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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 ›› 2021, Vol. 07 ›› Issue (05) : 266 -270. doi: 10.3877/cma.j.issn.2095-9141.2021.05.003

临床研究

NLR与PLR及联合指标预测创伤性颅脑损伤预后的临床价值及预后模型的构建
陈昊阳1, 冯雷2,†()   
  1. 1. 471000　洛阳，河南科技大学第一附属医院重症医学科
    2. 272000　济宁市第一人民医院神经外科
  • 收稿日期:2020-11-20 出版日期:2021-10-15
  • 通信作者: 冯雷

Clinical value of NLR, PLR and their combined indicators in predicting the prognosis of traumatic brain injury and the construction of prognostic model

Haoyang Chen1, Lei Feng2,†()   

  1. 1. Department of Critical Medicine, The First Affiliated Hospital of He’nan University of Science and Technology, Luoyang 471000, China
    2. Department of Neurosurgery, Jining First People’s Hospital, Jining 272000, China
  • Received:2020-11-20 Published:2021-10-15
  • Corresponding author: Lei Feng
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陈昊阳, 冯雷. NLR与PLR及联合指标预测创伤性颅脑损伤预后的临床价值及预后模型的构建[J/OL]. 中华神经创伤外科电子杂志, 2021, 07(05): 266-270.

Haoyang Chen, Lei Feng. Clinical value of NLR, PLR and their combined indicators in predicting the prognosis of traumatic brain injury and the construction of prognostic model[J/OL]. Chinese Journal of Neurotraumatic Surgery(Electronic Edition), 2021, 07(05): 266-270.

目的

研究创伤性颅脑损伤（TBI）患者生化及炎症指标的变化，探讨外周血中性粒细胞-淋巴细胞比值（NLR）和血小板-淋巴细胞比值（PLR）对患者预后的预测价值。

方法

回顾性分析济宁市第一人民医院神经外科自2019年1月至2020年1月收治的132例TBI患者的一般资料。根据患者伤后6个月的GOS评分分为预后良好组（91例）和预后不良组（41例）。比较2组患者的NLR和PLR，采用多因素Logistic回归分析影响TBI预后不良的独立危险因素，并构建预后模型，运用受试者工作特征曲线（ROC）分析NLR和PLR单独、联合指标以及各组预后模型对患者预后的预测价值。

结果

2组患者的NLR、PLR比较差异均有统计学意义（P<0.05）。多因素Logistic回归分析显示年龄、入院GCS评分、NLR以及PLR是TBI患者伤后6个月预后不良的独立危险因素（P<0.05）。根据本研究所得的独立危险因素构建患者预后模型，模型1：年龄+GCS评分；模型2：年龄+GCS评分+NLR；模型3：年龄+GCS评分+PLR；模型4：年龄+GCS评分+NLR+PLR。ROC曲线分析后显示各模型的曲线下面积（AUC）分别为：0.685、0.822、0.671、0.864。其中模型4的AUC最大，表明其预测准确度最高。

结论

NLR、PLR单独及联合指标对于TBI患者的预后均有一定的预测价值，NLR、PLR值越大，TBI患者6个月预后不良可能性越大，NLR、PLR结合患者年龄和GCS评分共同预测患者预后时准确度显著提升。

关键词: 创伤性颅脑损伤, 中性粒细胞-淋巴细胞比值, 血小板-淋巴细胞比值, 预后
Objective

To study the changes of biochemical and inflammatory indicators in patients with traumatic brain injury (TBI), and to explore the predictive value of peripheral blood neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR) on prognosis of patients.

Methods

The general data of 132 patients with TBI admitted to Neurosurgery Department of Jining First People’s Hospital from January 2019 to January 2020 were analyzed retrospectively. According to the GOS score 6 months after injury, the patients were divided into good prognosis group (91 cases) and poor prognosis group (41 cases). The general clinical data and laboratory examination indicators were collected to analyze whether there were any differences in NLR and PLR between the two groups. Multivariate logistic regression was used to analyze the independent risk factors affecting the poor prognosis of TBI. The prognosis model was constructed, and the predictive value of NLR and PLR alone and combined indicators on the prognosis of patients was obtained by receiver operating characteristic curve (ROC) analysis.

Results

There were significant differences in NLR and PLR between the two groups (P<0.05). Multivariate regression analysis showed that age, admission GCS score, NLR and PLR were independent risk factors for poor prognosis at 6 months after injury in TBI patients (P<0.05). According to the independent risk factors obtained in this study, the patient prognosis model was constructed. Model 1: age+GCS score; Model 2: age+GCS score+NLR; Model 3: age+GCS score+PLR; Model 4: age+GCS score+NLR. The ROC curve analysis showed that the area under curve (AUC) of each model were 0.685, 0.822, 0.671 and 0.864 respectively. The AUC of model 4 is the largest, which indicates that the prediction accuracy of model 4 is the highest.

Conclusion

NLR, PLR and their combined indicators have certain predictive value for the prognosis of TBI patients. The greater the NLR and PLR values, the greater the possibility of poor prognosis in 6 months of TBI patients. The accuracy of NLR, PLR combined with age and GCS score in predicting the prognosis of TBI patients is significantly improved.

Key words: Traumatic brain injury, Neutrophil to lymphocyte ratio, Platelet to lymphocyte ratio, Prognosis
表1 2组患者的一般临床资料比较
项目 预后良好组（n=91） 预后不良组（n=41） χ2/t值 P值
性别[例（%）]     0.644 0.422
  男 62（68.1） 25（61.0）    
  女 29（31.9） 16（39.0）    
年龄（岁，±s） 51.21±14.45 59.44±12.29 2.932 0.004
冠心病史[例（%）] 11（12.1） 8（19.5） 1.264 0.261
糖尿病史[例（%）] 10（11.0） 8（19.5） 1.744 0.187
高血压史[例（%）] 19（20.9） 13（31.7） 1.427 0.232
入院时GCS评分（分，±s） 10.89±2.14 7.29±2.65 7.645 <0.001
入院时收缩压（mmHg，±s） 135.67±16.82 140.37±21.32 1.246 0.217
入院时舒张压（mmHg，±s） 84.31±13.19 82.73±12.27 0.649 0.518
瞳孔对光反射迟钝[例（%）] 16（17.6） 26（63.4） 27.368 <0.001
入院血糖（mmol/L，±s） 7.62±1.56 9.53±1.94 6.013 <0.001
纤维蛋白原（g/L，±s） 2.37±0.67 2.23±0.55 1.112 0.269
部分活化凝血酶时间（s，±s） 25.16±3.44 25.35±4.57 0.234 0.816
表2 2组患者的血常规、NLR及PLR比较
组别 例数 血常规（×109/L） NLR PLR
WBC NE LY Plt
预后良好组 91 10.57（8.16，15.58） 8.48（5.59，13.57） 1.58（1.25，1.99） 211（180，241） 5.52（3.42，8.65） 127.04（103.52，164.13）
预后不良组 41 15.25（11.14，20.52） 12.81（9.64，17.42） 0.77（0.44，0.98） 174（155，238） 18.45（11.42，27.24） 255.88（182.04，401.79）
Z值   3.851 4.155 7.692 1.226 8.190 7.035
P值   <0.001 <0.001 <0.001 0.168 <0.001 <0.001
表3 影响颅脑损伤患者预后的多因素Logistic分析
变量 回归系数 标准误 Wald χ2值 OR值 95%CI
入院GCS评分 -0.885 0.271 10.686 0.421 0.243~0.701
NLR 0.293 0.110 7.095 1.335 1.081~1.664
PLR 0.023 0.009 7.210 1.021 1.006~1.041
年龄 0.089 0.043 4.370 1.087 1.006~1.189
图1 与颅脑损伤预后不良相关的指标构建预后模型的ROC分析
表4 不同模型预测颅脑损伤患者伤后6个月预后的ROC结果
指标 曲线下面积 约登指数 敏感度（%） 特异度（%） 95%CI P值
模型1 0.685 0.361 53.7 82.4 0.581~0.789 <0.001
模型2 0.822 0.511 61.0 90.1 0.744~0.901 <0.001
模型3 0.671 0.317 53.1 78.0 0.566~0.777 <0.001
模型4 0.864 0.630 70.7 92.3 0.795~0.932 <0.001
[1]
Iaccarino C, Carretta A, Nicolosi F, et al. Epidemiology of severe traumatic brain injury[J]. J Neurosurg Sci, 2018, 62(5): 535-541.
[2]
Hazeldine J, Hampson P, Lord JM. The impact of trauma on neutrophil function[J]. Injury, 2014, 45(12): 1824-1833.
[3]
Osler T, Cook A, Glance LG, et al. The differential mortality of Glasgow coma score in patients with and without head injury[J]. Injury, 2016, 47(9): 1879-1885.
[4]
靳佳敏,马翠红,范昆鹏,等.血浆NLR、PLR及其联合指标对脑梗死溶栓患者预后的预测价值[J].临床荟萃, 2020, 35(3): 228-232.
[5]
黎开宇,钟晖东,张海冰,等.术前中性粒细胞与淋巴细胞比值对重度颅脑外伤预后的预测价值[J].海南医学, 2018, 29(13): 1814-1817.
[6]
Büki A, Barzó P, Demeter B, et al. Guidelines for the treatment of traumatic brain injury-2017[J]. Ideggyogy Sz, 2017, 70(7-8): 223-245.
[7]
Karibe H, Hayashi T, Narisawa A, et al. Clinical characteristics and outcome in elderly patients with traumatic brain injury: for establishment of management strategy[J]. Neurol Med Chir (Tokyo), 2017, 57(8): 418-425.
[8]
Caterino JM, Raubenolt A, Cudnik MT. Modification of Glasgow coma scale criteria for injured elders[J]. Acad Emerg Med, 2011, 18(10): 1014-1021.
[9]
McIntyre A, Mehta S, Aubut J, et al. Mortality among older adults after a traumatic brain injury: a meta-analysis[J]. Brain Inj, 2013, 27(1): 31-40.
[10]
张小兵,高亮,吉宋泉,等.中性粒细胞-淋巴细胞比值在颅脑损伤预后评估中的作用[J].中国临床神经外科杂志, 2020, 25(7): 441-442, 446.
[11]
Sulhan S, Lyon KA, Shapiro LA, et al. Neuroinflammation and blood-brain barrier disruption following traumatic brain injury: Pathophysiology and potential therapeutic targets[J]. J Neurosci Res, 2020, 98(1): 19-28.
[12]
Nguyen HX, O’Barr TJ, Anderson AJ. Polymorphonuclear leukocytes promote neurotoxicity through release of matrix metalloproteinases, reactive oxygen species, and TNF-alpha[J]. J Neurochem, 2007, 102(3): 900-912.
[13]
Roth TL, Nayak D, Atanasijevic T, et al. Transcranial amelioration of inflammation and cell death after brain injury[J]. Nature, 2014, 505(7482): 223-228.
[14]
Hofstetter HH, Sewell DL, Liu F, et al. Autoreactive T cells promote post-traumatic healing in the central nervous system[J]. J Neuroimmunol, 2003, 134(1-2): 25-34.
[15]
Schwartz M, Moalem G. Beneficial immune activity after CNS injury: prospects for vaccination[J]. J Neuroimmunol, 2001, 113(2): 185-192.
[16]
Lattanzi S, Brigo F, Trinka E, et al. Neutrophil-to-lymphocyte ratio in acute cerebral hemorrhage: a system review[J]. Transl Stroke Res, 2019, 10(2): 137-145.
[17]
Ploplis VA, Donahue DL, Sandoval-Cooper MJ, et al. Systemic platelet dysfunction is the result of local dysregulated coagulation and platelet activation in the brain in a rat model of isolated traumatic brain injury[J]. J Neurotrauma, 2014, 31(19): 1672-1675.
[18]
Nekludov M, Bellander BM, Blombäck M, et al. Platelet dysfunction in patients with severe traumatic brain injury[J]. J Neurotrauma, 2007, 24(11): 1699-1706.
[19]
Yuan Q, Yu J, Wu X, et al. Prognostic value of coagulation tests for in-hospital mortality in patients with traumatic brain injury[J]. Scand J Trauma Resusc Emerg Med, 2018, 26(1): 3.
[20]
Dijkland SA, Foks KA, Polinder S, et al. Prognosis in moderate and severe traumatic brain injury: a systematic review of contemporary models and validation studies[J]. J Neurotrauma, 2020, 37(1): 1-13.
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