Abstract
Purpose We used a large real-world data from community settings to develop and validate a
10-year risk score for new-onset atrial fibrillation (AF) and calculate its net benefit
performance.
Methods Multivariable Cox proportional hazards model was used to estimate effects of risk
factors in the derivation cohort (n = 96,778) and to derive a risk equation. Measures of calibration and discrimination
were calculated in the validation cohort (n = 48,404).
Results Cumulative AF incidence rates for both the derivation and validation cohorts were
5.8% at 10 years. The final models included the following variables: age, sex, body
mass index, history of treated hypertension, systolic blood pressure ≥ 160 mm Hg,
chronic lung disease, history of myocardial infarction, history of peripheral arterial
disease, heart failure and history of an inflammatory disease. There was a 27-fold
difference (1.0% vs. 27.2%) in AF risk between the lowest (–1) and the highest (9)
sum score. The c-statistic was 0.743 (95% confidence interval [CI], 0.737–0.749) for the derivation
cohort and 0.749 (95% CI, 0.741–0.759) in the validation cohort. The risk equation
was well calibrated, with predicted risks closely matching observed risks. Decision
curve analysis displayed consistent positive net benefit of using the AF risk score
for decision thresholds between 1 and 25% 10-year AF risk.
Conclusion We provide a simple score for the prediction of 10-year risk for AF. The score can
be used to select patients at highest risk for treatments of modifiable risk factors,
monitoring for sub-clinical AF detection or for clinical trials of primary prevention
of AF.
Keywords
atrial fibrillation - models - risk assessment
