Mentis Alexios-Fotios A, Garcia Irene, Jiménez Juan, Paparoupa Maria, Xirogianni Athanasia, Papandreou Anastasia, Tzanakaki Georgina
National Meningitis Reference Laboratory, Department of Public Health Policy, School of Public Health, University of West Attica, 122 43 Athens, Greece.
Department of Mathematical Sciences and Informatics, and Health Research Institute (IdISBa), University of the Balearic Islands (UIB), 07122 Palma, Balearic Islands, Spain.
Diagnostics (Basel). 2021 Mar 28;11(4):602. doi: 10.3390/diagnostics11040602.
Differential diagnosis between bacterial and viral meningitis is crucial. In our study, to differentiate bacterial vs. viral meningitis, three machine learning (ML) algorithms (multiple logistic regression (MLR), random forest (RF), and naïve-Bayes (NB)) were applied for the two age groups (0-14 and >14 years) of patients with meningitis by both conventional (culture) and molecular (PCR) methods. Cerebrospinal fluid (CSF) neutrophils, CSF lymphocytes, neutrophil-to-lymphocyte ratio (NLR), blood albumin, blood C-reactive protein (CRP), glucose, blood soluble urokinase-type plasminogen activator receptor (suPAR), and CSF lymphocytes-to-blood CRP ratio (LCR) were used as predictors for the ML algorithms. The performance of the ML algorithms was evaluated through a cross-validation procedure, and optimal predictions of the type of meningitis were above 95% for viral and 78% for bacterial meningitis. Overall, MLR and RF yielded the best performance when using CSF neutrophils, CSF lymphocytes, NLR, albumin, glucose, gender, and CRP. Also, our results reconfirm the high diagnostic accuracy of NLR in the differential diagnosis between bacterial and viral meningitis.
鉴别细菌性脑膜炎和病毒性脑膜炎至关重要。在我们的研究中，为了区分细菌性脑膜炎和病毒性脑膜炎，通过传统（培养）和分子（PCR）方法，对两个年龄组（0 - 14岁和>14岁）的脑膜炎患者应用了三种机器学习（ML）算法（多元逻辑回归（MLR）、随机森林（RF）和朴素贝叶斯（NB））。脑脊液（CSF）中性粒细胞、CSF淋巴细胞、中性粒细胞与淋巴细胞比值（NLR）、血白蛋白、血C反应蛋白（CRP）、葡萄糖、血可溶性尿激酶型纤溶酶原激活剂受体（suPAR）以及CSF淋巴细胞与血CRP比值（LCR）被用作ML算法的预测指标。通过交叉验证程序评估ML算法的性能，对于病毒性脑膜炎，脑膜炎类型的最佳预测准确率高于95%，对于细菌性脑膜炎则为78%。总体而言，当使用CSF中性粒细胞、CSF淋巴细胞、NLR、白蛋白、葡萄糖、性别和CRP时，MLR和RF表现最佳。此外，我们的结果再次证实了NLR在细菌性脑膜炎和病毒性脑膜炎鉴别诊断中的高诊断准确性。
