Background: We aimed to identify the long-term risk of recurrence and mortality in patients who experienced acute ischemic stroke (AIS), acute myocardial infarction (AMI), or acute hemorrhagic stroke (AHS) using a population-level database. Methods: This retrospective cohort study included adults aged ≥55 years diagnosed with AIS, AMI, and AHS in the National Health Insurance Service Database between 2004 and 2007. The target outcomes were secondary AIS, AMI, AHS, and all-cause mortality.
View Article and Find Full Text PDFObjectives: Atrial fibrillation (AF), a significant cause of ischemic stroke, often goes undetected because of its asymptomatic nature. This study investigated whether the total bolus-tracking time (TTT) and average slope (AS) of a bolus-tracking graph could be used to predict AF.
Methods: This single-center, retrospective study included patients who underwent carotid CTA and a 24-h Holter test.
Background: This study proposes a cardiovascular diseases (CVD) prediction model using machine learning (ML) algorithms based on the National Health Insurance Service-Health Screening datasets.
Methods: We extracted 4699 patients aged over 45 as the CVD group, diagnosed according to the international classification of diseases system (I20-I25). In addition, 4699 random subjects without CVD diagnosis were enrolled as a non-CVD group.
There are limited data about characteristics of hypertension subtypes in Asian hypertensive patients and their impacts on treatment of hypertension. This prospective, multi-center, observational study evaluated 2439 hypertensive patients. (≥60 years) Inadequately controlled and drug-naïve patients were categorized into three hypertension subtypes (isolated systolic hypertension [ISH], combined systolic/diastolic hypertension [SDH], and isolated diastolic hypertension [IDH]), and proportions of each hypertension subtype were evaluated.
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