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
Main Authors: Lee, Wonwoo, Min, In Kyung, Yang, Kwang Ik, Kim, Daeyoung, Yun, Chang-Ho, Chu, Min Kyung
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 03-11-2021
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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.
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
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  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
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  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
BackLink https://www.ncbi.nlm.nih.gov/pubmed/34732803$$D View this record in MEDLINE/PubMed
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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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