创伤性颅脑损伤患者预后评估与预测:伤情特征、生物标志物及临床工具的研究进展与挑战
Prognostic Assessment and Prediction in Patients with Traumatic Brain Injury: Research Progress and Challenges in Injury Characteristics, Biomarkers, and Clinical Tools
摘要: 创伤性颅脑损伤(TBI)的预后评估亟需多模态指标协同优化。本文叙述性综述表明:1) 伤情特征中,动态格拉斯哥昏迷评分(GCS)、Rotterdam CT评分(>3分时死亡率增加40%)及弥散张量成像各向异性分数(DTI-FA,胼胝体FA < 0.6预示认知障碍)构成预后分层基础;2) 生物标志物方面,胶质纤维酸性蛋白(GFAP,AUC = 0.82预测颅内病变)与泛素C末端水解酶-L1 (UCH-L1,高值者死亡风险增加2.5倍)主导神经损伤评估,而中性粒细胞/白蛋白比值(NAR)作为新兴炎症标志物,显著提升死亡风险识别效能(NAR > 5.2时死亡风险增加3.1倍,P < 0.01);3) 临床工具中,IMPACT模型整合NAR后曲线下面积(AUC)提升至0.91 (ΔAUC = +0.07)。当前挑战集中于NAR阈值年龄依赖性、低白蛋白血症干扰及多模态临床整合不足,未来需构建“伤情–神经损伤–炎症监测”动态框架,推动NAR指导的靶向干预。
Abstract: The prognosis assessment of traumatic brain injury (TBI) is in urgent need of collaborative optimization of multimodal indicators. This systematic review shows that: 1) Among the injury characteristics, the dynamic Glasgow Coma Scale (GCS), Rotterdam CT score (a score > 3 is associated with a 40% increase in mortality), and fractional anisotropy from diffusion tensor imaging (DTI-FA, with corpus callosum FA < 0.6 predicting cognitive impairment) form the basis for prognostic stratification; 2) In terms of biomarkers, glial fibrillary acidic protein (GFAP, with an AUC of 0.82 for predicting intracranial lesions) and ubiquitin C-terminal hydrolase-L1 (UCH-L1, with high values associated with a 2.5-fold increase in the risk of death) dominate the assessment of neurological injury. Additionally, the neutrophil/albumin ratio (NAR), as an emerging inflammatory marker, significantly enhances the ability to identify death risk (a NAR > 5.2 is associated with a 3.1-fold increase in death risk, P < 0.01); 3) Among clinical tools, the area under the curve (AUC) of the IMPACT model increased to 0.91 (ΔAUC = +0.07) after integrating NAR. Current challenges focus on the age dependence of the NAR threshold, interference from hypoalbuminemia, and insufficient clinical integration of multimodal data. In the future, it is necessary to construct a dynamic framework of “injury condition - neurological injury - inflammation monitoring” to promote NAR-guided targeted interventions.
文章引用:石泊. 创伤性颅脑损伤患者预后评估与预测:伤情特征、生物标志物及临床工具的研究进展与挑战[J]. 临床医学进展, 2025, 15(9): 923-927. https://doi.org/10.12677/acm.2025.1592574

参考文献

[1] Karamian, A., Lucke-Wold, B. and Seifi, A. (2024) Prevalence of Traumatic Brain Injury in the General Adult Population of the USA: A Meta-Analysis. Neuroepidemiology, 1-10. [Google Scholar] [CrossRef] [PubMed]
[2] Komboz, F., Chehade, H.D., Al Saffar, B., Mielke, D., Rohde, V. and Abboud, T. (2024) Assessing Outcomes in Traumatic Brain Injury: Helsinki Score versus Glasgow Coma Scale. European Journal of Trauma and Emergency Surgery, 50, 2491-2499. [Google Scholar] [CrossRef] [PubMed]
[3] Li, Y., Wang, H., Liu, Z., Deng, Z., Huang, K., Li, G., et al. (2024) Neutrophil-Albumin Ratio Serves as a Superior Prognostic Biomarker for Traumatic Brain Injury. Scientific Reports, 14, Article No. 27563. [Google Scholar] [CrossRef] [PubMed]
[4] Jalali, R., Bałuch, M., Malinowska, J., Zwiernik, J., Kern, A., Bil, J., et al. (2025) GFAP/UCH-L1 as a Biomarker for Rapid Assessment of Mild TBI in Emergency Departments. Medical Science Monitor, 31, e948353. [Google Scholar] [CrossRef] [PubMed]
[5] Kang, X., Grossner, E., Yoon, B.C. and Adamson, M.M. (2025) Relationship between Structural and Functional Network Connectivity Changes for Patients with Traumatic Brain Injury and Chronic Health Symptoms. European Journal of Neuroscience, 61, e16678. [Google Scholar] [CrossRef] [PubMed]
[6] Patil, S., Subtirelu, R., Teichner, E., Kata, R., Gerlach, A., Ayubcha, C., et al. (2025) CT, MRI, and PET Imaging in Patients with Traumatic Brain Injury. PET Clinics, 20, 133-145. [Google Scholar] [CrossRef] [PubMed]
[7] Alivar, A., Saleh, S., Glassen, M., Suviseshamuthu, E.S., Handiru, V.S., Allexandre, D., et al. (2025) Correlations between Morpho-Structural Properties of the Brain and Cognitive and Motor Deficits in Individuals with Traumatic Brain Injury. Neurotrauma Reports, 6, 68-81. [Google Scholar] [CrossRef] [PubMed]
[8] Clarke, G.J.B., Follestad, T., Skandsen, T., Zetterberg, H., Vik, A., Blennow, K., et al. (2024) Chronic Immunosuppression across 12 Months and High Ability of Acute and Subacute CNS-Injury Biomarker Concentrations to Identify Individuals with Complicated mTBI on Acute CT and MRI. Journal of Neuroinflammation, 21, Article No. 109. [Google Scholar] [CrossRef] [PubMed]
[9] Helmrich, I.R.A.R., Czeiter, E., Amrein, K., Büki, A., Lingsma, H.F., Menon, D.K., et al. (2022) Incremental Prognostic Value of Acute Serum Biomarkers for Functional Outcome after Traumatic Brain Injury (CENTER-TBI): An Observational Cohort Study. The Lancet Neurology, 21, 792-802. [Google Scholar] [CrossRef] [PubMed]
[10] Okada, Y., Nakasone, H., Yoshimura, K., Tamaki, M., Kusuda, M., Nakamura, Y., et al. (2023) Plasma Ubiquitin C-Terminal Hydrolase-L1 (UCH-L1) Level as a Blood Biomarker of Neurological Damage after Allogeneic Hematopoietic Cell Transplantation. International Journal of Hematology, 118, 340-346. [Google Scholar] [CrossRef] [PubMed]
[11] Gugger, J.J., Walter, A.E., Parker, D., Sinha, N., Morrison, J., Ware, J., et al. (2023) Longitudinal Abnormalities in White Matter Extracellular Free Water Volume Fraction and Neuropsychological Functioning in Patients with Traumatic Brain Injury. Journal of Neurotrauma, 40, 683-692. [Google Scholar] [CrossRef] [PubMed]
[12] Shi, G., Liu, L., Cao, Y., Ma, G., Zhu, Y., Xu, J., et al. (2023) Inhibition of Neutrophil Extracellular Trap Formation Ameliorates Neuroinflammation and Neuronal Apoptosis via STING-Dependent IRE1α/ASK1/JNK Signaling Pathway in Mice with Traumatic Brain Injury. Journal of Neuroinflammation, 20, Article No. 222. [Google Scholar] [CrossRef] [PubMed]
[13] Cao, Y., Shi, M., Liu, L., Zuo, Y., Jia, H., Min, X., et al. (2023) Inhibition of Neutrophil Extracellular Trap Formation Attenuates NLRP1-Dependent Neuronal Pyroptosis via STING/IRE1α Pathway after Traumatic Brain Injury in Mice. Frontiers in Immunology, 14, Article ID: 1125759. [Google Scholar] [CrossRef] [PubMed]
[14] Shi, G., Cao, Y., Xu, J., Chen, B., Zhang, X., Zhu, Y., et al. (2025) Inhibition of S100A8/A9 Ameliorates Neuroinflammation by Blocking NET Formation Following Traumatic Brain Injury. Redox Biology, 81, Article ID: 103532. [Google Scholar] [CrossRef] [PubMed]
[15] van Erp, I.A.M., Michailidou, I., van Essen, T.A., van der Jagt, M., Moojen, W., Peul, W.C., et al. (2023) Tackling Neuroinflammation after Traumatic Brain Injury: Complement Inhibition as a Therapy for Secondary Injury. Neurotherapeutics, 20, 284-303. [Google Scholar] [CrossRef] [PubMed]
[16] Bergold, P. and Lawless, S. (2022) Better Together? Treating Traumatic Brain Injury with Minocycline plus N-acetylcysteine. Neural Regeneration Research, 17, 2589-2592. [Google Scholar] [CrossRef] [PubMed]
[17] Liu, B., Xu, X., Ge, Q., Yang, M., Zhuang, Y., Zhang, B., et al. (2023) Neutrophil-Derived Interleukin-17a Participates in Neuroinflammation Induced by Traumatic Brain Injury. Neural Regeneration Research, 18, 1046-1051. [Google Scholar] [CrossRef] [PubMed]
[18] Yang, Z., Wang, L., Hong, B., He, Z., Zhang, Q., Shen, T., et al. (2025) Inflammatory Burden Index as a Predictor of In‐hospital Mortality in Patients with Severe Fever with Thrombocytopenia Syndrome. Journal of Medical Virology, 97, e70225. [Google Scholar] [CrossRef] [PubMed]
[19] Tang, Y., Hou, H., Li, L., Yong, L., Zhang, S., Yan, L., et al. (2022) Neutrophil Percentage-to-Albumin Ratio: A Good Parameter for the Evaluation of the Severity of Anti-NMDAR Encephalitis at Admission and Prediction of Short-Term Prognosis. Frontiers in Immunology, 13, Article ID: 847200. [Google Scholar] [CrossRef] [PubMed]
[20] Zhang, D., Zhuang, D., Li, T., Liu, X., Zhang, Z., Zhu, L., et al. (2024) An Analysis of Neutrophil-to-Lymphocyte Ratios and Monocyte-to-Lymphocyte Ratios with Six-Month Prognosis after Cerebral Contusions. Frontiers in Immunology, 15, Article ID: 1336862. [Google Scholar] [CrossRef] [PubMed]
[21] Tanrıkulu, A.B., Kaya, H. and Çatak, Z. (2025) Comparative Analysis of Inflammatory Biomarkers in Methamphetamine-Associated Psychosis and Schizophrenia. Progress in Neuro-Psychopharmacology and Biological Psychiatry, 139, Article ID: 111404. [Google Scholar] [CrossRef] [PubMed]
[22] Xie, H., Wei, L., Ruan, G., Zhang, H., Shi, J., Lin, S., et al. (2024) AWGC2023 Cachexia Consensus as a Valuable Tool for Predicting Prognosis and Burden in Chinese Patients with Cancer. Journal of Cachexia, Sarcopenia and Muscle, 15, 2084-2093. [Google Scholar] [CrossRef] [PubMed]
[23] Yao, J., Xu, X., Gong, K., Tu, H., Xu, Z., Ye, S., et al. (2023) Prognostic Value of Neutrophil Count to Albumin Ratio in Patients with Decompensated Cirrhosis. Scientific Reports, 13, Article No. 20759. [Google Scholar] [CrossRef] [PubMed]