Value of routine heart rate variability parameters for atrial fibrillation detection in ischaemic stroke and high-risk TIA patients

Introduction Undetected atrial fibrillation (AF) increases the risk of recurrent ischaemic stroke, but current prediction scores do not incorporate heart rate variability (HRV) measures readily available from 24-h Holter ECGs. Methods In 697 patients with non-AF ischaemic stroke or non-AF high-risk transient ischaemic attack (TIA) from the STROKE-CARD Registry (NCT04582825), we assessed eight time-domain HRV parameters for predicting incident AF within 1 year. ROC analyses, logistic regression, and the Youden index were used to identify optimal cut-offs and compare HRV performance with Brown-ESUS AF and AS5F scores. Results New-onset AF was detected in 28 patients (4.0%). PNN50, rMSSD, and SDSD showed the best discrimination (AUC = 0.711, 0.766, and 0.775), outperforming both clinical scores (AUC ≤ 0.612). Optimal cut-offs were 5.5% (PNN50), 48.5 ms (rMSSD), and 43.5 ms (SDSD). Dichotomized analyses confirmed strong associations with AF (ORs 5.34–7.70, all p < 0.001), and adding HRV parameters significantly improved prediction beyond existing scores. Conclusions PNN50, rMSSD, and SDSD from routine Holter ECGs enhance AF risk prediction after non-cardioembolic stroke or high-risk TIA and may support targeted monitoring strategies.