Department of Neurology, Jiangxi Provincial People's Hospital Affiliated to Nanchang University, Nanchang, China.
Department of Prenatal Diagnosis, Jiangxi Maternal and Child Health Hospital, Nanchang, China.
Front Cell Infect Microbiol. 2020 Jan 17;9:448. doi: 10.3389/fcimb.2019.00448. eCollection 2019.
The discrimination of tuberculous meningitis and bacterial meningitis remains difficult at present, even with the introduction of advanced diagnostic tools. This study aims to differentiate these two kinds of meningitis by using the rule of clinical and laboratory features. A prospective observational study was conducted to collect the clinical and laboratory parameters of patients with tuberculous meningitis or bacterial meningitis. Logistic regression was used to define the diagnostic formula for the discrimination of tuberculous meningitis and bacterial meningitis. A receiver operator characteristic curve was established to determine the best cutoff point for the diagnostic formula. Five parameters (duration of illness, coughing for two or more weeks, meningeal signs, blood sodium, and percentage of neutrophils in cerebrospinal fluid) were predictive of tuberculous meningitis. The diagnostic formula developed from these parameters was 98% sensitive and 82% specific, while these were 95% sensitive and 91% specific when prospectively applied to another 70 patients. The diagnostic formula developed in the present study can help physicians to differentiate tuberculous meningitis from bacterial meningitis in high-tuberculosis-incidence-areas, particularly in settings with limited microbiological and radiological resources.
目前,即使引入了先进的诊断工具,结核性脑膜炎和细菌性脑膜炎的鉴别仍然很困难。本研究旨在通过临床和实验室特征的规律来区分这两种脑膜炎。一项前瞻性观察性研究收集了结核性脑膜炎或细菌性脑膜炎患者的临床和实验室参数。使用逻辑回归来确定鉴别结核性脑膜炎和细菌性脑膜炎的诊断公式。建立受试者工作特征曲线以确定诊断公式的最佳截断点。五个参数(病程、咳嗽两周或更长时间、脑膜征、血钠和脑脊液中性粒细胞百分比)可预测结核性脑膜炎。从这些参数中开发的诊断公式的敏感性为 98%,特异性为 82%,当前瞻性应用于另外 70 名患者时,敏感性为 95%,特异性为 91%。本研究中开发的诊断公式可帮助医生在高结核发病率地区,特别是在微生物学和影像学资源有限的环境中,将结核性脑膜炎与细菌性脑膜炎区分开来。