Association between migraine and the risk of vascular dementia: A nationwide longitudinal study in South Korea.

OBJECTIVE: We aimed to examine the potential association between migraine and vascular dementia (VaD) using a nationwide population database. BACKGROUND: Migraine and VaD showed similar structural and functional changes in pathophysiology process and shared common risk factors, However, whether migraine prevalence increases VaD incidence remains controversial. METHODS: This retrospective population-based cohort study used the medical records from the Korean National Health Insurance System database. Migraine (G43) was defined by using the Tenth Revision of the International Classification of Diseases code. More than two migraine diagnoses at least 3 months apart were defined as "chronic migraine". Cox proportional hazards model estimated hazard ratios (HRs) of VaD for group comparisons. RESULTS: We included 212,836 patients with migraine and 5,863,348 individuals without migraine. During 10 years of follow-up, 3,914 (1.8%) and 60,258 (1.0%) patients with and without migraine, respectively, were newly diagnosed with VaD. After adjustment, patients with migraine showed a 1.21-fold higher risk of VaD than those without migraine (HR = 1.21; 95% confidence interval (CI): 1.17-1.25). Patients with chronic migraine showed a higher cumulative incidence of VaD than those with episodic migraine. The adjusted HR for the VaD incidence with migraine was higher in: (1) patients aged <65 years; (2) women; (3) patients without hypertension, diabetes, or atrial fibrillation; and (4) non-smokers. CONCLUSION: Migraine is associated with an increased risk of VaD, particularly in chronic migraine patients. Incidence of VaD in the setting of migraine may have distinct pathophysiology from that of VaD with traditional cardiovascular risks.

Risk Factors and Temporal Patterns of Post-Stroke Epilepsy Across Stroke Subtypes: Insights from a Nationwide Cohort Study in Korea.

INTRODUCTION: We aimed to investigate the risk factors associated with post-stroke epilepsy (PSE) among patients with different subtypes of stroke, focusing on age-related risk and time-varying effects of stroke subtype on PSE development. METHODS: A retrospective, nationwide, population-based cohort study was conducted using Korean National Health Insurance Service-National Sample Cohort data. Patients hospitalized with newly diagnosed stroke from 2005 to 2015 were included and followed up for up to 10 years. The primary outcome was the development of PSE, defined as having a diagnostic code and a prescription for anti-seizure medication. Multivariable Cox proportional hazard models were used to estimate PSE hazard ratios (HRs), and time-varying effects were also assessed. RESULTS: A total of 8,305 patients with ischemic stroke, 1,563 with intracerebral hemorrhage (ICH), and 931 with subarachnoid hemorrhage (SAH) were included. During 10 years of follow-up, 4.6% of patients developed PSE. Among patients with ischemic stroke, significant risk factors for PSE were younger age (HR = 1.47), living in rural areas (HR = 1.35), admission through the emergency room (HR = 1.33), and longer duration of hospital stay (HR = 1.45). Time-varying analysis revealed elevated hazard ratios for ICH and SAH, particularly in the first two years following the stroke. The age-specific hazard ratios also showed an increased risk for those under the age of 65, with a noticeable decrease in risk beyond that age. CONCLUSION: The risk of developing PSE varies according to stroke subtype, age, and other demographic factors. These findings underscore the importance of tailored poststroke monitoring and management strategies to mitigate the risk of PSE.

The association between migraine and Parkinson's disease: a nationwide cohort study.

OBJECTIVES: Clinical studies have suggested an association between migraine and the occurrence of Parkinson's disease (PD). However, it is unknown whether migraine affects PD risk. We aimed to investigate the incidence of PD in patients with migraine and to determine the risk factors affecting the association between migraine and PD incidence. METHODS: Using the Korean National Health Insurance System database (2002-2019), we enrolled all Koreans aged ≥40 years who participated in the national health screening program in 2009. International Classification of Diseases (10th revision) diagnostic codes and Rare Incurable Diseases System diagnostic codes were used to define patients with migraine (within 12 months of enrollment) and newly diagnosed PD. RESULTS: We included 214,193 patients with migraine and 5,879,711 individuals without migraine. During 9.1 years of follow-up (55,435,626 person-years), 1,973 (0.92%) and 30,664 (0.52%) individuals with and without migraine, respectively, were newly diagnosed with PD. Following covariate adjustment, patients with migraine showed a 1.35-fold higher PD risk than individuals without migraine. The incidence of PD was not significantly different between patients with migraine with aura and those without aura. In males with migraine, underlying dyslipidemia increased the risk of PD (p=0.012). In contrast, among females with migraine, younger age (<65 years) increased the risk of PD (p=0.038). CONCLUSIONS: Patients with migraine were more likely to develop PD than individuals without migraine. Preventive management of underlying comorbidities and chronic migraine may affect the incidence of PD in these patients. Future prospective randomized clinical trials are warranted to clarify this association.

Association between migraine and Alzheimer's disease: a nationwide cohort study.

Background and objective: Migraine is a common chronic neurological disease characterized by pulsating headaches, photophobia, phonophobia, nausea, and vomiting. The prevalence of dementia in individuals aged over 65 years in Korea is more than 10%, and Alzheimer's disease (AD) dementia accounts for most cases. Although these two neurological diseases account for a large portion of the medical burden in Korea, few studies have examined the relationship between the two diseases. Therefore, this study investigated the incidence and risk of AD in patients with migraines. Methods: We retrospectively collected nationwide data from a national health insurance claims database governed by Korea's National Health Insurance Service. Among Koreans in the 2009 record, patients with migraine were identified according to the International Classification of Diseases, 10th revision (ICD-10) code G43. First, we screened the database for participants aged over 40 years. Individuals diagnosed with migraine at least twice over more than 3 months in a year were considered to have chronic migraine in this study. Further, all participants with an AD diagnosis (ICD-10 code: Alzheimer's disease F00, G30) were investigated for AD dementia development. The primary endpoint was AD development. Results: The overall incidence of AD dementia was higher in individuals with a history of migraine than in those with no migraine history (8.0 per 1,000 person-years vs. 4.1 per 1,000 person-years). The risk of AD dementia was higher in individuals diagnosed with migraine (hazard ratio = 1.37 [95% confidence interval, 1.35-1.39]) than in the control group after adjustments for age and sex. Individuals with chronic migraine had a higher incidence of AD dementia than those with episodic migraine. Younger age (<65 years old) was associated with an increased risk of AD dementia compared to older age (≥65 years old). Higher body mass index (BMI) (≥25 kg/m2) was also associated with an increased risk of AD dementia compared to lower BMI (<25 kg/m2) (p < 0.001). Conclusion: Our results suggest that individuals with a migraine history are more susceptible to AD than those without a migraine history. Additionally, these associations were more significant in younger and obese individuals with migraine than in individuals without migraine.

Deep-learning-based image quality enhancement of compressed sensing magnetic resonance imaging of vessel wall: comparison of self-supervised and unsupervised approaches.

While high-resolution proton density-weighted magnetic resonance imaging (MRI) of intracranial vessel walls is significant for a precise diagnosis of intracranial artery disease, its long acquisition time is a clinical burden. Compressed sensing MRI is a prospective technology with acceleration factors that could potentially reduce the scan time. However, high acceleration factors result in degraded image quality. Although recent advances in deep-learning-based image restoration algorithms can alleviate this problem, clinical image pairs used in deep learning training typically do not align pixel-wise. Therefore, in this study, two different deep-learning-based denoising algorithms-self-supervised learning and unsupervised learning-are proposed; these algorithms are applicable to clinical datasets that are not aligned pixel-wise. The two approaches are compared quantitatively and qualitatively. Both methods produced promising results in terms of image denoising and visual grading. While the image noise and signal-to-noise ratio of self-supervised learning were superior to those of unsupervised learning, unsupervised learning was preferable over self-supervised learning in terms of radiomic feature reproducibility.