Atrial fibrillation patterns and their cardiovascular risk profiles in the general population: the Rotterdam study

• Published in: Clinical research in cardiology Vol. 112; no. 6; pp. 736 - 746
• Main Authors: Tilly, Martijn J., Lu, Zuolin, Geurts, Sven, Ikram, M. Arfan, Stricker, Bruno H., Kors, Jan A., de Maat, Moniek P. M., de Groot, Natasja M. S., Kavousi, Maryam
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2023; Springer Nature B.V
• Subjects: Aged; Atrial Fibrillation - diagnosis; Atrial Fibrillation - epidemiology; Body measurements; Cardiac arrhythmia; Cardiology; Cardiovascular diseases; Cardiovascular Diseases - diagnosis; Cardiovascular Diseases - epidemiology; Classification; Diagnosis; Female; Fibrillation; Gender differences; Health risks; Heart Disease Risk Factors; Humans; Male; Medicine; Medicine & Public Health; Men; Middle Aged; Original Paper; Population studies; Risk assessment; Risk Factors; Sex differences; Treatment Outcome; Women; Atrial fibrillation patterns; Arrhythmia; Atrial fibrillation; Risk factors; Anthropometrics; Repeated measurements
• ISSN: 1861-0684; 1861-0692
• DOI: 10.1007/s00392-022-02071-6

Background Clinical guidelines categorize atrial fibrillation (AF) based on the temporality of AF events. Due to its dependence on event duration, this classification is not applicable to population-based cohort settings. We aimed to develop a simple and standardized method to classify AF patterns at population level. Additionally, we compared the longitudinal trajectories of cardiovascular risk factors preceding the AF patterns, and between men and women. Methods Between 1990 and 2014, participants from the population-based Rotterdam study were followed for AF status, and categorized into ‘single-documented AF episode’, ‘multiple-documented AF episodes’, or ‘long-standing persistent AF’. Using repeated measurements we created linear mixed-effects models to assess the longitudinal evolution of risk factors prior to AF diagnosis. Results We included 14,061 participants (59.1% women, mean age 65.4 ± 10.2 years). After a median follow-up of 9.4 years (interquartile range 8.27), 1,137 (8.1%) participants were categorized as ‘single-documented AF episode’, 208 (1.5%) as ‘multiple-documented AF episodes’, and 57 (0.4%) as ‘long-standing persistent AF’. In men, we found poorer trajectories of weight and waist circumference preceding ‘long-standing persistent AF’ as compared to the other patterns. In women, we found worse trajectories of all risk factors between ‘long-standing persistent AF’ and the other patterns. Conclusion We developed a standardized method to classify AF patterns in the general population. Participants categorized as ‘long-standing persistent AF’ showed poorer trajectories of cardiovascular risk factors prior to AF diagnosis, as compared to the other patterns. Our findings highlight sex differences in AF pathophysiology and provide insight into possible risk factors of AF patterns. Graphical abstract