Literature DB >> 12574789

Assessment of cardiovascular reactivity by fractal and recurrence quantification analysis of heart rate and pulse transit time.

J E Naschitz1, I Rosner, N Shaviv, I Khorshidi, S Sundick, H Isseroff, M Fields, R M Priselac, D Yeshurun, E Sabo, R Itzhak.   

Abstract

Methods used for the assessment of cardiovascular reactivity are flawed by nonlinear dynamics of the cardiovascular responses to stimuli. In an attempt to address this issue, we utilized a short postural challenge, recorded beat-to-beat heart rate (HR) and pulse transit time (PTT), assessed the data by fractal and recurrence quantification analysis, and processed the obtained variables by multivariate statistics. A 10-min supine phase of the head-up tilt test was followed by recording 600 cardiac cycles on tilt, that is, 5-10 min. Three groups of patients were studied, each including 20 subjects matched for age and gender--healthy subjects, patients with essential hypertension (HT), and patients with chronic fatigue syndrome (CFS). The latter group was studied on account of the well-known dysautonomia of CFS patients, which served as contrast against the cardiovascular reactivity of the healthy population. A total of 52 variables of the HR and PTT were determined in each subject. The multivariate model identified the best predictors for the assessment of reactivity of healthy subjects vs CFS. Based on these predictors, the "Fractal & Recurrence Analysis-based Score" (FRAS) was calculated: FRAS=76.2+0.04*HR-supine-DET -12.9*HR-tilt-R/L -0.31*HR-tilt-s.d. -19.27*PTT-tilt-R/L -9.42*PTT-tilt-WAVE. The median values and IQR of FRAS in the groups were: healthy=-1.85 (IQR 1.89), hypertensives=+0.52 (IQR 5.78), and CFS=-24.2 (5.34) (HT vs healthy subjects: P=0.0036; HT vs CFS: P<0.0001). Since the FRAS differed significantly between the three groups, it appears likely that the FRAS may recognize phenotypes of cardiovascular reactivity.

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Year:  2003        PMID: 12574789     DOI: 10.1038/sj.jhh.1001517

Source DB:  PubMed          Journal:  J Hum Hypertens        ISSN: 0950-9240            Impact factor:   3.012


  4 in total

1.  Morphology variability analysis of wrist pulse waveform for assessment of arteriosclerosis status.

Authors:  Lisheng Xu; Max Q-H Meng; Xianghua Qi; Kuanquan Wang
Journal:  J Med Syst       Date:  2010-06       Impact factor: 4.460

Review 2.  Pulse transit time by R-wave-gated infrared photoplethysmography: review of the literature and personal experience.

Authors:  Jochanan E Naschitz; Stanislas Bezobchuk; Renata Mussafia-Priselac; Scott Sundick; Daniel Dreyfuss; Igal Khorshidi; Argyro Karidis; Hagit Manor; Mihael Nagar; Elisabeth Rubin Peck; Shannon Peck; Shimon Storch; Itzhak Rosner; Luis Gaitini
Journal:  J Clin Monit Comput       Date:  2004-12       Impact factor: 2.502

3.  Recurrence Quantitative Analysis of Wavelet-Based Surrogate Data for Nonlinearity Testing in Heart Rate Variability.

Authors:  Martín Calderón-Juárez; Gertrudis Hortensia González Gómez; Juan C Echeverría; Héctor Pérez-Grovas; Eduardo Quintanar; Claudia Lerma
Journal:  Front Physiol       Date:  2022-02-09       Impact factor: 4.566

4.  Recurrence quantification analysis to characterize cyclical components of environmental elemental exposures during fetal and postnatal development.

Authors:  Paul Curtin; Austen Curtin; Christine Austin; Chris Gennings; Kristiina Tammimies; Sven Bölte; Manish Arora
Journal:  PLoS One       Date:  2017-11-07       Impact factor: 3.240

  4 in total

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