ArticleCNS neuroscience & therapeutics2021
Recognition of seizure semiology and semiquantitative FDG-PET analysis of anti-LGI1 encephalitis.
Article in CNS neuroscience & therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed.
- Article
- Article
- Comparison ofEuropean journal of nuclear medicine and molecular imaging · 2025Article
- Clinical, Electroencephalogram and Imaging Characteristics of Patients With Anti-LGI1 Antibody Encephalitis: A Multicenter Cohort Study.CNS neuroscience & therapeutics · 2025Article
- Movement disorders in autoimmune encephalitis: an update.Journal of neurology · 2023Review
- Comparison of quantitative FDG-PET and MRI in anti-LGI1 autoimmune encephalitis.Neuroradiology · 2023Article
- Brain Metabolic Alterations in Seropositive Autoimmune Encephalitis: AnBiomedicines · 2023Article
- Article
- Recognition of seizure semiology and semiquantitative FDG-PET analysis of anti-LGI1 encephalitis.CNS neuroscience & therapeutics · 2021Article
- Subcortical Hypermetabolism Associated With Cortical Hypometabolism Is a Common Metabolic Pattern in Patients With Anti-Leucine-Rich Glioma-Inactivated 1 Antibody Encephalitis.Frontiers in immunology · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
aimsAnti-leucine-rich glioma-inactivated 1 (LGI1) autoimmune encephalitis (AE) is characterized by complex manifestations of seizures. Here, we report a new seizure semiology, attempt to classify the disease by semiology type, and explore the metabolic pattern of each group.
methodsAnti-LGI1 AE patients were retrospectively screened between May 2014 and September 2019 in our tertiary epilepsy center. All enrolled patients had seizures during long-range video electroencephalogram (EEG) recordings, and all patients (except one) underwent [
resultsThirty-three patients were enrolled. According to the patients' seizure semiology, we divided the patients into four groups: focal impaired awareness seizures (FIAS, n = 17), faciobrachial dystonic seizures (FBDS)-only (n = 6), FBDS-plus (n = 8), and focal aware motor seizures (FAMS) (n = 2). No significant differences were found in the clinical manifestations or accessory tests except for the onset age (FIAS < FBDS-plus) and seizure semiology. This was the first study to extensively describe the clinical manifestations and EEG of FAMS in anti-LGI1 AE patients. In addition, we found that the patients with different semiologies all showed a wide range of abnormal metabolism, which is not limited to the temporal regions and basal ganglia, and extends far beyond our previous interpretation of FDG-PET data.
conclusionOur results showed that FAMS can serve as a rare indicative seizure semiology of anti-LGI1 AE and that individuals with this disease exhibited widespread functional network alterations.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.