New-onset atrial fibrillation prediction: the HARMS2-AF risk score

Eur Heart J. 2023 Sep 21;44(36):3443-3452. doi: 10.1093/eurheartj/ehad375.

Abstract

Aims: Lifestyle risk factors are a modifiable target in atrial fibrillation (AF) management. The relative contribution of individual lifestyle risk factors to AF development has not been described. Development and validation of an AF lifestyle risk score to identify individuals at risk of AF in the general population are the aims of the study.

Methods and results: The UK Biobank (UKB) and Framingham Heart Study (FHS) are large prospective cohorts with outcomes measured >10 years. Incident AF was based on International Classification of Diseases version 10 coding. Prior AF was excluded. Cox proportional hazards regression identified independent AF predictors, which were evaluated in a multivariable model. A weighted score was developed in the UKB and externally validated in the FHS. Kaplan-Meier estimates ascertained the risk of AF development. Among 314 280 UKB participants, AF incidence was 5.7%, with median time to AF 7.6 years (interquartile range 4.5-10.2). Hypertension, age, body mass index, male sex, sleep apnoea, smoking, and alcohol were predictive variables (all P < 0.001); physical inactivity [hazard ratio (HR) 1.01, 95% confidence interval (CI) 0.96-1.05, P = 0.80] and diabetes (HR 1.03, 95% CI 0.97-1.09, P = 0·38) were not significant. The HARMS2-AF score had similar predictive performance [area under the curve (AUC) 0.782] to the unweighted model (AUC 0.802) in the UKB. External validation in the FHS (AF incidence 6.0% of 7171 participants) demonstrated an AUC of 0.757 (95% CI 0.735-0.779). A higher HARMS2-AF score (≥5 points) was associated with a heightened AF risk (score 5-9: HR 12.79; score 10-14: HR 38.70). The HARMS2-AF risk model outperformed the Framingham-AF (AUC 0.568) and ARIC (AUC 0.713) risk models (both P < 0.001) and was comparable to the CHARGE-AF risk score (AUC 0.754, P = 0.73).

Conclusion: The HARMS2-AF score is a novel lifestyle risk score which may help identify individuals at risk of AF in the general community and assist population screening.

Keywords: Alcohol; Atrial fibrillation; Lifestyle modification; Obesity; Population screening; Sleep apnoea.

MeSH terms

  • Atrial Fibrillation*
  • Cohort Studies
  • Humans
  • Incidence
  • Longitudinal Studies
  • Male
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment
  • Risk Factors