Validation of the NEOS score in Chinese patients with anti-NMDAR encephalitis.

Journal: Neurology(R) Neuroimmunology & Neuroinflammation
Published:
Abstract

Objective: The performance of anti-NMDAR Encephalitis One-Year Functional Status (NEOS) in predicting the 1-year functional status in Chinese patients with anti-NMDAR encephalitis is unknown.

Methods: We recruited patients with anti-NMDAR encephalitis from the Multicenter and Prospective Clinical Registry Study of Anti-NMDAR Encephalitis in Beijing Area. Patients were followed up for 1 year. We defined the poor functional status as a modified Rankin Scale score of more than 2 and good functional status as a modified Rankin Scale score of no more than 2. We performed a receiver-operator characteristic analysis to assess the discriminatory power of the NEOS score in predicting the 1-year functional status by using the area under the curve (AUC). Calibration was assessed by Pearson correlation coefficient and Hosmer-Lemeshow tests.

Results: Among the 111 patients with anti-NMDAR encephalitis recruited from 364 potentially eligible participants, 87 (78.4%) had good functional status at 1 year, whereas the remaining 24 (21.6%) had poor functional status. The AUC of the NEOS score for 1-year poor functional status was 0.86 (95% CI 0.78-0.93, p < 0.001). The increased NEOS was associated with higher risk of 1-year poor functional status in patients with anti-NMDAR encephalitis.

Conclusions: The NEOS score is considered a reliable predictor of the risk of 1-year poor functional status in Chinese patients with anti-NMDAR encephalitis. This score could help to estimate the velocity of clinical improvement in advance. Clinicaltrialgov identifier: NCT02443350. Classification of evidence: This study provides Class III evidence that in patients with anti-NMDAR encephalitis, the NEOS score predicts 1-year functional status.

Authors
Yujing Peng, Feifei Dai, Lei Liu, Weiqi Chen, Hongyi Yan, Aihua Liu, Xinghu Zhang, Xiaohui Wang, Junying He, Yatong Li, Chenxi Li, Liuxi Chen, Yan Zhao, Lin Li, Qiuying Ma, Jiawei Wang