The CHARGE-AF score is a promising 5-year predictive model for incident atrial fibrillation that may improve AF prediction and stroke prevention when combined with mobile health technologies.
Does the CHARGE-AF score accurately predict incident atrial fibrillation?
The CHARGE-AF score is a promising 5-year predictive model for incident atrial fibrillation that could be integrated with mobile health technologies for better screening and stroke prevention.
Atrial fibrillation (AF) is the commonest arrhythmia in clinical practice and is associated with increased morbidity and mortality. Various predictive scores for new-onset AF have been proposed, but so far, none have been widely used in clinical practice. CHARGE-AF score was developed from a pooled diverse population from three large cohorts (Atherosclerosis Risk in Communities study, Cardiovascular Health Study and Framingham Heart Study). A simple 5-year predictive model includes the variables of age, race, height, weight, systolic and diastolic blood pressure, current smoking, use of antihypertensive medication, diabetes mellitus, history of myocardial infarction and heart failure. Recent studies report that the CHARGE-AF score has good discrimination for incident AF and seems to be a promising prediction model for this arrhythmia. New screening tools (smartphone apps, smartwatches) are rapidly developing for AF detection. Therefore, the wide application of the CHARGE-AF score in clinical practice and the upcoming usage of mobile health technologies and smartwatches may result in better AF prediction and adequate stroke prevention, especially in high-risk patients.
Goudis et al. (Sat,) conducted a review in Atrial fibrillation. CHARGE-AF score was evaluated on Incident atrial fibrillation. The CHARGE-AF score is a promising 5-year predictive model for incident atrial fibrillation that may improve AF prediction and stroke prevention when combined with mobile health technologies.