Analysis of Risk Factors for a Poor Prognosis in Patients with Anti- N -Methyl-D-Aspartate Receptor Encephalitis and Construction of a Prognostic Composite Score

Yejia Mo, Li Wang, Libo Zhu, Feng Li, Gang Yu, Yetao Luo, Meng Ni
Journal of Clinical Neurology 2020, 16 (3): 438-447

BACKGROUND AND PURPOSE: Anti- N -methyl-D-aspartate receptor (NMDAR) encephalitis is the most-common form of autoimmune encephalitis, but its early diagnosis is challenging. This study aimed to identify the risk factors for a poor prognosis in anti-NMDAR encephalitis and construct a prognostic composite score for obtaining earlier predictions of a poor prognosis.

METHODS: We retrospectively analyzed the clinical data, laboratory indexes, imaging findings, and electroencephalogram (EEG) data of 60 patients with anti-NMDAR encephalitis. The modified Rankin Scale (mRS) scores of patients were collected when they were discharged from the hospital. The mRS scores were used to divide the patients into two groups, with mRS scores of 3-6 defined as a poor prognosis. Logistic regression analysis was used to analyze independent risk factors related to a poor prognosis.

RESULTS: This study found that 23 (38.3%) and 37 (61.7%) patients had good and poor prognoses, respectively. Logistic regression analysis showed that age, disturbance of consciousness at admission, and ≥50% slow waves on the EEG were significantly associated with patient outcomes. An age, consciousness, and slow waves (ACS) composite score was constructed to predict the prognosis of patients with anti-NMDAR encephalitis at an early stage based on regression coefficients.

CONCLUSIONS: Age, disturbance of consciousness at admission, and ≥50% slow waves on the EEG were independent risk factors for a poor prognosis. The ACS prognostic composite score could play a role in facilitating early predictions of the prognosis of anti-NMDAR encephalitis.

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