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VISUALISATION OF CARDIOVASCULAR DYSREGULATION IN YOUNG
PATIENTS WITH TYPE 1 DIABETES MELLITUS BY POINCARÉ PLOT
1
MICHAL JAVORKA, 2 JANA JAVORKOVA, 1 INGRID TONHAJZEROVA,
1
KAMIL JAVORKA
1
Department of Physiology, Comenius University, Jessenius Faculty of Medicine,
2
Paediatric Clinic, Comenius University, Jessenius Faculty of Medicine,Faculty Hospital, Martin, Slovakia
A b s t r a c t
The noninvasive assessment of spontaneous physiological parameters variations can provide valuable information
about control systems involved in their complex regulation. Time series analysis is usually performed in time and frequency
domains – the so called linear methods. Inspired by effort to apply nonlinear time series analysis into cardiovascular
variability signals, the aim of this study was to compare heart rate and blood pressure variabilities (HRV and
BPV) between young patients with type 1 diabetes mellitus (DM) and control subjects using Poincaré plot.
Patients with type 1 DM (10 females, 7 males) aged 12.9 – 31.5 years (mean ± SEM: 22.4 ± 1.0 years) were investigated.
The control group consisted of 17 healthy probands matched for sex and age. The HRV and BPV were analysed
in time domain (mean, standard deviation - SD) and using quantitative analysis of Poincaré plot pattern measures during
supine rest.
In young patients with type 1 DM, significant reduction of all measured Poincaré plot parameters constructed from
R-R intervals was found. However, no significant difference between groups in BPV Poincaré plot measures was observed.
In conclusion, HRV Poincaré plot was able to reveal beat-to-beat HRV abnormalities. Poincaré plot can provide information
potentially usable for diagnosis and prognosis in visually understandable manner. We suggest that parasympathetic
dysfunction in cardiac regulation occurs earlier than dysregulation of sympathetic control of the vessels in young
diabetics.
K e y w o r d s : heart rate variability, blood pressure variability, diabetes mellitus, Poincaré plot
INTRODUCTION
The noninvasive assessment of spontaneous physiological parameters variations in time can
provide valuable information about control systems involved in their complex regulation. Repeatedly
measured values of any assessed parameter form time series that can be regarded as a signal
encompassing information about structure and status of dynamical system that generates
and modifies given parameter. Time series analysis is able to acquire data about normal dynamical
system as well as system changes during pathological circumstances with clinically important
applications (diagnosis, prognosis) (1, 2).
Time series analysis of physiological parameters is usually performed in time and frequency
domains – the so called linear methods. Time domain parameters based on basic statistical
parameters (e.g. mean value, standard deviation) provide summarized information on short- and
long-term variability in time series, but did not comprise information concerning oscillations`
patterns (3). These parameters are sensitive to artefacts and require gaussian distribution of
measured parameter. Time series analysis in frequency domain (spectral analysis) enables to
quantify cyclic oscillations (e.g. respiratory sinus arrhythmia). The nonperiodic oscillations are
ignored and usually regarded as a noise (1,4).
Cardiovascular control system components (baroreceptors, chemoreceptors, sympathetic
and parasympathetic nervous system, cardiac pacemaker, smooth muscles of blood vessels,
etc.) interact in a complex manner. These interactions are usually not linear – output is not proportional
to input (e.g. heart rate changes are not directly proportional to blood pressure
changes). The nonlinear systems are able to generate very complex signals that cannot be distinguished
from noise using linear time series analysis tools. Therefore, there is an ongoing
Address for correspondence:
Michal Javorka, MD, PhD, Department of Physiology, JLF UK
Malá Hora 4, 037 54 Martin, Slovakia
Phone:++421 43 41314 26, fax: ++ 421 43 42222 60, e-mail: mjavorka@jfmed.uniba.sk