IntroductionThe aim of this work is investigating the differences of Heart Rate Variability (HRV) features between normal subjects and patients suffering from Congestive Heart Failure (CHF) at several levels of NYHA scale.
CHF is …
IntroductionOnly a few studies have been focused on using HRV measures for diagnosis purpose in CHF and these studies proposed binary classification for identify normal and CHF patient without considering NYHA class.
One study* investigate the discrimination power of long term HRV measures; the other** proposed a classifier based on short term HRV measures but does not provide any information about NYHA class.
Consequently, we investigate the differences of Heart Rate Variability (HRV) features between normal subjects and patients suffering from Congestive Heart Failure (CHF) at several levels of NYHA scale. *M.H. Asyali, Discrimination power of long-term heart rate variability measures, in: Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Cancun, September 17–21, 2003.
**Y. Isler, and M. Kuntalp, “Combining classical HRV indices with wavelet entropy measures improves to performance in diagnosing congestive heart failure,” Computers in Biology and Medicine, vol. 37, no. 10, pp. 1502-1510, Oct, 2007.
MethodsWe performed a retrospective analysis of two public RR interval databases, to compare values for HRV measure in normal middle-aged subjects and in patients who suffered from chronic heart failure, with NYHA I, II and III.
We calculated statistical measures from 5-minute RR interval data using standard methods. Moreover, we estimated short-term frequency domain measures using the Lomb periodogram.
Measure Description Unit
SDNN Standard deviation of all NN intervals. ms
RMSSD The square root of the mean of the sum of the squares of differences between adjacent NN intervals
ms
AVNN Average of all NN intervals ms
pNN50 Percentage of differences between adjacent NN intervals that are > 50 ms
This is one member of the larger pNNx family
%
TOTALPOWER
Total spectral power of all NN intervals up to 0.04 Hz. ms2
VLF Total spectral power of all NN intervals between 0 and 0.04 Hz ms2
LF Total spectral power of all NN intervals between 0.04 and 0.15 Hz ms2
HF Total spectral power of all NN intervals between 0.15 and 0.4 Hz ms2
LF/HF Ratio of low to high frequency power
MethodsFor each selected feature and for each NYHA scale, histogram distribution has been computed.
Finally, we analyzed how the correlation matrix between features of NN series changes according to the severity of CHF.
ResultsWe show the mean and standard deviation of each measure according to NYHA class.
VALUE OF NN MEASURES
Measure
Unit
Normal (mean±SD)
NYHAI (mean±SD)
NYHAII (mean±SD)
NYHAIII (mean±SD)
SDNN ms 47.4±24.8 50.4±29.6 24.3±17.6 25.8±16.9 RMSSD ms 24.8±14.6 25.5±14.2 14.5±8.0 17.0±8.1 AVNN ms 6.2±10.1 7.5±12.3 1.6±4.9 2.3±4.6 pNN50 % 803±156 797±157 639±87 701±103 TOT. POW. ms2 3089±4474 4160±6740 917±1719 968±1599 VLF ms2 2130±3721 2810±5179 670±1290 716±1360 LF ms2 671±965 806±1301 158±355 149±244 HF ms2 287±494 544±770 89±214 103±139 LF/HF - 3.7±2.9 2.1±1.6 2.2±2.0 1.5±1.4
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the histogram distribution of each measure according to NYHA class.
ResultsWe show the correlation matrix between HRV measures
Correlation between NN Measures in Normal Subjects
CORRELATION BETWEEN NN MEASURES IN NORMAL SUBJECTS
AVN
N SDNN RMSSD pNN50 VLF LF HF
AVNN 1 0.30 0.50 0.47 0.16 0.35 0.40
SDNN 1 0.51 0.48 0.84 0.61 0.53
RMSSD 1 0.96 0.23 0.53 0.85
pNN50 1 0.22 0.51 0.83
VLF 1 0.45 0.32
LF 1 0.61
HF 1
CORRELATION BETWEEN NN MEASURES IN NYHA II
AVNN SDNN RMSSD pNN50 VLF LF HF
AVNN 1 0.46 0.45 0.42 0.34 0.34 0.42
SDNN 1 0.73 0.62 0.88 0.77 0.69
RMSSD 1 0.89 0.57 0.74 0.86 pNN50 1 0.52 0.74 0.93
VLF 1 0.70 0.63
LF 1 0.84
HF 1
CORRELATION BETWEEN NN MEASURES IN NYHA I
AVNN SDNN RMSSD pNN50 VLF LF HF
AVNN 1 0.41 0.75 0.67 0.27 0.39 0.55
SDNN 1 0.63 0.51 0.88 0.78 0.79
RMSSD 1 0.95 0.42 0.65 0.82 pNN50 1 0.32 0.55 0.74
VLF 1 0.70 0.65
LF 1 0.86
HF 1
CORRELATION BETWEEN NN MEASURES IN NYHA III
AVNN SDNN RMSSD pNN50 VLF LF HF
AVNN 1 0,43 0,38 0,24 0,31 0,33 0,34
SDNN 1 0,59 0,44 0,88 0,76 0,64
RMSSD 1 0,89 0,33 0,53 0,78 pNN50 1 0,24 0,42 0,73
VLF 1 0,62 0,44
LF 1 0,72
HF 1
DiscussionSDNN, RMSSD and TOTAL POWER has higher values in healthy subjects than in CHF patients.
Moreover, VLF, LF and HF seem to be depressed in CHF patient.
The other parameters, such as AVNN, did not appear to be different between normal and CHF.
The correlations between some features of NN series increase according to the severity of CHF.
From the shown results it is possible conclude that there is a variation in HRV features, according to NYHA classification. We suppose that this variation may drive the research of a hierarchic classifier in order to distinguish not only normal versus CHF patient but also mild versus severe CHF.
