Correlations between frequency-domain HRV indexes and lagged Poincare plot width in healthy and diabetic subjects

Abstract

The conventional Poincaré plot for heart rate variability (HRV) analysis is a scatterplot of successive (lag 1) pairs of RR intervals (intervals between heartbeats), and its width (SD1) is considered a measure of short-term variability. It has been shown that SD1 correlates better with HF than with LF (high- and low-frequency bands of the spectrum, respectively). Our aim was to assess how these correlations were affected when SD1 was obtained for longer lags. 10 min ECGs were used to construct Poincaré plots with lags of 1-10 heartbeats in two groups of subjects, one with normal HRV and the other with impaired HRV (control and diabetic groups respectively, N = 15 each). SD1 was quantified for these subjects and HRV spectral indices were estimated. The diabetic group had lower LF, HF and SD1 than the control group (p < 0.05). In both groups, SD1 tended to increase as the lag increased. In the control group, SD1 for lags 1 and 2 was highly correlated with HF (r(s) > 0.9), while SD1 for lags 4 correlated better with LF (r(s) 0.9) than with HF (0.65 <or= r(s) <or= 0.73). However, in the diabetic group, the correlation results did not change in that way for different lags (correlation results between HF and SD1: r(s) 0.95 for lags 1-10). In conclusion, the comparative strength of the correlations between lagged Poincaré widths and spectral indices might be useful to distinguish normal from pathological HRV.