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Heart rate variability assessment using time-frequency analysis in hypotensive and non-hypotensive patients in hemodialysis

Applied Sciences (Switzerland), ISSN: 2076-3417, Vol: 10, Issue: 17
2020
  • 8
    Citations
  • 0
    Usage
  • 17
    Captures
  • 1
    Mentions
  • 0
    Social Media
Metric Options:   Counts1 Year3 Year

Metrics Details

  • Citations
    8
    • Citation Indexes
      8
  • Captures
    17
  • Mentions
    1
    • Blog Mentions
      1
      • Blog
        1

Article Description

Intradialytic hypotension occurs in 10-30% of hemodialysis (HD) sessions. This phenomenon affects the cardiovascular system's functions, which are reflected in the activity of the autonomic nervous system (ANS). To indirectly assess the ANS during HD, we analyzed the mean R-R intervals and the spectral power of heart rate variability (HRV) from 20 end-stage renal disease patients divided into hypotensive and non-hypotensive groups. The spectrotemporal analysis was accomplished using short-time Fourier transform with 10 min epochs of HRV overlapping by 40%. The spectral power was divided into three segments according to high frequency, low frequency, and very low frequency bandwidths and averaged to fit quadratic regression models. The analysis of the mean R-R intervals showed significant differences between the groups (p = 0.029). The power variation over time was significant in each spectral band (p«0.05). The average power, maximum power, and time when the peak was reached differed for each band and between groups, showing the ability to correctly identify the decompensation of the ANS and discriminate between hypotensive and non-hypotensive patients. Additionally, the changes in the sympathovagal ratio were not significant and very scattered for the hypotensive group (p = 0.23) compared to the non-hypotensive group, where the changes were significant (p«0.05) and much less scattered

Bibliographic Details

Brayans Becerra-Luna; Raúl Cartas-Rosado; Raúl Martínez-Memije; Oscar Infante-Vázquez; Claudia Lerma; Juan Carlos Sánchez-García; Gabriel Sánchez-Pérez; Héctor Pérez-Grovas; José Manuel Rodríguez-Chagolla; Miguel Cadena-Méndez

MDPI AG

Materials Science; Physics and Astronomy; Engineering; Chemical Engineering; Computer Science

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