Novel Scoring System for Distinction Between Paroxysmal and Non-Paroxysmal Atrial Fibrillation

Oikawa, Jun; Niwano, Shinichi; Fukaya, Hidehira; Nakamura, Hironori; Igarashi, Tazuru; Fujiishi, Tamami; Ishizue, Naruya; Yoshizawa, Tomoharu; Satoh, Akira; Kishihara, Jun; Murakami, Masami; Ako, Junya

doi:10.1253/circj.cj-16-1054

Cited by 2 publications

(3 citation statements)

References 23 publications

(14 reference statements)

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“…FCL shows dynamic changes according to the phase of AF. We have previously reported a study in which FCL was helpful for distinguishing between paroxysmal and persistent AF [10]. In that study, prolonged FCL (> 165 ms) at the time of the first documented episode of AF was found to be an independent predictor of paroxysmal AF.…”

Section: Discussionmentioning

confidence: 91%

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Fibrillation cycle length predicts cardiovascular events in patients with long-standing persistent atrial fibrillation

et al. 2021

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Background Atrial fibrillation (AF) is associated with an increased risk of heart failure (HF), stroke, and death. Although fibrillation cycle length (FCL) is used as a surrogate for atrial refractoriness, its impact on outcomes remains unclear. This study aimed to identify predictors of cardiovascular events, including FCL, in patients with long-standing persistent AF. Methods The study included 190 consecutive patients with long-standing persistent AF (mean age 74 years, 74% male). Patients with valvular AF or hemodialysis-dependent end-stage renal disease and those on anti-arrhythmic drugs were excluded. The primary composite outcome was occurrence of cardiovascular events (myocardial infarction, HF), cerebrovascular events (stroke, transient ischemic attack), and all-cause death. FCL was calculated by fast Fourier transformation analysis of fibrillation waves in the surface electrocardiogram. Results Over a median follow-up of 2.6 years, the primary outcome occurred in 31 patients (cardiovascular events, n = 18; cerebrovascular events, n = 8; all-cause death, n = 5). In multivariate analysis, longer FCL and history of HF were independent predictors of these outcomes. In a Cox proportional hazards model adjusted for age, sex, and history of HF, patients with an FCL > 160 ms (cut-off determined by receiver-operating characteristic curve analysis) were at increased risk of the outcome (hazard ratio 12.9; 95% confidence interval 4.99-44.10; p < 0.001). Conclusions FCL was independently associated with cardiovascular outcomes in patients with long-standing persistent AF.

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Section: Discussionmentioning

confidence: 91%

“…The methods used to measure FCL have been described elsewhere [10,11]. In brief, the V1 lead recording was analyzed in patients found to have AF on a surface 12-lead ECG.…”

Section: Fft Analysis Of Fibrillation Wavementioning

confidence: 99%

Fibrillation cycle length predicts cardiovascular events in patients with long-standing persistent atrial fibrillation

et al. 2021

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“…It has been reported that in the early stage of AF, the autonomic nervous system tends to cause tachycardia, but afterwards, the HR decreases over time. 24 The larger HRR group in the present study might have included more patients with permanent AF in the relatively early stage.…”

Section: Discussionmentioning

confidence: 95%

Variation in heart rate range by 24‐h Holter monitoring predicts heart failure in patients with atrial fibrillation

et al. 2022

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Aims The analysis of heart rate (HR) changes, such as the HR variability or HR turbulence, has been reported as a marker of cardiovascular events during sinus rhythm; however, those relationships during atrial fibrillation (AF) remain controversial, and those parameters are not commonly used in AF patients. We sought to investigate the relationship between a simple index focused on the HR and heart failure (HF) events in patients with permanent AF. Methods and results We enrolled 198 patients with permanent AF and evaluated the HR range, defined as the maximum HR minus the minimum HR on 24‐h Holter electrocardiogram recordings. The patients were divided into two groups, i.e., the larger (n = 101) and smaller (n = 97) HR range (HRR) groups, determined by the median value. The HF events were defined as hospitalizations for HF or urgent hospital visits due to exacerbations of one's HF status. The observation period of this study was set at 5 years from registration. The median age was 73 (68–77) years, and 29% were female. The median HRR was 84 (63–118) beats per minutes (bpm). During the observational period of 1825 days (median), HF events occurred in 37 (0.047 per patient‐year) patients. In a log‐rank test, the larger HRR group had more frequent HF events than the smaller HRR group (P = 0.0078). In the adjusted Cox proportional hazards model using the significantly different factors from the univariate analysis (Model 1) and factors and medications associated with HF (Model 2), the larger HRR group had a higher prevalence of HF events than the smaller HRR group for both models [Model 1, adjusted hazard ratio = 3.21, 95% confidence interval (CI) 1.593–6.708, P = 0.0009; Model 2, adjusted hazard ratio = 3.12, 95% CI 1.522–6.685, P = 0.002]. When analysed using the time‐dependent Cox proportional hazards model, the HRR was associated with HF with a statistically significant difference in both the univariate and multivariate analyses [hazard ratio = 1.01, 95% CI 1.006–1.020, P = 0.0002; Model 1, adjusted hazard ratio = 1.02, 95% CI 1.011–1.027, P < 0.0001; Model 2, adjusted hazard ratio = 1.01, 95% CI 1.008–1.021, P = 0.0003). There was no significant difference in the chronotropic medications between the two groups. Conclusions In patients with permanent AF, a larger HRR was associated with HF events.

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Novel Scoring System for Distinction Between Paroxysmal and Non-Paroxysmal Atrial Fibrillation

Cited by 2 publications

References 23 publications

Fibrillation cycle length predicts cardiovascular events in patients with long-standing persistent atrial fibrillation

Fibrillation cycle length predicts cardiovascular events in patients with long-standing persistent atrial fibrillation

Variation in heart rate range by 24‐h Holter monitoring predicts heart failure in patients with atrial fibrillation

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