DocumentCode :
3375426
Title :
Distinguishing normal and abnormal heart rate variability using graphical and non-linear analyses
Author :
Stein, P.K. ; Hui, N. ; Domitrovich, P.P. ; Gottdiener, J. ; Rautaharju, P.
fYear :
2004
fDate :
19-22 Sept. 2004
Firstpage :
205
Lastpage :
208
Abstract :
Abnormal HRV could confound risk stratification. Method: Hourly PoincarP and FFTplots examined in 270 rapes from the Cardiovascular Health Study. Afrer 8 years, 63 subjects had died. Hourly short and longer-term oletrended fractal scaling exponent and interbeat correlations were calculated. Hourly HRV was scored as nom1 (a), borderline (0.5) or abnormal (1) from plot appearance and HRV values. Scores were summed by subject and normalized to create nn abnormalig score (ABN,O- 100%). Cox regression determined the relationship of ABN and mortality. Results: Increased ABN was associated with mortality, p=O.O0.5. After adjustment for age (p=O.OOI) and gender (p=O.OOS), ABN remained associated with mortality (p=O.OIS). When ABN was dichotomized at 57%. HR and SDNN were not diflerent, but higher ABN (N=67) had significantly increased short and intermediate-term XRV and mortaliry. Conclusion: Even with a relatively crude guant$cation method, abnormal rhythms were associated with both mortality and increased HRV.
Keywords :
Cardiology; Doped fiber amplifiers; Fractals; Frequency domain analysis; Heart rate; Heart rate variability; Neural networks; Rhythm; Risk analysis; Sun;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computers in Cardiology, 2004
Conference_Location :
Chicago, IL, USA
Print_ISBN :
0-7803-8927-1
Type :
conf
DOI :
10.1109/CIC.2004.1442908
Filename :
1442908
Link To Document :
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