부산대학교 도서관

Atrial fibrillation is a substantial health-care challenge and is considered to be a global pandemic, as prevalence rates have increased greatly[1] and atrial fibrillation-related hospitalisations outnumber those of major cardiac conditions such as heart failure and myocardial infarction.[2] Atrial fibrillation confers an increased risk of stroke and mortality; it therefore needs to be detected not only to manage the arrhythmia but also to prevent comorbidities and death.[3] A 10-second, 12-lead electrocardiograph (ECG) in current clinical practice is unlikely to reveal possible atrial fibrillation if not present in this short monitoring time. Performance improved when including all ECGs acquired during each patient's window of interest, which began at the study start date for those without atrial fibrillation and 31 days before the first recorded atrial fibrillation ECG for patients with atrial fibrillation. Additionally, linking these variables with genetic markers,[11] AI-enabled algorithms,[7] and smart monitoring by means of wearables[5] to diagnose atrial fibrillation and quantify atrial fibrillation burden promises a safer and more efficient prevention of atrial fibrillation-related complications. [Extracted from the article]