Classifying migraine subtypes and their characteristics by latent class analysis using data of a nation-wide population-based study
Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical symptoms. We aimed to identify natural subgroups of migraine based on symptoms listed in the diagnostic criteria of the third edition of the International...
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Published in: | Scientific reports Vol. 11; no. 1; p. 21595 |
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Abstract | Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical symptoms. We aimed to identify natural subgroups of migraine based on symptoms listed in the diagnostic criteria of the third edition of the International Classification of Headache Disorders. Latent class analysis (LCA) was applied to the data of the Korean Sleep-Headache Study, a nationwide population-based survey. We selected a three-class model based on Akaike and Bayesian information criteria and characterized the three identified classes as “mild and low frequency,” “photophobia and phonophobia,” and “severe and high frequency.” In total, 52.0% (65/125) of the participants were classified as “mild and low frequency,” showing the highest frequency of mild headache intensity but the lowest overall headache frequency. Meanwhile, “photophobia and phonophobia” involved 33.6% (42/125) of the participants, who showed the highest frequency of photophobia and phonophobia. Finally, “severe and high frequency” included 14.4% (18/125) of the participants, and they presented the highest frequency of severe headache intensity and highest headache frequency. In conclusion, LCA is useful for analyzing the heterogeneity of migraine symptoms and identifying migraine subtypes. This approach may improve our understanding of the clinical characterization of migraine. |
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AbstractList | Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical symptoms. We aimed to identify natural subgroups of migraine based on symptoms listed in the diagnostic criteria of the third edition of the International Classification of Headache Disorders. Latent class analysis (LCA) was applied to the data of the Korean Sleep-Headache Study, a nationwide population-based survey. We selected a three-class model based on Akaike and Bayesian information criteria and characterized the three identified classes as "mild and low frequency," "photophobia and phonophobia," and "severe and high frequency." In total, 52.0% (65/125) of the participants were classified as "mild and low frequency," showing the highest frequency of mild headache intensity but the lowest overall headache frequency. Meanwhile, "photophobia and phonophobia" involved 33.6% (42/125) of the participants, who showed the highest frequency of photophobia and phonophobia. Finally, "severe and high frequency" included 14.4% (18/125) of the participants, and they presented the highest frequency of severe headache intensity and highest headache frequency. In conclusion, LCA is useful for analyzing the heterogeneity of migraine symptoms and identifying migraine subtypes. This approach may improve our understanding of the clinical characterization of migraine. Abstract Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical symptoms. We aimed to identify natural subgroups of migraine based on symptoms listed in the diagnostic criteria of the third edition of the International Classification of Headache Disorders. Latent class analysis (LCA) was applied to the data of the Korean Sleep-Headache Study, a nationwide population-based survey. We selected a three-class model based on Akaike and Bayesian information criteria and characterized the three identified classes as “mild and low frequency,” “photophobia and phonophobia,” and “severe and high frequency.” In total, 52.0% (65/125) of the participants were classified as “mild and low frequency,” showing the highest frequency of mild headache intensity but the lowest overall headache frequency. Meanwhile, “photophobia and phonophobia” involved 33.6% (42/125) of the participants, who showed the highest frequency of photophobia and phonophobia. Finally, “severe and high frequency” included 14.4% (18/125) of the participants, and they presented the highest frequency of severe headache intensity and highest headache frequency. In conclusion, LCA is useful for analyzing the heterogeneity of migraine symptoms and identifying migraine subtypes. This approach may improve our understanding of the clinical characterization of migraine. |
ArticleNumber | 21595 |
Author | Chu, Min Kyung Yang, Kwang Ik Kim, Daeyoung Min, In Kyung Lee, Wonwoo Yun, Chang-Ho |
Author_xml | – sequence: 1 givenname: Wonwoo surname: Lee fullname: Lee, Wonwoo organization: Department of Neurology, Severance Hospital, Yonsei University College of Medicine – sequence: 2 givenname: In Kyung surname: Min fullname: Min, In Kyung organization: Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine – sequence: 3 givenname: Kwang Ik surname: Yang fullname: Yang, Kwang Ik organization: Department of Neurology, Soonchunhyang University College of Medicine, Cheonan Hospital – sequence: 4 givenname: Daeyoung surname: Kim fullname: Kim, Daeyoung organization: Department of Neurology, Chungnam National University Hospital – sequence: 5 givenname: Chang-Ho surname: Yun fullname: Yun, Chang-Ho organization: Department of Neurology, Bundang Clinical Neuroscience Institute, Seoul National University Bundang Hospital – sequence: 6 givenname: Min Kyung surname: Chu fullname: Chu, Min Kyung email: chumk@yonsei.ac.kr organization: Department of Neurology, Severance Hospital, Yonsei University College of Medicine |
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Snippet | Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical symptoms. We... Abstract Migraine neither presents with a definitive single symptom nor has a distinct biomarker; thus, its diagnosis is based on combinations of typical... |
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SubjectTerms | 692/617 692/617/375/1654 692/617/375/226 Adult Bayes Theorem Bayesian analysis Cross-Sectional Studies Female Headache Headache - classification Headache - diagnosis Headaches Heterogeneity Humanities and Social Sciences Humans Hyperacusis - complications Latent Class Analysis Male Middle Aged Migraine Migraine Disorders - classification Migraine Disorders - diagnosis multidisciplinary Neurology - standards Photophobia - complications Population studies Population-based studies Reference Values Republic of Korea Science Science (multidisciplinary) Sleep |
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Title | Classifying migraine subtypes and their characteristics by latent class analysis using data of a nation-wide population-based study |
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