Work

Performance of Ambulatory Electrocardiographic Data for Prediction of Stroke and Heart Failure Events

Year: 2024

Type: article

Abstract: Background: Despite clear associations between arrhythmia burden and cardiovascular risk, clinical risk scores that predict cardiovascular events do not incorporate individual-level arrhythmia characteristics from long-term continuous monitoring (LTCM). Objectives: This study evaluated the performance of risk models that use data from LTCM and patient claims for prediction of heart failure (HF) and ischemic stroke. Methods: -VASc score. Results: -VASc for prediction of stroke hospitalization (C-statistic 0.75 [95% CI: 0.74-0.77] vs 0.71 [95% CI: 0.70-0.72], respectively). Atrial fibrillation was associated with greater risk in the most predictive models (HF hospitalization, HR: 1.53 [95% CI: 1.35-1.72]; stroke hospitalization, HR: 1.58 [95% CI: 1.30-1.93]), and premature ventricular couplets were associated with greater risk of HF hospitalization (HR: 1.54, 95% CI: 1.43-1.65). Conclusions: -VASc performed modestly for prediction of stroke and HF events; predictive ability improved significantly with addition of LTCM ECG covariates. The presence of atrial fibrillation and ventricular ectopy on 14-day LTCM were strongly associated with HF events.

Source: JACC Advances

DOI: 10.1016/j.jacadv.2024.101340