Heart rate fragmentation as a marker of altered activity of the autonomic nervous system activity : a novel predictor of atrial fibrillation occurrence in the general population
Authors: Guichard J B , Hupin D , Pichot V , Celle S , Da Costa A , Barthelemy J C , Roche F 
Published: May 2023

Abstract

Funding Acknowledgements
Type of funding sources: Private company. Main funding source(s): Unrestricted grant for fellowship support - Abbott Medical

Background
The dysfunction of the autonomic nervous system (ANS) plays an important role in atrial fibrillation (AF). However, the meaning of high heart rate variability (HRV) in predicting AF is still under debate due to conflicting results in population-based studies. Short-term HRV is conceptually attributed to physiologic vagal tone modulation. But recent data suggest that a component of short-term HRV, called heart rate fragmentation, is related to ANS breakdown and not to the parasympathetic activity.

Purpose
– To assess the predictive capacity of novel short-term HRV-derived metrics regarding the occurrence of AF in the general population during long-term follow-up.

Methods
– A cohort study was designed to prospectively assess the predictive value of ANS activity level among general population regarding cardiovascular events and mortality. 1011 subjects aged 65 were enrolled in the study from September 2000 to December 2002. The study population had no history of AF and a low cardiovascular risk. A median follow-up of 17.8 years was managed. HRV data were acquired by 24-h Holter electrocardiogram (ECG) monitoring at baseline and assessed by frequency domain and time domain methods. Heart rate fragmentation using the percentage of inflection points (PIP) and alpha 1-index (using fractal evaluation of NN intervals) were then calculated. The study outcome was the development of AF during follow-up, defined as a standard 12-lead ECG recording or Holter recording with ≥ 30 s of AF.

Results
– AF was diagnosed in 123 patients during the 18-year follow-up, representing a cumulative incidence of 13.4%. Using multivariate analysis, the occurrence of AF was independently predicted by the male gender (HR=1.96, 95%CI:1.31-2.94, p&lt;0.01), a higher percentage of NN intervals that differ by more than 50 ms from the previous interval (pnn50) (HR=2.01, 95%CI:1.27-3.18, p&lt;0.01), an increased percentage of inflection points (HR=2.48, 95%CI:1.47-4.18,p&lt;0.01), and a reduced alpha 1 index (HR=1.63, 95%CI:1.04-2.55, p&lt;0.01). Given these results, a predictive score was built up based on the 4 independent predictors (Figure 1A). A predictive score of AF occurrence during the 18-year follow-up was assigned to every patient from 0 to 4. Compared to the group of patients with a score of 0 (Figure 1B), AF occurrence was progressively increased in patients with a score of 2 (n=390, HR=5.93, 95%CI:0.82-43.08, p=0.08), of 3 (n=175, HR=12.75., 95%CI:1.75-92.83, p=0.01), and of 4 (n=55, HR=22.31, 95%CI:2.98-167.23, p&lt;0.01).

Conclusion
(Figure 2) – Different markers of short-term HRV predict independently the AF occurrence in the general population aged 65, including markers of ANS breakdown gathered in metrics of heart rate fragmentation, such as an increased PIP and a reduced alpha 1-index. A clinical predictive score based on these predictors is able de segregate a population at high risk of AF occurrence among the general population.