Serum neuron-specific enolase can predict the severity and outcome of anti-N-methyl-D-aspartate receptor encephalitis

IF 3.2 3区 医学 Q2 MEDICAL LABORATORY TECHNOLOGY Clinica Chimica Acta Pub Date : 2024-09-06 DOI:10.1016/j.cca.2024.119962
Yinyao Lin , Haiyan Li , Enpeng Song , Zhengqi Lu , Yongqiang Dai , Bingjun Zhang
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Abstract

Background

Little is known about the association between serum neuron-specific enolase (NSE) concentration and anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis. This study aims to investigate if serum NSE concentration is related to the clinical features of anti-NMDAR encephalitis.

Methods

Serum NSE levels were detected in 58 anti-NMDAR encephalitis cases, 58 matched healthy controls and 58 matched disease controls. Demographic features, clinical symptoms, cerebrospinal fluid parameters and brain MRI indexes of the cases were evaluated.

Results

Serum NSE concentrations were significant higher in case group than those in healthy controls and disease controls (both p < 0.001). Serum NSE concentrations in patients with mRS≥3 one year after onset were obviously higher than in those with mRS<3 (p < 0.001). Patients with status epilepticus or central hypoventilation had higher serum NSE levels than those without (p = 0.003 and p = 0.006). Serum NSE concentrations in cases with brain lesions or brain atrophy were significant higher than in those without (p = 0.001 and p < 0.001, respectively). Serum NSE concentrations were found to be significant higher in cases with limited response to treatment compared to those with favourable therapy outcomes (p < 0.001). Spearman’s correlation analysis showed a significant positive association between serum NSE concentration and mRS score at the most critical time (max mRS) (r = 0.575, p < 0.001) and one year after onset (r = 0.705, p < 0.001). Cox regression results reflected that high serum NSE level was an independent predictor of poor prognosis in anti-NMDAR encephalitis group (p = 0.001), and the ROC curve threshold value was 15.72 ng/ml.

Conclusions

Serum NSE concentrations in anti-NMDAR encephalitis cases are higher than those in controls. It can be used to predict the brain damage degree and prognosis of anti-NMDAR encephalitis cases.

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血清神经元特异性烯醇化酶可预测抗 N-甲基-D-天冬氨酸受体脑炎的严重程度和预后。
背景:人们对血清神经元特异性烯醇化酶(NSE)浓度与抗N-甲基-D-天冬氨酸受体(NMDAR)脑炎之间的关系知之甚少。本研究旨在探讨血清 NSE 浓度是否与抗 NMDAR 脑炎的临床特征有关:方法:检测 58 例抗 NMDAR 脑炎病例、58 例匹配的健康对照组和 58 例匹配的疾病对照组的血清 NSE 水平。对病例的人口统计学特征、临床症状、脑脊液参数和脑磁共振成像指标进行评估:结果:病例组血清 NSE 浓度明显高于健康对照组和疾病对照组(均为 p):抗NMDAR脑炎病例的血清NSE浓度高于对照组。它可用于预测抗 NMDAR 脑炎病例的脑损伤程度和预后。
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来源期刊
Clinica Chimica Acta
Clinica Chimica Acta 医学-医学实验技术
CiteScore
10.10
自引率
2.00%
发文量
1268
审稿时长
23 days
期刊介绍: The Official Journal of the International Federation of Clinical Chemistry and Laboratory Medicine (IFCC) Clinica Chimica Acta is a high-quality journal which publishes original Research Communications in the field of clinical chemistry and laboratory medicine, defined as the diagnostic application of chemistry, biochemistry, immunochemistry, biochemical aspects of hematology, toxicology, and molecular biology to the study of human disease in body fluids and cells. The objective of the journal is to publish novel information leading to a better understanding of biological mechanisms of human diseases, their prevention, diagnosis, and patient management. Reports of an applied clinical character are also welcome. Papers concerned with normal metabolic processes or with constituents of normal cells or body fluids, such as reports of experimental or clinical studies in animals, are only considered when they are clearly and directly relevant to human disease. Evaluation of commercial products have a low priority for publication, unless they are novel or represent a technological breakthrough. Studies dealing with effects of drugs and natural products and studies dealing with the redox status in various diseases are not within the journal''s scope. Development and evaluation of novel analytical methodologies where applicable to diagnostic clinical chemistry and laboratory medicine, including point-of-care testing, and topics on laboratory management and informatics will also be considered. Studies focused on emerging diagnostic technologies and (big) data analysis procedures including digitalization, mobile Health, and artificial Intelligence applied to Laboratory Medicine are also of interest.
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