Distinguishing Normal and Abnormal Heart Rate Variability Using Graphical and Non-Linear Analyses

摘要

Abnormal HRV could confound risk stratification. Method: Hourly Poincare and FFT plots examined in 270 tapes from the Cardiovascular Health Study. After 8 years, 63 subjects had died. Hourly short and longer-term detrended fractal scaling exponent and interbeat correlations were calculated. Hourly HRV was scored as normal (0), borderline (0.5) or abnormal (1) from plot appearance and HRV values. Scores were summed by subject and normalized to create an abnormality score (ABN, 0-100%). Cox regression determined the relationship of ABN and mortality. Results: Increased ABN was associated with mortality, p=0.005. After adjustment for age (p=0.001) and gender (p=0.005), ABN remained associated with mortality (p=0.015). When ABN was dichotomized at 57%, HR and SDNN were not different, but higher ABN (N=67) had significantly increased short and intermediate-term HRV and mortality. Conclusion: Even with a relatively crude quantification method, abnormal rhythms were associated with both mortality and increased HRV.