The performance of five models compared with atrial high rate episodes predicts new atrial fibrillation after cardiac implantable electronic devices implantation

Abstract

Abstract Aims Several predicting models have been evaluated for new‐onset atrial fibrillation (AF) in several clinical conditions, but never in patients with cardiac implantable electronic devices (CIED). We aimed to evaluate the five predicting models compared with atrial high rate episodes (AHRE) to predict new AF in patients with CIED. Methods and Results We retrospective enrolled 470 consecutive patients with CIED and without a history of AF. The five predicting models, including CHA2DS2‐VASc score, C2HEST score, mCHEST score, HAT2CH2 score, and HAVOC score were used. The primary endpoint was new AF documented by 12‐lead electrocardiography (ECG) or 30‐s ECG strip. Multivariable Cox regression analysis was used to determine variables associated with independent factors of new AF. Patients' median age was 76 years and 58.7% were male. During follow‐up (median 29 months), 34 new AF occurred (incidence rate 2.99/100 patient‐years, 95% CI 1.67–6.20). Multivariable Cox regression analysis showed AHRE ≥6 min and 24 h, and HAT2CH2 score were independent predictors for new AF. Optimal AHRE cutoff value was 9.3 min with highest Youden index (AUC, 0.806; 95% CI, 0.722–0.889; p < .001). The AF occurrence rate of AHRE ≥9.3 min was 7 times AHRE <9.3 min (p < .001). Conclusions We compared 5 predicting models for new AF in patients with CIED and without a history of AF. AHRE ≥6 min and 24 h, and HAT2CH2 score were independent predictors for AF.

Keywords

• atrial fibrillation
• cardiac implantable electronic device
• predicting models