인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Objective This study aimed to explore the clinical characteristics and temporal disease course of patients with autoimmune encephalitis (AE) and paraneoplastic neurological syndrome (PNS) in Sweden. Methods Thirty‐seven antibody‐positive AE and PNS cases were identified in the Healthcare region Mid Sweden between 2015 and 2019. Clinical data were collected through a retrospective review of electronic health records. Patients were divided into three subgroups based on antibody type: neuronal surface antibodies (NSAbs), onconeural antibodies, and anti‐GAD65 antibodies. Results Nineteen patients had NSAbs, 11 onconeural antibodies, and seven anti‐GAD65 antibodies. Anti‐LGI1 and anti‐NMDAR were the most frequently detected NSAbs, with anti‐NMDAR cases having an older‐than‐expected age distribution (median age 40, range 17–72). Only 11 of 32 (30%) of patients had findings suggesting encephalitis on initial MRI, but 28 of 31 (90%) had pathological findings on initial cerebrospinal fluid analysis. All patients but one had abnormal EEG findings. Median time to immunotherapy was comparable among the three subgroups, whereas patients with anti‐LGI1, anti‐CASPR2, and anti‐IgLON5 had an eightfold longer time to immunotherapy than anti‐NMDAR and anti‐GABA‐B ( p = .0016). There was a seasonal variation in onset for patients with non‐tumor‐related NSAbs and anti‐GAD65 antibodies, with most patients (72%) falling ill in spring or summer. Conclusion Swedish patients with AE and PNS had similar clinical characteristics as previously described cohorts from other geographical regions except for anti‐NMDAR encephalitis, with older onset than expected. The onset of non‐tumor‐related AE occurred predominantly in the warm seasons, and AE with a more insidious onset was associated with delayed treatment initiation.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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