A risk score for predicting atrial fibrillation in individuals with preclinical diastolic dysfunction: a retrospective study in a single large urban center in the United States.

BACKGROUND

Left ventricular diastolic dysfunction has been shown to associate with increased risk of atrial fibrillation (AF). We aimed to examine the predictors of AF in individuals with preclinical diastolic dysfunction (PDD) - diastolic dysfunction without clinical heart failure - and develop a risk score in this population.

METHODS

Patients underwent echocardiogram from December 2009 to December 2015 showing left ventricular ejection fraction (LVEF) ≥ 50% and grade 1 diastolic dysfunction, without clinical heart failure, valvular heart disease or AF were included. Outcome was defined as new onset AF. Cumulative probabilities were estimated and multivariable adjusted competing-risks regression analysis was performed to examine predictors of incident AF. A predictive score model was constructed.

RESULTS

A total of 9591 PDD patients (mean age 66, 41% men) of racial/ethnical diversity were included in the study. During a median follow-up of 54 months, 455 (4.7%) patients developed AF. Independent predictors of AF included advanced age, male sex, race, hypertension, diabetes, and peripheral artery disease. A risk score including these factors showed a Wolber's concordance index of 0.65 (0.63-0.68, p <  0.001), suggesting a good discrimination.

CONCLUSIONS

Our study revealed a set of predictors of AF in PDD patients. A simple risk score predicting AF in PDD was developed and internally validated. The scoring system could help clinical risk stratification, which may lead to prevention and early treatment strategies.