Novartis Finland Oy, Espoo, Finland.
Medaffcon Oy, Espoo, Finland.
J Headache Pain. 2020 Jan 31;21(1):8. doi: 10.1186/s10194-020-1077-x.
Migraine is a complex neurological disorder with high co-existing morbidity burden. The aim of our study was to examine the overall morbidity and phenotypic diseasome for migraine among people of working age using real world data collected as a part of routine clinical practice.
Electronic medical records (EMR) of patients with migraine (n = 17,623) and age- and gender matched controls (n = 17,623) were included in this retrospective analysis. EMRs were assessed for the prevalence of ICD-10 codes, those with at least two significant phi correlations, and a prevalence >2.5% in migraine patients were included to phenotypic disease networks (PDN) for further analysis. An automatic subnetwork detection algorithm was applied in order to cluster the diagnoses within the PDNs. The diagnosis-wise connectivity based on the PDNs was compared between migraine patients and controls to assess differences in morbidity patterns.
The mean number of diagnoses per patient was increased 1.7-fold in migraine compared to controls. Altogether 1337 different ICD-10 codes were detected in EMRs of migraine patients. Monodiagnosis was present in 1% and 13%, and the median number of diagnoses was 12 and 6 in migraine patients and controls. The number of significant phi-correlations was 2.3-fold increased, and cluster analysis showed more clusters in those with migraine vs. controls (9 vs. 6). For migraine, the PDN was larger and denser and exhibited one large cluster containing fatigue, respiratory, sympathetic nervous system, gastrointestinal, infection, mental and mood disorder diagnoses. Migraine patients were more likely affected by multiple conditions compared to controls, even if no notable differences in morbidity patterns were identified through connectivity measures. Frequencies of ICD-10 codes on a three character and block level were increased across the whole diagnostic spectrum in migraine.
Migraine was associated with an increased multimorbidity, evidenced by multiple different approaches in the study. A systematic increase in the morbidity across the whole spectrum of ICD-10 coded diagnoses, and when interpreting PDNs, were detected in migraine patients. However, no specific diagnoses explained the morbidity. The results reflect clinical praxis, but also undoubtedly, the pathophysiological phenotypes related to migraine, and emphasize the importance of better understanding migraine-related morbidity.
偏头痛是一种复杂的神经障碍，伴有较高的共存发病率负担。我们的研究旨在使用作为常规临床实践一部分收集的真实世界数据，检查工作年龄人群偏头痛的整体发病率和表型疾病网络。
本回顾性分析纳入了偏头痛（n=17623）和年龄、性别匹配的对照者（n=17623）的电子病历（EMR）。评估了 EMR 中 ICD-10 编码的患病率，那些至少有两个显著 phi 相关性的编码，以及在偏头痛患者中患病率>2.5%的编码被纳入表型疾病网络（PDN）进行进一步分析。应用自动子网络检测算法对 PDN 中的诊断进行聚类。比较偏头痛患者和对照者的 PDN 基于诊断的连通性，以评估发病率模式的差异。
偏头痛患者的平均每位患者诊断数增加了 1.7 倍。总共在偏头痛患者的 EMR 中检测到了 1337 种不同的 ICD-10 编码。单诊断存在于 1%和 13%的患者中，偏头痛患者和对照者的中位数诊断数分别为 12 个和 6 个。显著 phi 相关性的数量增加了 2.3 倍，聚类分析显示偏头痛患者比对照者有更多的聚类（9 个对 6 个）。对于偏头痛，PDN 更大、更密集，并表现出一个包含疲劳、呼吸系统、交感神经系统、胃肠道、感染、精神和情绪障碍诊断的大聚类。与对照者相比，偏头痛患者更有可能受到多种疾病的影响，即使通过连通性测量没有发现明显的发病率模式差异。偏头痛患者整个 ICD-10 编码诊断谱的三字符和块级别的 ICD-10 编码频率增加。
偏头痛与多种疾病相关，这在研究中通过多种方法得到证实。偏头痛患者整个 ICD-10 编码诊断谱的发病率呈系统增加，在解读 PDN 时也得到了检测。然而，没有特定的诊断可以解释发病率。结果反映了临床实践，但也无疑反映了与偏头痛相关的病理生理表型，并强调了更好地理解偏头痛相关发病率的重要性。
