Burden of migraine in Finland: multimorbidity and phenotypic disease networks in occupational healthcare

Abstract

Background: 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. Methods: 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. Results: 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. Conclusions: 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.

My Migraine Voice survey: disease impact on healthcare resource utilization, personal and working life in Finland

“…There has been a paucity of data for the spectrum of migraine impact in the Nordic countries. Earlier studies from Finland have shown an almost 2-fold increase in healthcare visits and sick leave days when compared to age-matched counterparts [ 17 – 19 ]. In Sweden, a recent national patient organization survey showed a correlation between the loss in yearly quality adjusted life-years (QALYs) and increasing number of migraine days indicating that productivity loss represented a significant part of costs in migraine [ 20 ].…”

Evaluation of the Pharmacokinetic Interaction and Safety of Ubrogepant Coadministered With Esomeprazole Magnesium

“…Many individuals with migraine have gastrointestinal conditions that are commonly treated with prescription or OTC esomeprazole magnesium; these include GERD, acid reflux, and dyspepsia. In populationbased studies, dyspepsia was found to be 2 times higher in individuals with migraine compared with those without migraine in Finland, 20 and the prevalence of dyspepsia was 41% among individuals with migraine in Iran. 21 Rates of GERD were 1.8 times higher among individuals with migraine vs those without in the Finland study.…”

Phenotypic Disease Network Analysis to Identify Comorbidity Patterns in Hospitalized Patients with Ischemic Heart Disease Using Large-Scale Administrative Data

“…First, the present study included a large and representative sample of Chinese populations which provided a unique opportunity to study the entire spectrum of phenotypic chronic diseases rather than focusing on a single disease or a small number of them [ 9 , 10 , 11 , 12 , 13 ]. Second, using network theory and diagnostic codes from discharge data, a more in-depth exploration of the complex relationships between chronic conditions was undertaken by obtaining a profile of significant comorbidities in IHD inpatients [ 67 ]. Last, to the best of our knowledge, this is the first case–control study in China to investigate differences in comorbidity status between IHD and non-IHD inpatients, which has important implications for the integrated management of inpatients with IHD [ 68 ].…”