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There is an increasing proportion of the general population surviving to old age with significant chronic disease, multi-morbidity, and disability. The prevalence of pre-frail state and frailty syndrome increases exponentially with advancing age and is associated with greater morbidity, disability, hospitalization, institutionalization, mortality, and health care resource use. Frailty represents a global problem, making early identification, evaluation, and treatment to prevent the cascade of events leading from functional decline to disability and death, one of the challenges of geriatric and general medicine. Cardiac arrhythmias are common in advancing age, chronic illness, and frailty and include a broad spectrum of rhythm and conduction abnormalities. However, no systematic studies or recommendations on the management of arrhythmias are available specifically for the elderly and frail population, and the uptake of many effective antiarrhythmic therapies in these patients remains the slowest. This European Heart Rhythm Association (EHRA) consensus document focuses on the biology of frailty, common comorbidities, and methods of assessing frailty, in respect to a specific issue of arrhythmias and conduction disease, provide evidence base advice on the management of arrhythmias in patients with frailty syndrome, and identifies knowledge gaps and directions for future research. There is an increasing proportion of the general population surviving to old age with significant chronic disease, multi-morbidity, and disability. The prevalence of pre-frail state and frailty syndrome increases exponentially with advancing age and is associated with greater morbidity, disability, hospitalization, institutionalization, mortality, and health care resource use. Frailty represents a global problem, making early identification, evaluation, and treatment to prevent the cascade of events leading from functional decline to disability and death, one of the challenges of geriatric and general medicine. Cardiac arrhythmias are common in advancing age, chronic illness, and frailty and include a broad spectrum of rhythm and conduction abnormalities. However, no systematic studies or recommendations on the management of arrhythmias are available specifically for the elderly and frail population, and the uptake of many effective antiarrhythmic therapies in these patients remains the slowest. This European Heart Rhythm Association (EHRA) consensus document focuses on the biology of frailty, common comorbidities, and methods of assessing frailty, in respect to a specific issue of arrhythmias and conduction disease, provide evidence base advice on the management of arrhythmias in patients with frailty syndrome, and identifies knowledge gaps and directions for future research.

Atrial Fibrillation (AF) is the most common cardiac rhythm disorder. It is associated with increased hospitalization, risk of heart failure, and risk of stroke. Once on AF, it can sometimes be difficult to revert to sinus rhythm (SR), potentially requiring pharmacological or electrical cardioversion. Earlier warning of an imminent switch from SR to AF, even if by only a few minutes, could prompt patients to take actions (e.g., taking oral antiarrhythmic drugs) to avoid AF and its associated complications, thereby easing the workload of healthcare professionals and reducing costs to the health system. The question is whether there is information, even if subtle, in the minutes prior to AF to indicate an imminent switch from SR. This paper shows that, for the vast majority of patients, the answer is affirmative. On test data, our algorithm can predict the onset of AF on average 31 minutes before it appears, with an accuracy of 83% and an F1-score of 85%. Moreover, this performance was obtained from R R interval (RRI) signals, which can be obtained from common wearable devices such as smartwatches and smart bands. The predictions were performed using a deep convolutional neural network, trained and cross-validated on 24-hour RRI signals obtained from Holter electrocardiogram recordings of 280 patients, with an additional 70 patients used as test data. We further tested the model with data from two other external centers with 73 patients. Overall, the proposed method has low computational time and could be embedded in common wearable devices that capture RRI for continuous heart monitoring and early warning of AF onset.