Amsterdam UMC, University of Amsterdam, Department of Neurology, Amsterdam Neuroscience, Meibergdreef 9, Amsterdam, the Netherlands.
Amsterdam UMC, University of Amsterdam, Department of Epidemiology and Data Science, Amsterdam, the Netherlands.
J Infect. 2024 Mar;88(3):106117. doi: 10.1016/j.jinf.2024.01.016. Epub 2024 Feb 5.
We aimed to determine diagnostic accuracy of inflammatory markers in plasma and cerebrospinal fluid (CSF) for the diagnosis of central nervous system (CNS) infections and specifically bacterial meningitis.
We analyzed 12 cytokines, chemokines, and acute phase reactants in CSF and plasma of 738 patients with suspected neurological infection included in a multicenter prospective cohort. We determined diagnostic accuracy for predicting any CNS infection and bacterial meningitis.
We included 738 episodes between 2017 and 2022, split into a derivation (n = 450) and validation cohort (n = 288). Of these patients, 224 (30%) were diagnosed with CNS infection, of which 81 (11%) with bacterial meningitis, 107 (14%) with viral meningitis or encephalitis, and 35 patients (5%) with another CNS infection. Diagnostic accuracy of CRP, IL-6, and Il-1β in CSF was high, especially for diagnosing bacterial meningitis. Combining these biomarkers in a multivariable model increased accuracy and provided excellent discrimination between bacterial meningitis and all other disorders (AUC = 0.99), outperforming all individual biomarkers as well as CSF leukocytes (AUC = 0.97). When applied to the population of patients with a CSF leukocyte count of 5-1000 cells/mm, accuracy of the model also provided a high diagnostic accuracy (AUC model = 0.97 vs. AUC CSF leukocytes = 0.80) with 100% sensitivity and 92% specificity. These results remained robust in a temporal validation cohort.
Inflammatory biomarkers in CSF are able to differentiate CNS infections and especially bacterial meningitis from other disorders. When these biomarkers are combined, their diagnostic accuracy exceeds that of CSF leukocytes alone and as such these markers have added value to current clinical practice.
我们旨在确定血浆和脑脊液（CSF）中炎症标志物对中枢神经系统（CNS）感染，特别是细菌性脑膜炎的诊断准确性。
我们分析了纳入多中心前瞻性队列的 738 例疑似神经感染患者的 CSF 和血浆中的 12 种细胞因子、趋化因子和急性期反应物。我们确定了预测任何 CNS 感染和细菌性脑膜炎的诊断准确性。
我们纳入了 2017 年至 2022 年期间的 738 例发作，分为推导队列（n=450）和验证队列（n=288）。这些患者中，224 例（30%）被诊断为 CNS 感染，其中 81 例（11%）为细菌性脑膜炎，107 例（14%）为病毒性脑膜炎或脑炎，35 例（5%）为其他 CNS 感染。CSF 中 CRP、IL-6 和 Il-1β 的诊断准确性较高，尤其是对细菌性脑膜炎的诊断。将这些生物标志物组合在多变量模型中可提高准确性，并提供细菌性脑膜炎与所有其他疾病之间的出色鉴别能力（AUC=0.99），优于所有单个生物标志物和 CSF 白细胞（AUC=0.97）。当应用于 CSF 白细胞计数为 5-1000 个/mm 的患者人群时，该模型的准确性也提供了高诊断准确性（AUC 模型=0.97 与 AUC CSF 白细胞=0.80），具有 100%的敏感性和 92%的特异性。这些结果在时间验证队列中仍然稳健。
CSF 中的炎症标志物能够区分 CNS 感染，特别是细菌性脑膜炎与其他疾病。当这些生物标志物组合使用时，其诊断准确性超过单独使用 CSF 白细胞，因此这些标志物对当前的临床实践具有附加价值。
