Machine Learning-Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study.

Background: The risk of developing atherosclerotic cardiovascular disease (ASCVD) varies among individuals and is related to a variety of lifestyle factors in addition to the presence of chronic diseases.

Objective: We aimed to assess the predictive accuracy of machine learning (ML) models incorporating lifestyle risk behaviors for ASCVD risk using the Korean nationwide database.

Methods: Using data from the Korea National Health and Nutrition Examination Survey, 5 ML algorithms were used for the prediction of high ASCVD risk: logistic regression (LR), support vector machine, random forest, extreme gradient boosting, and light gradient boosting models.

Assessing the Equivalence of Telephone-MoCA and MoCA-22 in Healthy Adults.

Background And Purpose: The Telephone-Montreal Cognitive Assessment (T-MoCA) is a remote cognitive screening tool increasingly used in clinical and research contexts. However, its applicability in Korean populations remains underexplored.

Methods: This study examined the equivalence between the T-MoCA and the face-to-face Korean MoCA-22 (K-MoCA-22) in a community-based sample of 113 cognitively normal adults aged 21-91 years.

Effectiveness and Safety of Endovascular Treatment in Large Vessel Occlusion Stroke with an NIHSS Score of ≤5 Exhibiting Predominant Cortical Signs.

: Our study aimed to evaluate the impact of EVT on stroke outcomes in patients with LVO with a National Institute of Health Stroke Scale (NIHSS) score of ≤5, exhibiting primarily cortical signs. : We conducted a multicenter registry-based analysis of patients with acute ischemic stroke with LVO who arrived within 12 h of onset. Among these, patients with low NIHSS scores and prominent cortical signs (Items 2, 3, 9, or 11) were included.

Early warning score and feasible complementary approach using artificial intelligence-based bio-signal monitoring system: a review.

Early warning score (EWS) have become an essential component of patient safety strategies in healthcare environments worldwide. These systems aim to identify patients at risk of clinical deterioration by evaluating vital signs and other physiological parameters, enabling timely intervention by rapid response teams. Despite proven benefits and widespread adoption, conventional EWS have limitations that may affect their ability to effectively detect and respond to patient deterioration.

Comparison of Cognitive Deterioration Between Propofol and Remimazolam Anesthesia in ApoE4 Knock-In Mouse Model.

Perioperative neurocognitive disorder (PND) is a concern following anesthesia, particularly in individuals at risk for Alzheimer's disease (AD). This study compared the cognitive and pathological effects of propofol and remimazolam in a mouse model with AD following surgery. Five-month-old male ApoE4-KI mice underwent abdominal surgery under either propofol (170 mg/kg) or remimazolam (85 mg/kg) anesthesia.

The Comprehensive Effect of Depression, Anxiety, and Headache on Pain Intensity and Painkiller Use in Patients with Headache Analyzed by Unsupervised Clustering Using Machine Learning.

: Patients with headache experience depression, anxiety, and reduced quality of life, which are individually associated with pain intensity and painkiller use, but their comprehensive combined effect remains unclear. : Comprehensive patient groups were formed based on unsupervised clustering using machine learning algorithms, and their associations were analyzed via ordinary least square regression. K-means and t-distributed stochastic neighbor embedding (t-SNE) combined with hierarchical density-based spatial clustering of applications with noise (HDBSCAN) were applied for clustering.

Inverse association of obesity with bout periodicity in episodic cluster headache: a multicenter cross-sectional study.

Background: Cluster headache (CH) is the most painful headache disorder. Despite a large body of evidence on obesity's negative influence on migraine, its impact on cluster headache disease activity remains unexplored. We aimed to determine whether body mass index (BMI) and obesity are associated with lifetime bout occurrence and annual bout frequency in patients with episodic cluster headache (ECH).

Mirodenafil improves cognitive function by reducing microglial activation and blood-brain barrier permeability in ApoE4 KI mice.

Introduction: Alzheimer's disease (AD) has significant public health concerns in the aging society. AD can compromise brain function and lead to severe neurological abnormalities associated with dementia. The human Apolipoprotein E (ApoE4) gene is a strong risk factor for AD.

Phosphodiesterase 5 Inhibitor Improves Insulin Sensitivity by Regulating Adipose Tissue Macrophage Polarization in Diet-Induced Obese Mice.

Background: Obesity is a rapidly increasing global health issue, which is associated with glucose and insulin resistance. Phosphodiesterase type 5 (PDE5) inhibitors (PDE5i) are known for their ability to enhance blood flow and vascular stability and are widely used to treat conditions such as erectile dysfunction, pulmonary hypertension, heart failure, and cancer. However, studies investigating the role of PDE5i in alleviating obesity and metabolic diseases remains unclear.

Pain Lateralization in Cluster Headache and Associated Clinical Factors.

Background And Purpose: The pain lateralization in cluster headache (CH) may be related to the asymmetry in the functions of the brain hemispheres. The right-sided dominance of pain in CH has been found inconsistently across studies, and so we aimed to characterize this and identify the factors influencing pain lateralization during current and previous bouts.

Methods: This study enrolled 227 patients from the Korean Cluster Headache Registry between October 2018 and December 2020.

Sex-Specific Associations Between Dynapenia and Risk of Atherosclerotic Cardiovascular Disease: A Machine-Learning-Based Approach.

: Dynapenia, age-associated loss in muscle strength, is an emerging risk factor for atherosclerotic cardiovascular disease (ASCVD), which may have different effects depending on sex. This study aims to investigate the association between dynapenia and ASCVD risk, evaluate its predictive significance among traditional factors, and explore sex-specific patterns through machine learning models. : This retrospective case-control study uses data from 19,582 participants aged 40-79 from the Korean National Health and Nutrition Examination Survey (KNHANES).

Functional Disability and Psychological Impact in Headache Patients: A Comparative Study Using Conventional Statistics and Machine Learning Analysis.

: Recent research has focused on exploring the relationships between various factors associated with headaches and understanding their impact on individuals' psychological states. Utilizing statistical methods and machine learning models, these studies aim to analyze and predict these relationships to develop effective approaches for headache management and prevention. : Analyzing data from 398 patients (train set = 318 and test set = 80), we investigated the influence of various features on outcomes such as depression, anxiety, and headache intensity using machine learning and linear regression.

One-Year Compliance After Calcitonin Gene-Related Peptide Monoclonal Antibody Therapy for Migraine Patients in a Real-World Setting: A Multicenter Cross-Sectional Study.

Calcitonin gene-related peptide monoclonal antibodies (CGRP mAbs) are a breakthrough migraine treatment, but long-term compliance under limited public insurance coverage has not been well known. This study explores one-year treatment patterns and outcomes of CGRP mAbs using real-world data. This multicenter retrospective study included migraine patients treated with CGRP monoclonal antibodies (CGRP mAbs) from July 2022 to June 2023.

Relationship Between Frequency Domain Indicators of Heart Rate Variability and Both Age and Duration of Illness in Patients with Headache: A Cross-Sectional Study.

: One of the most prevalent neurological conditions in the world, headaches impact a large number of people. Patients who experience headaches often have autonomic nervous system dysfunction, which can influence the onset and duration of headaches. Heart rate variability (HRV) serves as an indicator of the autonomic nervous system's activity and balance.

Comparison of early warning scoring systems for predicting stroke occurrence among hospitalized patients: A study using smart clinical data warehouse.

Background: This study aimed to evaluate the predictive ability of two widely used early warning scoring systems, the Modified Early Warning Score (MEWS) and the National Early Warning Score (NEWS), for predicting stroke occurrence in hospitalized patients.

Methods: The study enrolled 5,474 patients admitted to the intensive care unit from the general ward using data from the Smart Clinical Data Warehouse (CDW). MEWS and NEWS were calculated based on vital signs and clinical parameters within four hours of stroke onset.

Lifestyle risk behavior and atherosclerotic cardiovascular risk: An analysis using the Korea National Health and Nutrition Examination Survey.

Background: Clustering lifestyle risk behaviors is important for predicting cardiovascular disease risk. However, it is unclear which behavior mediates other ones to influence cardiovascular disease risk. We aimed to assess the causal inference of each lifestyle risk behavior for the atherosclerotic cardiovascular disease (ASCVD) risk of the general population.

Influence of Age and Sex on Post-Craniotomy Headache.

Post-craniotomy headache (PCH) is a common postoperative complication, and some of these patients progress to chronic PCH (CPCH). We aimed to identify clinical variables associated with PCH and its progression to CPCH, especially possible associations between age and sex differences. Therefore, we examined clinical information on PCH using the Clinical Data Warehouse over 10 years.

Association of liver function markers and apolipoprotein E ε4 with pathogenesis and cognitive decline in Alzheimer's disease.

Background: Alzheimer's disease (AD) is a complex neurodegenerative disorder influenced by various factors, including liver function, which may impact the clearance of amyloid-β (Aβ) in the brain. This study aimed to explore how the apolipoprotein E () ε4 allele affects the relationship of liver function markers with AD pathology and cognition.

Methods: We analyzed data from two independent cohorts, including 732 participants from the Hallym University Medical Center and 483 from the Alzheimer's Disease Neuroimaging Initiative, each group consisting of individuals with and without the ε4 allele.

Impact of white matter hyperintensity volumes estimated by automated methods using deep learning on stroke outcomes in small vessel occlusion stroke.

Introduction: Although white matter hyperintensity (WMH) shares similar vascular risk and pathology with small vessel occlusion (SVO) stroke, there were few studies to evaluate the impact of the burden of WMH volume on early and delayed stroke outcomes in SVO stroke.

Materials And Methods: Using a multicenter registry database, we enrolled SVO stroke patients between August 2013 and November 2022. The WMH volume was estimated by automated methods using deep learning (VUNO Med-DeepBrain, Seoul, South Korea), which was a commercially available segmentation model.

Optimal use of antithrombotic agents in recent small subcortical strokes accompanied by atrial fibrillation.

Background: This study aimed to evaluate the efficacy and safety of anticoagulants (AC) and antiplatelets (APT) in patients with recent small subcortical infarctions (RSSI) and atrial fibrillation (AF).

Methods: We utilized a prospective multicenter stroke registry database to identify patients with RSSI with a concurrent diagnosis of AF. Propensity score matching analysis was used to balance baseline differences among the AC-only, APT-only, and their combination groups.

Effects of Prior Metformin Use on Stroke Outcomes in Diabetes Patients with Acute Ischemic Stroke Receiving Endovascular Treatment.

Diabetes mellitus (DM) predisposes individuals to vascular injury, leading to poor outcomes after ischemic stroke and symptomatic hemorrhagic transformation (SHT) after thrombolytic and endovascular treatment (EVT). Metformin (MET), an oral antidiabetic drug, has shown potential neuroprotective effects, but its impact on stroke prognosis in DM patients undergoing EVT remains unclear. In a multicenter study, 231 patients with DM undergoing EVT for acute ischemic stroke were enrolled.

Diagnosis, Treatment, and Follow-Up of Giant-Cell Arteritis: A Retrospective Multicenter Study.

Background And Purpose: Giant-cell arteritis (GCA) is the most common type of vasculitis in the elderly and is associated with high risks of visual loss and recurrence. Owing to its rarity in Asian populations, the current clinical interventions for these patients are not well known. Here we aimed to characterize the current management status of patients with GCA using Korean multicenter data.

Differences in Neuropathology between Nitroglycerin-Induced Mouse Models of Episodic and Chronic Migraine.

Multiple animal models of migraine have been used to develop new therapies. Understanding the transition from episodic (EM) to chronic migraine (CM) is crucial. We established models mimicking EM and CM pain and assessed neuropathological differences.

Association of Serum Liver Enzymes with Brain Amyloidopathy and Cognitive Performance.

Background: Alzheimer's disease (AD) is characterized by amyloid-β (Aβ) plaque accumulation and neurofibrillary tangles in the brain. Emerging evidence has suggested potential interactions between the brain and periphery, particularly the liver, in regulating Aβ homeostasis.

Objective: This study aimed to investigate the association of serum liver enzymes with brain amyloidopathy and cognitive performance in patients with complaints of cognitive decline.