Addition of 24-Hour Heart Rate Variability Parameters to the Cardiovascular Health Study Stroke Risk Score and Prediction of Incident Stroke: The Cardiovascular Health Study

Background Heart rate variability ( HRV ) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24‐hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score ( CHS ‐ SCORE ), previously developed at the baseline examination. Methods and Results N=884 stroke‐free CHS participants (age 75.3±4.6), with 24‐hour Holters adequate for HRV analysis at the 1994–1995 examination, had 68 strokes over ≤8 year follow‐up (median 7.3 [interquartile range 7.1–7.6] years). The value of adding HRV to the CHS ‐ SCORE was assessed with stepwise Cox regression analysis. The CHS ‐ SCORE predicted incident stroke ( HR =1.06 per unit increment, P =0.005). Two HRV parameters, decreased coefficient of variance of NN intervals ( CV %, P =0.031) and decreased power law slope ( SLOPE , P =0.033) also entered the model, but these did not significantly improve the c‐statistic ( P =0.47). In a secondary analysis, dichotomization of CV % ( LOWCV % ≤12.8%) was found to maximally stratify higher‐risk participants after adjustment for CHS ‐ SCORE . Similarly, dichotomizing SLOPE ( LOWSLOPE HRV categories were combined (eg, HIGHCV % with HIGHSLOPE ), the c‐statistic for the model with the CHS ‐ SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS ‐ SCORE alone ( P =0.02). Conclusions In this sample of older adults, 2 HRV parameters, CV % and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8‐year follow‐up. These findings will require validation in separate, larger cohorts.