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Review
. 2005 Jan;10(1):88-101.
doi: 10.1111/j.1542-474X.2005.10101.x.

Heart Rate Variability: Measurement and Clinical Utility

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Free PMC article
Review

Heart Rate Variability: Measurement and Clinical Utility

Robert E Kleiger et al. Ann Noninvasive Electrocardiol. .
Free PMC article

Abstract

Electrocardiographic RR intervals fluctuate cyclically, modulated by ventilation, baroreflexes, and other genetic and environmental factors that are mediated through the autonomic nervous system. Short term electrocardiographic recordings (5 to 15 minutes), made under controlled conditions, e.g., lying supine or standing or tilted upright can elucidate physiologic, pharmacologic, or pathologic changes in autonomic nervous system function. Long-term, usually 24-hour recordings, can be used to assess autonomic nervous responses during normal daily activities in health, disease, and in response to therapeutic interventions, e.g., exercise or drugs. RR interval variability is useful for assessing risk of cardiovascular death or arrhythmic events, especially when combined with other tests, e.g., left ventricular ejection fraction or ventricular arrhythmias.

Figures

Figure 1
Figure 1
R‐R interval power spectra. The upper panel plots log power versus frequency for a 5‐minute periodogram and the lower panel plots log power versus frequency for a 24‐hour periodogram. In the lower panel, frequency is plotted on a log scale and the Y axis is markedly compressed compared with the upper panel. Note the exponential increase in power as frequency decreases below the low frequency band for both graphs. The two graphs resemble each other, but with much greater amplitude in the 24‐hour plot (lower panel). The similarity in the graphs is consistent with fractal behavior for power below the low frequency band.
Figure 2
Figure 2
Nonlinear Measures of R‐R Interval fluctuations. The top panel shows a two‐dimensional vector analysis of a Poincaré plot; the middle panel shows calculation of detrended fluctuation analysis (DFA); and the bottom panel shows calculation of the power law slope. The Poincaré plots and DFA analyses are derived from a 1‐hour recording at night in a healthy subject. The power law slope is derived from a 24‐hour recording. Abbreviations: SD1, short‐term beat‐to‐beat R‐R variability from the Poincaré plot (width); SD2, long‐term beat‐to‐beat variability from the Poincaré plot (length); α1, the short‐term fractal scaling exponent for 4–11 beats; α2, the intermediate‐term fractal scaling exponent (11–20 beats), β, power law slope (adapted from Ref. 73)
Figure 3
Figure 3
Kaplan‐Meier survival curves from the Multi‐Center Post‐Infarction Study demonstrating decreased survival among patients with SDNN <50 ms (from Ref. 28)

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