞳孔对光反射[例(%)]     0.001 0.001
  灵敏 42(85.7) 7(14.3)    
  迟钝 62(82.7) 13(17.3)    
  消失 24(55.8) 19(44.2)    
气管切开[例(%)]     0.528 0.408
  37(72.5) 14(27.5)    
  91(78.4) 25(21.6)    
受伤到手术的时间间隔[例(%)]     0.482 0.888
  ≤6 h 34(81.0) 8(19.0)    
  7~24 h 52(70.3) 22(29.7)    
  >24 h 42(82.4) 9(17.6)    
手术方式[例(%)]     0.031 0.028
  单侧DC 104(80.6) 25(19.4)    
  双侧DC 24(63.2) 14(36.8)    
表5 多元Logistic回归模型预测出院死亡率
图1 预后良好和较低出院死亡率的受试者工作特征曲线
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