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

Rohan K. Bodapati, Jorge Kizer, Willem J. Kop, Hooman Kamel, Phyllis K. Stein

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

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.

Original languageEnglish (US)
Article numbere004305
JournalJournal of the American Heart Association
Volume6
Issue number7
DOIs
StatePublished - Jul 1 2017

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Heart Rate
Stroke
Myocardial Infarction
Health
Regression Analysis

Keywords

  • Autonomic nervous system
  • Clinical stroke risk model
  • Heart rate variability
  • Prediction
  • Predictors
  • Risk prediction
  • Risk stratification
  • Stroke

ASJC Scopus subject areas

  • Cardiology and Cardiovascular Medicine

Cite this

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. / Bodapati, Rohan K.; Kizer, Jorge; Kop, Willem J.; Kamel, Hooman; Stein, Phyllis K.

In: Journal of the American Heart Association, Vol. 6, No. 7, e004305, 01.07.2017.

Research output: Contribution to journalArticle

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title = "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",
abstract = "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.",
keywords = "Autonomic nervous system, Clinical stroke risk model, Heart rate variability, Prediction, Predictors, Risk prediction, Risk stratification, Stroke",
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T1 - Addition of 24-hour heart rate variability parameters to the cardiovascular health study stroke risk score and prediction of incident stroke

T2 - The cardiovascular health study

AU - Bodapati, Rohan K.

AU - Kizer, Jorge

AU - Kop, Willem J.

AU - Kamel, Hooman

AU - Stein, Phyllis K.

PY - 2017/7/1

Y1 - 2017/7/1

N2 - 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.

AB - 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.

KW - Autonomic nervous system

KW - Clinical stroke risk model

KW - Heart rate variability

KW - Prediction

KW - Predictors

KW - Risk prediction

KW - Risk stratification

KW - Stroke

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