Seasonal trends in atrial fibrillation episodes and physical activity collected daily with a remote monitoring system for cardiac implantable electronic devices

• Published in: International journal of cardiology 2017-05, Vol.234, p.48-52
• Main Authors: Censi, Federica, Calcagnini, Giovanni, Mattei, Eugenio, Calò, Leonardo, Curnis, Antonio, D'Onofrio, Antonio, Vaccari, Diego, Zanotto, Gabriele, Morichelli, Loredana, Rovai, Nicola, Gargaro, Alessio, Ricci, Renato Pietro
• Format: Article
• Language: English
• Subjects: Aged; Atrial fibrillation; Atrial Fibrillation - diagnosis; Atrial Fibrillation - epidemiology; Atrial Fibrillation - physiopathology; Cardiovascular; Defibrillators, Implantable - statistics & numerical data; Electrocardiography, Ambulatory - instrumentation; Electrocardiography, Ambulatory - methods; Exercise - physiology; Female; Home monitoring; Humans; Incidence; Italy - epidemiology; Male; Middle Aged; Pacemaker, Artificial - statistics & numerical data; Physical activity; Remote Sensing Technology - methods; Seasonality; Seasons; Statistics as Topic
• ISSN: 0167-5273; 1874-1754
• DOI: 10.1016/j.ijcard.2017.02.074

Abstract Background Remote monitoring (RM) of cardiac implantable electronic devices is an ideal experimental model to evaluate long-term trends of physiological and clinical data automatically collected from large patient cohorts. Objectives We studied data of atrial fibrillation (AF) and physical activity (PA) transmitted daily during 3.5 years from a subgroup of patients enrolled in the HomeGuide trial, a previously conducted study on patients routinely followed with a RM system transmitting clinical and diagnostic data daily. Methods We selected 988 patients (80% male, mean age 68 ± 11) implanted with a pacemaker (16%) or an implantable defibrillator and provided with atrial sensing and movement sensors. Remotely transmitted data were processed in order to obtain AF incidence and time of PA in the form of collective time series daily sampled. Results We found that both PA and AF incidence clearly showed seasonal trends with an annual period and inverse correlation. In a first-order autoregressive model the regression coefficient of daily activity to AF incidence was − 0.64 (standard error, 0.18, p < 0.0001), while the cross-correlation coefficient reached its maximum values at ± 180 day lags. AF incidence was 14.4% higher and PA was 14.7% lower in winters than in summers ( p < 0.0001 for both comparisons). Power spectral analysis revealed weekly periodicity in the PA series (corresponding to festivity rest) but not in the AF incidence. Conclusions RM data collected daily from a relatively large patient cohort revealed marked seasonal trends in AF incidence and PA with opposite behavior in winters and summers.