Can we predict the occurrence of atrial fibrillation?

Atrial fibrillation (AF) is a complex disease with increasing prevalence in an aging population and longer survival with cardiovascular diseases. Whereas most clinical efforts have been aimed at predicting risk of AF sequelae such as stroke and heart failure, little is known on primary prevention. AF risk assessment is complicated by the existence of distinct subtypes of AF, such as lone AF or postoperative AF, in contrast to common AF in the elderly. Due to its often intermittent nature, diagnosing AF can be a challenge. Risk prediction becomes reasonable when specific interventions arise. Due to our limited understanding of AF pathophysiology and substantial lack of specific preventive strategies in the population, modification of the general cardiovascular risk profile has largely remained the only option. Initial attempts at combining established risk factors for AF such as age, sex, hypertension, body mass index, electrocardiographic characteristics, and cardiovascular disease in a risk-prediction instrument have produced a robust algorithm. However, known risk factors only explain a fraction of the population-attributable risk of AF, and the search for novel risk indicators is ongoing. More efficient monitoring for electrocardiographic precursors of AF and the field of genomics are evolving areas of AF risk factor research. A better understanding of the underlying substrate of AF will provide targets for prevention. In the future, clinical trials will be needed to establish risk categories, interventions, and their efficacy. Despite a relevant public-health impact, knowledge on risk prediction and primary prevention of AF is still limited today. There are no conflicts of interest to disclose.