4.4 Article

Prediction of neutrophil-to-lymphocyte ratio in the diagnosis and progression of autoimmune encephalitis

期刊

NEUROSCIENCE LETTERS
卷 694, 期 -, 页码 129-135

出版社

ELSEVIER IRELAND LTD
DOI: 10.1016/j.neulet.2018.12.003

关键词

Neutrophil-to-lymphocyte ratio; Autoimmune encephalitis; Disease progression; New predictor; Biomarker

资金

  1. National Natural Science Foundation of China [81671183]

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Objective: Autoimmune encephalitis (AIE) is a group of inflammatory disorders of the brain. The severity of AIE vary among individuals and it is always a challenge to predict. In this study, we measured the neutrophil-to-lymphocyte ratio (NLR), a novel potential biomarker of inflammatory status in other inflammatory diseases, in ME patients and evaluated NLR as a biomarker for monitoring AIE progression. Methods: The study participants consisted of 34 newly diagnosed AIE patients and 35 ages and sex-matched healthy controls. Demographic and clinical assessment data were reviewed and abstracted retrospectively. NLR levels were calculated from the peripheral blood tests. The relationship between mRS (the modified Ranking Scale) score and NLR levels, total white blood cells, absolute neutrophil counts and absolute lymphocyte counts were investigated. The performance of NLR in predicting severe AIE was also determined. Results: Peripheral NLR level in AIE patients were significantly higher than in healthy controls (p < 0.001). Additionally, median NLR level in patients with severe impairments (using modified Ranking Scale, mRS > 3) was significantly elevated (p < 0.001) compared to patients with mild to moderate impairments (mRS <= 3). Spearman correlation analysis indicated that NLR and neutrophil counts were positively associated to mRS score (r = 0.595, p < 0.001 for NLR, and r = 0.392, p = 0.022 for neutrophil counts). While lymphocyte counts were negatively correlated with mRS score (r = - 0.522, p = 0.002). Multivariate logistic regression analysis revealed that increased NLR value was an independent risk factor for severe AIE (OR: 2.171, 95% CI: 1.218-3.868, p = 0.009). Furthermore, according to the ROC curve, the best NLR cut-off value to predict severe disease activity of AIE was 4.82, with a sensitivity of 78% and specificity of 88%. Conclusion: Our results suggest that NLR in peripheral blood may be a practical and reliable biomarker to monitor disease progression in patients with AIE.

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