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Heart rate variability: just a surrogate for mean heart rate?

See related article, pp 1334–1343

In this issue of Hypertension , Monfredi et al1 address a phenomenon that has been repeatedly described in the literature2–5 but, nevertheless, went largely unnoticed by the scientific community using heart rate variability (HRV) to assess cardiac autonomic control or to predict cardiovascular health. The phenomenon studied by Monfredi et al1 is that most HRV parameters are inversely related to the actual level of HR, such that HRV is usually lower if HR is high and vice versa. The importance of the work by Monfredi et al1 is that it explores the physiological mechanisms underlying the relationship between HR and HRV using mathematical and biophysical models applied to data from various species and even in vitro preparations with differing levels of mean HR. Furthermore, using the standard deviation (SD) of normal to normal intervals6 as an example of one of the more frequently used HRV parameters; they provide a simple equation that can be used to normalize this HRV parameter so that it is independent of the actual level of HR.

By convention, HRV is typically calculated from RR-interval and not from HR time series.6 As pointed out in a recent review article by Sacha,4 the relationship between HRV (calculated from RR-intervals) and HR is partly because of the inverse relationship between HR and RR-interval (eg, if HR fluctuates by ±10 bpm, the corresponding fluctuations in RR-intervals are ±250 ms at an average HR of 50 bpm but only ±60 ms at an average HR of 100 bpm). Thus, if HRV is calculated from RR-intervals, a …