BackgroundThe neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR) are biomarkers that may reflect inflammatory status in some immune-related diseases. This study aims to investigate the association of NLR and MLR with the severity and prognosis of autoimmune encephalitis (AE).MethodsA total of 199 patients diagnosed with AE in the First Affiliated Hospital of Zhengzhou University from October 2015 to October 2021 were retrospectively analyzed. The Clinical Assessment Scale for Autoimmune Encephalitis (CASE) and the modified Rankin Scale (mRS) were used to evaluate the severity of the patients at admission, and the patients were divided into mild group (CASE ≤ 4) and severe group (CASE ≥ 5) according to the CASE score. Poor prognosis was described as an mRS of 3 or more at 12 months. Binary logistic regression analysis was performed to assess risk factors for the severity and prognosis of AE.ResultsNLR and MLR of severe group were significantly higher than that of mild group. NLR and MLR were positively correlated with the CASE score (r = 0.659, P < 0.001; r = 0.533, P < 0.001) and the mRS score (r = 0.609, P < 0.001;r = 0.478, P < 0.001) in AE patients. Multivariate logistic analysis showed that NLR (OR = 1.475, 95%CI: 1.211-1.796, P < 0.001) and MLR (OR = 15.228, 95%CI: 1.654-140.232, P = 0.016) were independent risk factors for the severity of AE. In addition, the CASE score and the mRS score were positively correlated (r = 0.849, P < 0.001). Multivariate logistic analysis showed that the CASE at admission (OR = 1.133, 95%CI: 1.043-1.229, P = 0.003) and age (OR = 1.105, 95%CI: 1.062-1.150, P < 0.001) were independent risk factors for the poor prognosis of AE patients. The NLR and MLR at admission and whether they decreased after immunotherapy were not associated with the prognosis of AE patients (P > 0.05).ConclusionsNLR and MLR, readily available and widespread inflammatory markers, were helpful for clinicians to monitor disease progression and identify potentially severe patients of AE early to optimize clinical treatment decisions.