Wang Yating, Guo Junshuang, Yang Fan, Dong Ruirui, Song Dandan, Huang Peipei, Wen Lijun, Xiang Guoliang, Wang Shuiyu, Teng Junfang, Miao Wang
Neuro-Intensive Care Unit of the First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, China.
Department of Immunology, School of Basic Medical Science, Central South University, Changsha, Hunan, China.
Front Neurol. 2023 Jun 9;14:1118282. doi: 10.3389/fneur.2023.1118282. eCollection 2023.
The purpose of this research was to evaluate the influence of immunity on infection in patients with severe hemorrhagic stroke and explore the mechanism underlying this connection.
Clinical data obtained from 126 patients with severe hemorrhagic stroke were retrospectively analyzed, and the factors affecting infection were screened by multivariable logistic regression models. Nomograms, calibration curves, the Hosmer-Lemeshow goodness-of-fit test, and decision curve analysis were used to examine the effectiveness of the models in evaluating infection. The mechanism underlying the reduction in CD4 T-cell levels in blood was explored by analysis of lymphocyte subsets and cytokines in cerebrospinal fluid (CSF) and blood.
The results showed that CD4 T-cell levels of <300/μL was an independent risk factor for early infection. The models for multivariable logistic regression involving the CD4 T-cell levels and other influencing factors had good applicability and effectiveness in evaluating early infection. CD4 T-cell levels decreased in blood but increased in CSF. Similarly, interleukin (IL)-6 and IL-8 levels in CSF had a significant increase, generating a substantial concentration gradient between the CSF and the blood.
Reduced blood CD4 T-cell counts among patients who had severe hemorrhagic stroke increased the risk of early infection. CSF IL-6 and IL-8 may be involved in inducing the migration of CD4 T cells into the CSF and decreasing blood CD4 T-cell levels.
本研究旨在评估免疫对重症出血性脑卒中患者感染的影响,并探讨这种关联背后的机制。
回顾性分析126例重症出血性脑卒中患者的临床资料,采用多变量逻辑回归模型筛选影响感染的因素。使用列线图、校准曲线、Hosmer-Lemeshow拟合优度检验和决策曲线分析来检验模型在评估感染方面的有效性。通过分析脑脊液(CSF)和血液中的淋巴细胞亚群及细胞因子,探讨血液中CD4 T细胞水平降低的机制。
结果显示,血液中CD4 T细胞水平<300/μL是早期感染的独立危险因素。涉及CD4 T细胞水平及其他影响因素的多变量逻辑回归模型在评估早期感染方面具有良好的适用性和有效性。血液中CD4 T细胞水平降低,但脑脊液中升高。同样,脑脊液中的白细胞介素(IL)-6和IL-8水平显著升高,在脑脊液和血液之间形成了显著的浓度梯度。
重症出血性脑卒中患者血液中CD4 T细胞计数降低增加了早期感染的风险。脑脊液IL-6和IL-8可能参与诱导CD4 T细胞迁移至脑脊液并降低血液中CD4 T细胞水平。