Asymmetrical properties of heart rate variability in type 1 diabetes

Guzik, Przemysław; Piskorski, Jarosław; Contreras, Paola; Migliaro, Eduardo R.

doi:10.1007/s10286-010-0057-7

Cited by 38 publications

(34 citation statements)

References 6 publications

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“…Similar results were also observed in patients with DM1 ≥40 years of age (8,18), and in young subjects with a mean age of 22 years (34).…”

Section: Discussionsupporting

confidence: 77%

“…In the control group, the visual analysis of Poincaré plot showed a greater beat-to-beat dispersion and long-term RR dispersion which is representative of a normal ANS behaviour (10,16). Similar results were found in studies that also qualitatively analyzed the Poincaré plot in individuals with DM1 (8,18).…”

Section: ) Rr(n) (Ms) On the X-axis And Rr (N+1) (Ms) On The Y-axissupporting

confidence: 83%

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Geometric indexes of heart rate of variability identifies autonomic alterations in young patients with type 1 diabetes mellitus

Souza¹,

Pastre²

2016

Curr Res Cardiol

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ObjeCtiveS:To compare autonomic modulation in young patients with type 1 diabetes mellitus (DM1) (n=20) and healthy control subjects (n=23) using geometric indexes of heart rate variability (HRV) associated with linear domains of time and frequency; and to verify correlations between geometric indexes and those obtained by the time and the frequency domain of diabetic individuals. MethOdS: Heart rate was recorded as beat-to-beat with subjects supine for 30 min. The following indexes were calculated: RRtri, TINN, Poincaré plot, SD1, SD2, SD1/SD2, RMSSD, SDNN, LF and HF (ms²/un) (DM1) (1) because it affects the fibres of the autonomic nerves of the heart and blood vessels, causing heart rate abnormalities and vascular dynamic impairments (2,3), leading to increased mortality (4,5).Changes in the autonomic modulation of DM1 were previously described through heart rate variability (HRV) (6-9), a noninvasive assessment method that measures the oscillation of intervals between consecutive heart beats (RR), which are related to influences from the autonomic nervous system (ANS) on the sinus node (10,11).Most studies that assessed autonomic modulation by HRV included populations with type 2 diabetes mellitus (9,12-15), a population that normally have associated comorbidities that could interfere in autonomic modulation (12). Also, these studies used linear methods of analysis of frequency and time domains (14,15), which present limitations as stationary requirements, and show more sensitivity to interference and ectopic beats when compared with nonlinear methods (16). Nonlinear methods are based on chaos theory and may enable better discrimination between normal and abnormal ANS physiology (6). For example, the Poincaré plot is a method used for geometric and nonlinear analysis of the autonomic modulation (16-18). A previous study involving type 2 diabetic individuals assessed different methods of HRV and reported that geometric methods are more reliable for evaluating the presence of an autonomic diabetic disease (19), and studies that analyze this type of indexes in DM1 population were not deeply explored.Therefore, geometric methods could identify autonomic changes and help to plan a better treatment strategy in DM1 patients. Thus, the aim of the present study was: to compare HRV indexes obtained by geometric methods (RRtri, TINN and Poincaré plot -SD1, SD2 and SD1/SD2), associated to indexes of time domain (RMSSD and SDNN) and frequency domain (LF, HF (ms²/un) and LF/HF), of individuals with DM1 and healthy control subjects; and to verify correlations between geometric indexes and those obtained by the time and the frequency domain of diabetic individuals. MethOdS SubjectsThe present study included 43 young adults who were divided into two groups: the DM1 group (n=20 [nine men, 11 women]) with a mean (± SD) age 22.05±4.35 years, with 10.60±4.81 years of DM1 diagnosis, and a control group with 23 healthy subjects (15 men, eight women) mean age 21.69±2.42 years.The inclusion criteria were absence of cardiorespirato...

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“…Similar results were also observed in patients with DM1 ≥40 years of age (8,18), and in young subjects with a mean age of 22 years (34).…”

Section: Discussionsupporting

confidence: 77%

Section: ) Rr(n) (Ms) On the X-axis And Rr (N+1) (Ms) On The Y-axissupporting

confidence: 83%

Geometric indexes of heart rate of variability identifies autonomic alterations in young patients with type 1 diabetes mellitus

Souza¹,

Pastre²

2016

Curr Res Cardiol

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“…34 We have also reported on the reduced expression of short-term heart rate asymmetry in patients with type 1 diabetes of long duration of at least 25 years in whom diabetic autonomic neuropathy is a very common finding. 21 Additionally, we have reported on the significant correlation between various measures of heart rate asymmetry and indices of HRV and baroreflex function, but not blood pressure variability. 33 Further, we have described another phenomenon of the asymmetry of systolic blood pressure variability in healthy people, and although short-term heart rate asymmetry was also present in the same persons there was no correlation between both phenomena.…”

Section: Discussionmentioning

confidence: 90%

Asymmetry of the Variability of Heart Rate and Conduction Time Between Atria and Ventricles

Guzik

Zuchowski

Błaszyk

et al. 2013

Circ J

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“…[18][19][20] Heart rate asymmetry, although independent of blood pressure asymmetry, is probably related to baroreflex, which is supported by the observation that heart rate asymmetry is correlated with measures of baroreflex function. 32 Porta et al 33 showed that asymmetrical features of HRV change during sympathetic provocation like head-up tilting and that heart rate asymmetry expression increases during the day compared with night, both in healthy people and patients with congestive heart failure. 17,24 Recently, we showed that heart rate asymmetry is reduced in patients with type 1 diabetes of at least 25-year duration of the disease both in 10-min resting and in 24-h ambulatory Holter ECG recordings.…”

Section: Discussionmentioning

confidence: 99%

Asymmetric features of short-term blood pressure variability

et al. 2010

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Prolongations of cardiac cycles have a significantly larger contribution to short-term heart rate variability than shorteningsthis is called heart rate asymmetry. Our aim is to establish the existence of blood pressure asymmetry phenomenon, which has not been done so far. We used 30-min resting continuous recordings of finger pressure waveforms from 227 healthy young volunteers (19-31 years old; 97 female), and performed Poincaré plot analysis of systolic blood pressure (SBP) to quantify the effect. Median contribution of SBP increases (C i ) to short-term blood pressure variability was 52.8% (inter-quartile range: 50.9-55.1%) and median number of SBP increases (N i ) was 48.8% (inter-quartile range: 47.2-50.1%). The C i 450% was found in 82% (Po0.0001; binomial test) and N i o50% in 75% (Po0.0001) of the subjects. Although SBP increases are significantly less abundant than reductions, their contribution to short-term blood pressure variability is significantly larger, which means that short-term blood pressure variability is asymmetric. SBP increases and reductions have unequal contribution to short-term blood pressure variability at supine rest in young healthy people. As this asymmetric behavior of blood pressure variability is present in most of the healthy studied people at rest, it can be concluded that blood pressure asymmetry is a physiological phenomenon. Keywords: blood pressure asymmetry; blood pressure variability; heart rate asymmetry; heart rate variability; sympatheticparasympathetic balance INTRODUCTIONBoth heart rate variability (HRV) and blood pressure variability (BPV) are related to autonomic activity and provide some information on the mechanisms regulating the cardiovascular system. 1-6 Various physiological oscillations (for example, respiration, Mayer waves) and cardiovascular reflexes (for example, arterial and cardiopulmonary baroreflexes) are responsible for HRV and BPV. [1][2][3][4][6][7][8][9] A number of mathematical approaches like the time-domain analysis, spectral analysis, graphic or nonlinear methods have been applied in the analysis of HRV and BPV. [1][2][3][4][5][6][9][10][11][12][13] Even though heart rate and blood pressure are different cardiovascular signals, very often the same techniques are used for the quantification of both HRV and BPV. 1,[3][4][5][6][7][8][9]13 On the other hand, descriptors of baroreflex function like baroreflex sensitivity and baroreflex delay (the delay of sinus node response to a change in blood pressure) reflect the blood pressure influence on heart rate more directly. 3,9,14 Most of the methods applied to the analysis of HRV and BPV look at the changes of the duration of cardiac cycle of sinus origin (RR) intervals or blood pressure, but do not analyze their direction, that is, whether they represent increases or decreases of heart rate or blood

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Asymmetrical properties of heart rate variability in type 1 diabetes

Abstract: Heart rate variability related to heart rate decelerations and accelerations is reduced in patients with type 1 diabetes compared to healthy individuals both in resting 10-min and ambulatory 24-h ECGs.

Cited by 38 publications

References 6 publications

Geometric indexes of heart rate of variability identifies autonomic alterations in young patients with type 1 diabetes mellitus

Geometric indexes of heart rate of variability identifies autonomic alterations in young patients with type 1 diabetes mellitus

Asymmetry of the Variability of Heart Rate and Conduction Time Between Atria and Ventricles

Asymmetric features of short-term blood pressure variability

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