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Funding Sources
Introduction Pulmonary vein isolation (PVI) has become an accepted treatment for atrial fibrillation (AF) [1]. The efficacy of PVI is sometimes insufficient, and atrial substrate modification of target specific AF signals indicating the substrate responsible for AF perpetuation has been proposed [2,3]. Complex fractionated atrial electrograms (CFAEs), which are electrograms that demonstrate continuous fractionation and very short myc pathway lengths during AF, may represent the substrate of AF [2,3]. In addition, atrial sites that represent local electrograms with high-dominant frequencies (DFs) may be associated with AF maintenance [4–6]. We reported that a combined high-DF site and continuous CFAE site (fractionated intervals ≤50ms) ablation for the atrial substrate following PVI was effective in both paroxysmal and persistent AF [7]. High-DF and continuous CFAE sites as surrogates for localized sources maintaining AF were potential AF ablation targets [7]. On the other hand, localized electrical sources (rotor and focal impulse) have been reported to be prevalent sustaining mechanisms of human AF using a specific computational mapping device [8]. The patients who underwent a focal impulse and rotor modulation (FIRM)-guided ablation maintained a higher freedom from AF. However, AF rotors did not exhibit consistent or characteristic fractionated electrogram features [9,10]. In another report, FIRM-identified rotor sites did not exhibit any quantitative atrial electrogram characteristics and rotor ablation resulted in AF termination or organization in a minority of the patients [11]. Therefore, this study aimed to evaluate the atrial characteristic electrogram features at high-DF and continuous CFAE sites during AF using a high-density 20-pole circular mapping catheter.
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Conflict of interest
Acknowledgments
Introduction Red cell distribution width (RDW) is a measure of red cell size variability, with higher RDW values reflecting greater heterogeneity (anisocytosis), and its use in the clinical setting has been confined to the differentiation between several etiologies of anemia [1]. However, in recent years, RDW has emerged as a novel predictor of all-cause mortality in multiple cardiovascular settings including congestive heart failure (CHF), and ischemic heart disease (IHD) [2–8]. Atrial fibrillation is a common cardiac arrhythmia among older adults that is likely to increase 2.5-fold during the next 50 years [9]. Frequent hospitalization, hemodynamic abnormalities, and thromboembolic events related to atrial fibrillation can result in significant morbidity and mortality [10]. Identification of new prognostic risk factors like RDW would be valuable for adverse outcome prediction in patients with atrial fibrillation, especially if obtained routinely and inexpensively. Recently, we showed that RDW is an independent predictor of stroke in patients with atrial fibrillation [11]. However, whether RDW is also associated with increased risk of mortality in patients with atrial fibrillation remains unknown. In this study we aimed to assess the association of RDW and changes in RDW over time with all-cause mortality in patients with atrial fibrillation, using data from a population-based electronic medical registry (EMR) database of the largest health maintenance organization (HMO) in Israel.
Materials and methods
Results A total of 69,412 adult subjects with atrial fibrillation were included in the study. The mean age was 74.8 (±12.0) years, and 35,415 (51.9%) were women. A previous history of stroke or TIA was detected in 16,415 (23.6%) subjects, and overall 28,272 (40.7%) patients with atrial fibrillation were treated with anticoagulants at baseline (Table 1). Compared to those in the lowest quartile, subjects in the highest quartile were older, and were more likely to be women. The proportion of subjects with cardiovascular risk factors, and comorbidities along with the average CHADS2 and CHA2DS2-VASc scores increased across RDW quartiles (Table 1). The baseline socio-demographic, clinical, medication use, and laboratory characteristics of the study participants are presented by RDW quartiles as shown in Table 1.