The global prevalence of atrial fibrillation (AF) is rising, paralleling increased life expectancy. Early rhythm control benefits AF management. However, in low-risk, often asymptomatic, AF patients, anticoagulant monotherapy is the selected treatment, aligning with current guidelines. However, early AF progression in these low-risk individuals is not well-understood. Thus, this study aims to: 1) determine the proportion of low-risk AF patients who worsen within a year of initial AF diagnosis and 2) identify risk factors such treatment transitions. We analyzed data from 18623 AF patients, spanning January 2005 to June 2017. Low-risk patients were those on anticoagulant monotherapy ± rate control, following the JCS/JHRS 2020 Guideline on Pharmacotherapy of Cardiac Arrhythmias. We defined 2 patterns of treatment transition for 1) initiating ablation or antiarrhythmic drug therapy and 2) solely using antiarrhythmic drugs. This retrospective cohort study was employed a 12-month study, following a 6-month screening period. We included 1874 patients for all rhythm control (analysis 1) and 1503 for only medication-based control (analysis 2). The primary endpoint, treatment transition of AF under monotherapy, occurred in 28.4% of patients in analysis 1 and 10.8% in analysis 2. Risk factors common to both scenarios were male gender, baseline rate control drug use, and rivaroxaban selection, as identified by multiple logistic regression. These findings suggest a higher AF treatment transition trend in patients starting rivaroxaban, calling for further research. The study highlights the importance of informed early rhythm control initiation decisions in clinical settings.
Keyphrases
- atrial fibrillation
- end stage renal disease
- risk factors
- ejection fraction
- newly diagnosed
- chronic kidney disease
- catheter ablation
- clinical trial
- stem cells
- combination therapy
- prognostic factors
- heart failure
- patients undergoing
- oral anticoagulants
- left atrial appendage
- emergency department
- left atrial
- healthcare
- open label
- bone marrow
- blood pressure
- machine learning
- percutaneous coronary intervention
- artificial intelligence
- mental health
- big data
- coronary artery disease
- left ventricular
- climate change
- cell therapy