BACKGROUND: Heart rate (HR) variability has been shown to predict spontaneous onset of atrial fibrillation (AF). This study was designed to test the hypothesis that HR variability after electrical cardioversion (CV) of persistent AF predicts the recurrence of AF. METHODS: Various time and frequency domain measures of HR variability, along with the non-linear measures of HR dynamics, were analyzed from the 24-hour ECG recordings in 78 patients with persistent AF after restoration of sinus rhythm with electrical CV. RESULTS: During the follow-up of one month, 27 patients (35%) had recurrence of AF. The patients with AF recurrence had significantly higher standard deviation of all R-R intervals (SDNN 117 +/- 34 versus 100 +/- 29 P < 0.05), increased high-frequency (InHF 5.7 +/- 0.6 versus 5.3 +/- 0.7 P < 0.05 ), low-frequency (InLF 6.2 +/- 0.8 versus 5.6 +/- 0.9 P < 0.01) and very-low-frequency (InVLF 7.1 +/- 0.8 versus 6.5 +/- 0.8 P < 0.01) power spectral components of HR variability than those who remained in sinus rhythm. Approximate entropy, a measure of complexity of HR dynamics, and the short-term fractal scaling exponent did not differ between the groups, but the long-term power-law slope beta was steeper among the patients who remained in sinus rhythm (P < 0.05). During the first week after the CV, increased HF power (highest tertile) was the most powerful predictor of AF recurrence with odds ratio of 2.8 (95% confidence interval 1.0 to 8.0, P < 0.05). Increased VLF power spectral component at baseline predicted best the late recurrence of AF with odds ratio of 3.3 (95% confidence interval 1.6 to 7.2, P < 0.01). No clinical or echocardiographic variable predicted the recurrence of AF. CONCLUSIONS: Increased HR variability in all major power spectral bands is associated with late recurrence of AF after electrical CV. Enhanced cardiac vagal outflow, reflected as an increased HF power spectral component, seems to predict specifically the early recurrence of AF after the CV.
BACKGROUND: Heart rate (HR) variability has been shown to predict spontaneous onset of atrial fibrillation (AF). This study was designed to test the hypothesis that HR variability after electrical cardioversion (CV) of persistent AF predicts the recurrence of AF. METHODS: Various time and frequency domain measures of HR variability, along with the non-linear measures of HR dynamics, were analyzed from the 24-hour ECG recordings in 78 patients with persistent AF after restoration of sinus rhythm with electrical CV. RESULTS: During the follow-up of one month, 27 patients (35%) had recurrence of AF. The patients with AF recurrence had significantly higher standard deviation of all R-R intervals (SDNN 117 +/- 34 versus 100 +/- 29 P < 0.05), increased high-frequency (InHF 5.7 +/- 0.6 versus 5.3 +/- 0.7 P < 0.05 ), low-frequency (InLF 6.2 +/- 0.8 versus 5.6 +/- 0.9 P < 0.01) and very-low-frequency (InVLF 7.1 +/- 0.8 versus 6.5 +/- 0.8 P < 0.01) power spectral components of HR variability than those who remained in sinus rhythm. Approximate entropy, a measure of complexity of HR dynamics, and the short-term fractal scaling exponent did not differ between the groups, but the long-term power-law slope beta was steeper among the patients who remained in sinus rhythm (P < 0.05). During the first week after the CV, increased HF power (highest tertile) was the most powerful predictor of AF recurrence with odds ratio of 2.8 (95% confidence interval 1.0 to 8.0, P < 0.05). Increased VLF power spectral component at baseline predicted best the late recurrence of AF with odds ratio of 3.3 (95% confidence interval 1.6 to 7.2, P < 0.01). No clinical or echocardiographic variable predicted the recurrence of AF. CONCLUSIONS: Increased HR variability in all major power spectral bands is associated with late recurrence of AF after electrical CV. Enhanced cardiac vagal outflow, reflected as an increased HF power spectral component, seems to predict specifically the early recurrence of AF after the CV.
Authors: Eva María Cirugeda Roldan; Sofía Calero; Víctor Manuel Hidalgo; José Enero; José Joaquín Rieta; Raúl Alcaraz Journal: Entropy (Basel) Date: 2020-07-07 Impact factor: 2.524
Authors: William Whang; Karina W Davidson; David Conen; Usha B Tedrow; Brendan M Everett; Christine M Albert Journal: J Am Heart Assoc Date: 2012-06-22 Impact factor: 5.501
Authors: Eco J C de Geus; Peter J Gianaros; Ryan C Brindle; J Richard Jennings; Gary G Berntson Journal: Psychophysiology Date: 2018-10-25 Impact factor: 4.016