期刊
JOURNAL OF THE AMERICAN HEART ASSOCIATION
卷 6, 期 7, 页码 -出版社
WILEY
DOI: 10.1161/JAHA.116.004305
关键词
autonomic nervous system; clinical stroke risk model; heart rate variability; prediction; predictors; risk prediction; risk stratification; stroke
资金
- National Heart, Lung, and Blood Institute [HHSN268201200036C, HHSN-268200800007C, N01HC55222, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, U01HL080295]
- National Institute on Aging [R01AG023629]
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 <-1.4) maximally stratified higher-risk participants. When these 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.
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