Abstract
Abstract Background Atrial fibrillation (AF) increases the risk of hospitalization for heart failure (HF), as well as that of thromboembolism. The strategy for prediction of thromboembolism has been well-established; however, little focus has been placed on the risk stratification for and prevention of HF hospitalization in AF patients. Purpose The aim of this study is to investigate the predictors and risk model of HF hospitalization in non-valvular AF patients without pre-existing HF. Methods The Fushimi AF Registry is a community-based prospective survey of AF patients in Fushimi-ku, Kyoto, Japan. The inclusion criterion of the registry is the documentation of AF at 12-lead electrocardiogram or Holter monitoring at any time, and there are no exclusion criteria. We started to enroll patients from March 2011, and follow-up data were available for 4,472 patients by the end of October 2020. From the registry, we excluded patients without a pre-existing HF (defined as having one of the following; prior hospitalization for HF, New York Heart Association class ≥2, or left ventricular ejection fraction [LVEF] <40%), and those with valvular AF (mitral stenosis or prosthetic heart valve). Among 3,188 non-valvular AF patients without pre-existing HF, we explored the risk factors for the HF hospitalization during follow-up period. The risk model for predicting HF hospitalization was determined by the cumulative numbers of risk factors which were significant on multivariate analysis. Results The mean age was 72.4±10.8 years, 1197 were female and 1787 were paroxysmal AF. The mean CHADS2 and CHA2DS2-VASc scores were 1.7±1.2 and 2.9±1.6, respectively. During the median follow-up period of 5.1 years, HF hospitalization occurred in 285 (8.9%), corresponding to an annual incidence of 1.8 events per 100 person-years. In multivariable Cox regression analysis, advanced age (≥75 years), valvular heart disease, coronary artery disease, reduced LVEF (<60%), chronic obstructive pulmonary disease (COPD) and anemia were independently associated with the higher incidence of HF hospitalization (all P<0.001) (Picture 1). A risk model based on these 6 variables could stratify the incidence of HF hospitalization during follow-up period (log-rank; P<0.001) (Picture 2). Patients with ≥3 risk factors had an 11-fold higher incidence of HF hospitalization compared with those not having any of these risk factors (hazard ratio: 11.3, 95% confidence interval: 7.0–18.4; P<0.001). Conclusions Advanced age, coronary artery disease, valvular heart disease, reduced LVEF, COPD and anemia were independently associated with the risk of HF hospitalization in AF patients without pre-existing HF. There was good prediction for endpoint of HF hospitalization using these 6 variables, providing the opportunities for the implementation of strategies to reduce the incidence of HF among AF patients. Funding Acknowledgement Type of funding sources: None.
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