Department of Neurology, Severance Hospital, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.
Biostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul, Korea.
Sci Rep. 2021 Nov 3;11(1):21595. doi: 10.1038/s41598-021-01107-7.
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.
偏头痛既没有明确的单一症状，也没有明显的生物标志物；因此，其诊断基于典型症状的组合。我们旨在根据国际头痛疾病分类第 3 版诊断标准中列出的症状，确定偏头痛的自然亚组。潜在类别分析 (LCA) 应用于韩国睡眠头痛研究的数据，这是一项全国性基于人群的调查。我们根据赤池信息量准则和贝叶斯信息准则选择了一个三类别模型，并将这三个确定的类别描述为“轻度和低频”、“畏光和畏声”和“重度和高频”。总的来说，52.0%（65/125）的参与者被归类为“轻度和低频”，表现出最频繁的轻度头痛强度，但总体头痛频率最低。同时，“畏光和畏声”涉及 33.6%（42/125）的参与者，他们表现出最频繁的畏光和畏声。最后，“重度和高频”包括 14.4%（18/125）的参与者，他们表现出最频繁的重度头痛强度和最高的头痛频率。总之，LCA 可用于分析偏头痛症状的异质性，并确定偏头痛亚型。这种方法可能会提高我们对偏头痛临床特征的理解。
