nav emailalert searchbtn searchbox tablepage yinyongbenwen piczone journalimg journalInfo journalinfonormal searchdiv searchzone qikanlogo popupnotification paper paperNew
2026, 05, v.20 22-26
老年中型颅脑创伤患者继发脑积水的风险预测模型
基金项目(Foundation): 陕西省创新人才推进计划-科技创新团队项目(2022TD-42)
邮箱(Email): sjwklixia@sina.com;
DOI:
发布时间: 2026-05-19
出版时间: 2026-05-19
移动端阅读
摘要:

目的 探讨老年中型颅脑创伤(mTBI)患者继发脑积水的风险因素并构建预测模型。方法 按8∶2随机分配比例,将空军军医大学西京医院神经外科2023年1月至2024年12月期间收治的256例老年mTBI患者分为模型组(204例)和验证组(52例)。利用模型组患者临床资料进行单因素分析、多因素Logistic回归分析,并构建预测模型。利用验证组数据进行模型效能检验,并通过受试者工作特征曲线评估模型的区分度与校准度。结果 256例患者中发生脑积水23例(8.98%)。单因素分析显示,入院拉斯哥昏迷程度(GCS)评分、硬膜下血肿、蛛网膜下腔出血、脑室积血、脑挫裂伤、颅内感染及腰椎穿刺脑脊液置换与老年mTBI继发脑积水发生相关(均P<0.05)。多因素Logistic回归分析表明,入院GCS评分<10分、存在硬膜下血肿、合并蛛网膜下腔出血、合并脑室积血和合并颅内感染是老年mTBI继发脑积水的危险因素,而进行腰椎穿刺脑脊液置换为其保护因素(均P<0.05)。据此建立预测模型:Z=-9.332+2.892×入院GCS评分<10分+2.573×存在硬膜下血肿+2.467×合并蛛网膜下腔出血+2.005×合并脑室积血+1.840×合并颅内感染-2.104×进行腰椎穿刺脑脊液置换。该模型受试者工作特征曲线下面积为0.942(95%CI:0.900~0.983),最大约登指数为0.745,对应最佳截断值为0.116,此时特异性为0.903,敏感度为0.842。HosmerLemeshow检验示χ2=0.695(P>0.05)。内部验证结果显示,模型特异性为0.917,敏感度为0.750,预测准确率为0.904。结论 入院GCS评分<10分、存在硬膜下血肿、合并蛛网膜下腔出血、合并脑室积血和合并颅内感染会增加老年mTBI患者脑积水的发生风险,而进行腰椎穿刺脑脊液置换治疗可降低该风险。基于上述因素构建的预测模型具有良好的效能,可为老年m TBI后脑积水的早期预防与识别提供参考。

Abstract:

Objective To explore the risk factors of secondary hydrocephalus in elderly patients with moderate traumatic brain injury(mTBI) and construct a prediction model. Methods 256 elderly mTBI patients admitted to the Department of Neurosurgery of Xijing Hospital from January 2023 to December 2024 were selected and divided into model group(n=204) and validation group(n=52) with a ratio of 8:2. The risk factors of post-traumatic hydrocephalus in model group were analyzed through univariate analysis and multivariate regression analysis. The hydrocephalus prediction model was evaluated by receiver operating characteristic(ROC) curve and were tested in validation group. Results Among the 256 patients, 23 occurred post-traumatic hydrocephalus during the following-up period(8.98%). Univariate analysis revealed that admission Glasgow coma scale(GCS), subdural hematomas, subarachnoid hemorrhage, intraventricular hemorrhage, cerebral contusion and laceration, intracranial infection, and lumbar puncture for cerebrospinal fluid replacement were associated with post-traumatic hydrocephalus in elderly mTBI patients. Logistic regression analysis showed that admission GCS<10, the presence of subdural hematomas, concomitant subarachnoid hemorrhage, intraventricular hemorrhage and intracranial infection were the risk factors of hydrocephalus, while lumbar puncture with cerebrospinal fluid replacement served as a protective factor for hydrocephalus(P<0.05). Base on these factors, the following prediction model was constructed: Z=-9.332+2.892×admission GCS<10 +2.573×the presence of subdural hematomas+2.467×concomitant subarachnoid hemorrhage+2.005× concomitant intraventricular hemorrhage+1.840×concomitant intracranial infection-2.104×lumbar puncture with cerebrospinal fluid replacement. The area under receiver operating characteristic curve was 0.942(95%CI: 0.900~0.983), with a maximum Youden index of 0.745. The corresponding optimal cut-off value was 0.116, yielding a specificity of 0.903 and a sensitivity of 0.842. The Chi square value of Hosmer-Lemeshow test was 0.695(P>0.05). The internal validation data showed that the prediction specificity, sensitivity and accuracy of the model were 0.750, 0.917 and 0.904 respectively. Conclusions Admission GCS< 10, presence of subdural hematomas, concomitant subarachnoid hemorrhage, intraventricular hemorrhage and intracranial infection increase the risk of hydrocephalus in elderly patients with mTBI, whereas lumbar puncture with cerebrospinal fluid replacement reduces the risk. The well-performing model can be used as an effective tool for early prevention and identification of hydrocephalus in elderly patients with mTBI.

参考文献

[1]Guo S, Han R, Chen F, et al. Epidemiological characteristics for patients with traumatic brain injury and the nomogram model for poor prognosis:An 18-year hospital-based study[J]. Front Neurol, 2023,14:1138217. DOI:10.3389/fneur.2023. 1138217.

[2]Lang L, Wang T, Xie L, et al. An independently validated nomogram for individualised estimation of short-term mortality risk among patients with severe traumatic brain injury:A modelling analysis of the center-tbi china registry study[J]. EClinicalMedicine, 2023, 59:101975. DOI:10.1016/j.eclinm.2023.101975.

[3]Kumaria A, Tolias CM. Post-traumatic hydrocephalus:Unknown knowns and known unknowns[J]. Br J Neurosurg, 2022, 36(3):295-297. DOI:10.1080/02688697. 2021.1979683.

[4]Rufus P, Moorthy RK, Joseph M, et al. Post traumatic hydrocephalus:Incidence, pathophysiology and outcomes[J]. Neurol India, 2021, 69:420-428. DOI:10.4103/0028-3886.313609.

[5]中华神经外科分会神经创伤专业组,中华创伤学会分会神经创伤专业组.颅脑创伤后脑积水诊治中国专家共识[J].中华神经外科杂志, 2014, 30(8):840-843. DOI:10.3760/cma.j.issn.1001-2346.2014.08.013.

[6]Kim JH, Ahn JH, Oh JK, et al. Factors associated with the development and outcome of hydrocephalus after decompressive craniectomy for traumatic brain injury[J]. Neurosurg Rev, 2021, 44(1):471-478.DOI:10.1007/s10143-020-01306-8.

[7]黄贤键,吴楚伟,邹隽风,等.创伤性脑损伤后脑积水发生的危险因素分析[J].中华创伤杂志, 2019, 35(3):216-220. DOI:10.3760/cma.j.issn.1001-8050.2019. 03.008.

[8]王宁.重型颅脑创伤患者去骨瓣减压术后发生脑积水的影响因素[J].贵州医科大学学报, 2023, 48(4):461-465. DOI:10.19367/j.cnki.1000-2707.2023.04.014.

[9]Jesuyajolu DA, Moti T, Zubair AA, et al. Factors associated with post traumatic hydrocephalus following decompressive craniectomy:A single-center experience[J]. Surg Neurol Int, 2023, 14:18. DOI:10.14748/sneuroint.v14i1.18.

[10]国务院第七次全国人口普查领导小组办公室. 2020年第七次全国人口复查主要数据[M].北京:中国统计出版社, 2021.

[11]Deng H, Goldschmidt E, Nwachuku E, et al. Hydrocephalus and cerebrospinal fluid analysis following severe traumatic brain injury:Evaluation of a prospective cohort[J]. Neurol Int, 2021, 13(4):527-534. DOI:10.4103/1678-2659.320092.

[12]Lindfors M, Vehviläinen J, Bendel S, et al. Incidence and risk factors of posttraumatic hydrocephalus and its association with outcome following intensive care unit treatment for traumatic brain injury:A multicenter observational study[J]. J Neurosurg, 2023, 139(5):1420-1429. DOI:10.3171/2022.10.JNS221703.

[13]Ved R, Fraser R, Hamadneh S, et al. Clinical features associated with the development of hydrocephalus following tbi in the paediatric age group[J]. Childs Nerv Syst, 2021, 37(2):511-517. DOI:10.1007/s00381-020-04915-3.

[14]Rumalla K, Letchuman V, Smith KA, et al. Hydrocephalus in pediatric traumatic brain injury:National incidence, risk factors, and outcomes in 124, 444 hospitalized patients[J]. Pediatr Neurol, 2018, 80:70-76. DOI:10.1016/j.pediatrneurol.2017.11.013.

[15]Goldschmidt E, Deng H, Puccio AM, et al. Post-traumatic hydrocephalus following decompressive hemicraniectomy:Incidence and risk factors in a prospective cohort of severe tbi patients[J]. J Clin Neurosci, 2020, 73:85-88. DOI:10.1016/j.jocn.2019. 12.013.

[16]Allred D. Management of medical complications during the rehabilitation of moderate-severe traumatic brain injury[J]. Phys Med Rehabil Clin N Am, 2024, 35(3):507-521. DOI:10.1016/j.pmr.2024.05.003.

[17]Chen Q, Feng Z, Tan Q, et al. Post-hemorrhagic hydrocephalus:Recent advances and new therapeutic insights[J]. J Neurol Sci, 2017,375:220-230. DOI:10.1016/j.jns. 2017.06.028.

[18]Xu H, Dong Y, Bao D, et al. Shunt-dependent post-traumatic hydrocephalus:Predictors and long-term functional outcomes[J]. Neurol Ther, 2023, 12(5):1607-1622. DOI:10.1007/s40120-023-00515-1.

[19]Hannah EM, Zyck S, Hazama A, et al. Scoping review of the risk factors and time frame for development of post-traumatic hydrocephalus[J]. Rev Neurosci, 2022, 33(2):133-146. DOI:10.1515/revneuro-2021-0119.

[20]Cava FC, Castellani GB, Maietti E, et al. A new clinical protocol for a timely diagnosis and treatment of hydrocephalus in patients with severe acquired brain injury[J]. Brain Sci, 2023, 13(7):1067. DOI:10.3390/brainsci13071067.

[21]Heinonen A, Rauhala M, Isokuortti H, et al. Incidence of surgically treated post-traumatic hydrocephalus 6 months following head injury in patients undergoing acute head computed tomography[J]. Acta Neurochir(Wien),2022, 164(9):2357-2365. DOI:10.1007/s00701-022-05299-3.

基本信息:

中图分类号:R651.15

引用信息:

[1]汪仁聪,郑新瑞,鲁传豪,等.老年中型颅脑创伤患者继发脑积水的风险预测模型[J].中华神经外科疾病研究杂志,2026,20(05):22-26.

基金信息:

陕西省创新人才推进计划-科技创新团队项目(2022TD-42)

发布时间:

2026-05-19

出版时间:

2026-05-19

检 索 高级检索

引用

GB/T 7714-2015 格式引文
MLA格式引文
APA格式引文