Decrease in the heart rate complexity prior to the onset of atrial fibrillation

Tuzcu, Volkan; Nas, Selman; Börklü, Tülay; Ugur, Ahmet

doi:10.1093/europace/eul031

Cited by 60 publications

(53 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Changes in the entropies (ApEn, SampEn) were already reported in some cardiovascular researches [21][22][23][24], postural control investigations [25,26], physical activity measures [27,28] and in analysis of cardiodepressive vasovagal syncope [24]. The presented analysis of changes in the complexity of joint signals of ECG, ICG and blood pressure during passive provocation of the neuro-cardiogenic reaction will add to further understanding of the course and mechanism of vasovagal syndrome.…”

Section: Introductionmentioning

confidence: 69%

“…The in-depth description of the comparisons of both of these statistics can be found in the literature [20]. Despite elementary differences between ApEn and SampEn, both statistics are extensively used in cardiovascular physiology [20,22,23,[27][28][29][30][31][33][34][35][36][40][41][42]. In this paper we also show the possible applications of ApEn (m, r, N) and SampEn (m, r, N) for the analysis of physiological signals.…”

Section: Approximate Entropy and Sample Entropymentioning

confidence: 99%

See 1 more Smart Citation

Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Buszko

Piątkowska

Koźluk

et al. 2017

Entropy

View full text Add to dashboard Cite

This paper presents an application of Approximate Entropy (ApEn) and Sample Entropy (SampEn) in the analysis of heart rhythm, blood pressure and stroke volume for the diagnosis of vasovagal syndrome. The analyzed biosignals were recorded during positive passive tilt tests-HUTT(+). Signal changes and their entropy were compared in three main phases of the test: supine position, tilt, and pre-syncope, with special focus on the latter, which was analyzed in a sliding window of each signal. In some cases, ApEn and SampEn were equally useful for the assessment of signal complexity (p < 0.05 in corresponding calculations). The complexity of the signals was found to decrease in the pre-syncope phase (SampEn (RRI): 1.20-0.34, SampEn (sBP): 1.29-0.57, SampEn (dBP): 1.19-0.48, SampEn (SV): 1.62-0.91). The pattern of the SampEn (SV) decrease differs from the pattern of the SampEn (sBP), SampEn (dBP) and SampEn (RRI) decrease. For all signals, the lowest entropy values in the pre-syncope phase were observed at the moment when loss of consciousness occurred.

show abstract

Section: Introductionmentioning

confidence: 69%

Section: Approximate Entropy and Sample Entropymentioning

confidence: 99%

Entropy in Investigation of Vasovagal Syndrome in Passive Head Up Tilt Test

Buszko

Piątkowska

Koźluk

et al. 2017

Entropy

View full text Add to dashboard Cite

show abstract

“…Reduced approximate and sample entropy values of heartbeat fluctuations have been found to precede spontaneous episodes of atrial fibrillation in patients without structural heart disease ( Vikman et al 1999;Tuzcu et al 2006). Furthermore, the values of approximate entropy before the onset of atrial fibrillation were lower than the values obtained from matched healthy control subjects.…”

Section: (B ) Physiological Background Of Entropy Measures Of Rr Intementioning

confidence: 94%

“…The sample entropy is a measure similar to the approximate entropy. However, it excludes self-matches and as a consequence reduces the superimposed bias (Richman & Moorman 2000;Tuzcu et al 2006;Heffernan et al 2007). It is also less dependent on the length of the time series.…”

Section: (A ) Measures Of Entropymentioning

confidence: 99%

Clinical impact of evaluation of cardiovascular control by novel methods of heart rate dynamics

Huikuri

Perkiömäki

Maestri

et al. 2009

Phil. Trans. R. Soc. A.

165

124

View full text Add to dashboard Cite

Heart rate variability (HRV) has been conventionally analysed with time-and frequencydomain methods, which measure the overall magnitude of RR interval fluctuations around its mean value or the magnitude of fluctuations in some predetermined frequencies. Analysis of heart rate dynamics by novel methods, such as heart rate turbulence after ventricular premature beats, deceleration capacity of heart rate and methods based on chaos theory and nonlinear system theory, have gained recent interest. Recent observational studies have suggested that some indices describing nonlinear heart rate dynamics, such as fractal scaling exponents, heart rate turbulence and deceleration capacity, may provide useful prognostic information in various clinical settings and their reproducibility may be better than that of traditional indices. For example, the short-term fractal scaling exponent measured by the detrended fluctuation analysis method has been shown to predict fatal cardiovascular events in various populations. Similarly, heart rate turbulence and deceleration capacity have performed better than traditional HRV measures in predicting mortality in post-infarction patients. Approximate entropy, a nonlinear index of heart rate dynamics, which describes the complexity of RR interval behaviour, has provided information on the vulnerability to atrial fibrillation. There are many other nonlinear indices which also give information on the characteristics of heart rate dynamics, but their clinical usefulness is not as well established. Although the concepts of nonlinear dynamics, fractal mathematics and complexity measures of heart rate behaviour, heart rate turbulence, deceleration capacity in relation to cardiovascular physiology or various cardiovascular events are still far away from clinical medicine, they are a fruitful area for research to expand our knowledge concerning the behaviour of cardiovascular oscillations in normal healthy conditions as well as in disease states.

show abstract

“…As we know that SamEn is a measure of complexity of the biological signal and here SamEn is lower in IUGR1 and higher in the other two groups. Normally AF patients have lower SamEn [27]. Table 5 summarises the results of 15 min pre-awake as we compare normal with IUGR1 and IUGR2, as well as IUGR1 against IUGR2.…”

Section: Discussion:-mentioning

confidence: 99%