ArticleHeliyon2024
Mapping the global research landscape and trends of autoimmune encephalitis: A bibliometric analysis.
Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Global trends and research hotspots in autoimmune encephalitis: insights from a bibliometric and visualized analysis: 1971-2025.Frontiers in immunology · 2026Pooled it
- In Children,Open forum infectious diseases · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Autoimmune encephalitis (AE) is a neuroautoimmune disease featured by the presence of antibodies targeting neuronal surface, synaptic, or intracellular antigens. An increasing number of articles on its clinical manifestations, treatments, and prognosis have appeared in recent years. The objectives of this study were to summarize this growing body of literature and provide an overview of hotspots and trends in AE research using bibliometric analysis. Methods: We retrieved AE-related articles published between 1999 and 2022 from the Web of Science Core Collection. Using bibliometric websites and software, we analyzed the data of AE research, including details about countries, institutions, authors, references, journals, and keywords. Results: We analyzed 3348 articles, with an average of 32.83 citations per article and an H-index of 141. The USA (1091, 32.587%), China (531, 15.860%), Germany (447, 13.351%), England (266, 7.945%), and Japan (213, 6.362%) had the greatest numbers of publications. The top five institutions by numbers of publications were Oxford (143, 4.271%), the Udice French Research Universities (135, 4.032%), the University of Pennsylvania (135, 4.032%), l'Institut National de la Sante de la Recherche Medicale Inserm (113, 3.375%), and the University of Barcelona (110, 3.286%). The most productive authors were J. Dalmau (98, 2.927%), A. Vincent (65, 2.479%), H. Pruess (64, 1.912%), C. G. Bien (43, 1.284%), and F. Graus (43, 1.284%). "autoimmune encephalitis" was the most frequently used keyword (430), followed by "antibodies" (420), "NMDA receptor encephalitis" (383), and "limbic encephalitis" (368). In recent years, research hotspots have focused on the diagnosis and immunotherapy of NMDAR encephalitis and on limbic encephalitis. Conclusion: Developed Western countries have made significant contributions to this field. China has shown a steady increase in the number of publications in recent years, but the quality and influence of these articles warrant efforts at improvement. Future directions in AE research lie in two key areas: (i) the clinical manifestations, prevalence, and prognosis of AE (enabled by advances in diagnosis); and (ii) the efficacy and safety of targeted, individualized immunotherapy.
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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.