Nonlinear heart rate dynamics: Circadian profile and influence of age and gender

Vandeput, Steven; Verheyden, Bart; Aubert, André; Huffel, Sabine Van

doi:10.1016/j.medengphy.2011.07.004

Cited by 37 publications

(48 citation statements)

References 55 publications

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“…These findings suggest that the magnitude of the HP changes became smaller and HP dynamics turned out to be more regular and predictable as a function of age. These results are in agreement with previous studies regardless of whether they are based on entropy rates [14,15,17,18,22,23,28,34] or on different metrics [2,13,15,16,19,22,23,29,34].…”

Section: Complexity Of the Hp Variability At Rest: Aging And Gender Esupporting

confidence: 93%

“…This observation is in agreement with the conclusion drawn by a recently proposed symbolic analysis approach [19]. Some studies using different nonlinear HP variability indexes detected the gender dependency of the relation of cardiac control complexity to age [13,16,17] but they rejected the statement that women have a significantly steeper negative relation with age than men. This discrepancy might be mostly the effect of the calculation of a biased entropy rate (i.e., ApEn) that might limit the statistical power in distinguishing groups [35].…”

Section: Complexity Of the Hp Variability At Rest: Aging And Gender Esupporting

confidence: 88%

“…These changes are mirrored by a reduction in heart period (HP) variability [2][3][4][5][6][7][8][9], by an increase of systolic blood pressure (SAP) variability [10][11][12], and by a reduction in complexity of physiological dynamics [2][3][4][13][14][15][16][17][18][19][20][21][22][23]. Although the abovementioned studies indicate that aging reduces the complexity of the cardiovascular control and prove the gender dependence, it is still unclear whether the complexity reduction and the gender relation are similarly observable from HP and SAP variabilities and if it persists during a cardiovascular control challenge.…”

Section: Introductionmentioning

confidence: 99%

“…Although the abovementioned studies indicate that aging reduces the complexity of the cardiovascular control and prove the gender dependence, it is still unclear whether the complexity reduction and the gender relation are similarly observable from HP and SAP variabilities and if it persists during a cardiovascular control challenge. Indeed, protocols assessing the effect of aging on the complexity of the cardiovascular control are mainly limited to the evaluation of the complexity of the HP variability [13][14][15][19][20][21][22][23] and mostly do not deliberately challenge the cardiovascular control according to an experimental maneuver or pharmacological intervention [13][14][15][16][17][18][19]22,23]. In addition, those studies challenging autonomic nervous system regulation have a limited power because age ranges are inadequate [20] or they are mainly based on biased indexes of complexity such as approximate entropy [21].…”

Section: Introductionmentioning

confidence: 99%

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Effect of the Postural Challenge on the Dependence of the Cardiovascular Control Complexity on Age

Catai

Takahashi

Perseguini

et al. 2014

Entropy

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Short-term complexity of heart period (HP) and systolic arterial pressure (SAP) was computed to detect age and gender influences over cardiovascular control in resting supine condition (REST) and during standing (STAND). Healthy subjects (n = 110, men = 55) were equally divided into five groups (21-30; 31-40; 41-50; 51-60; and 61-70 years of age). HP and SAP series were recorded for 15 min at REST and during STAND. A normalized complexity index (NCI) based on conditional entropy was assessed. At REST we found that both NCIHP and NCISAP decreased with age in the overall population, but only women were OPEN ACCESSEntropy 2014, 16 6687 responsible for this trend. During STAND we observed that both NCIHP and NCISAP were unrelated to age in the overall population, even when divided by gender. When the variation of NCI in response to STAND (ΔNCI = NCI at REST-NCI during STAND) was computed individually, we found that ΔNCIHP progressively decreased with age in the overall population, and women were again responsible for this trend. Conversely, ΔNCISAP was unrelated to age and gender. This study stresses that the complexity of cardiovascular control and its ability to respond to stressors are more importantly lost with age in women than in men.

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Section: Complexity Of the Hp Variability At Rest: Aging And Gender Esupporting

confidence: 93%

Section: Complexity Of the Hp Variability At Rest: Aging And Gender Esupporting

confidence: 88%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effect of the Postural Challenge on the Dependence of the Cardiovascular Control Complexity on Age

Catai

Takahashi

Perseguini

et al. 2014

Entropy

View full text Add to dashboard Cite

show abstract

“…Female gender seems to result in a lower total variability (Vandeput et al 2012), whereas vagal modulation has been found to be similar (Moodithaya & Avadhany, 2012) or higher (Fukusaki et al 2000;Huikuri et al 1996) when compared to men. These differences in HRV are probably caused by lower sympathetic and higher vagal control of the heart in women (Carter et al 2003).…”

Section: Factors Affecting Hrvmentioning

confidence: 88%

Heart rate variability is related to training load variables in interval running exercises

Kaikkonen¹,

Hynynen

Mann

et al. 2011

Eur J Appl Physiol

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From Pharmacogenomics and Systems Biology to Personalized Care: A Framework of Systems and Dynamical Medicine

Yan¹

2014

Methods in Molecular Biology

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With the integration of pharmacogenomics and systems biology, personalized medicine would be possible by switching the gear from the reductionism-based and disease-focused medical system toward a dynamical systems-based and human-centric health care. Comprehensive models are needed to represent the properties of complex adaptive systems (CASs) to elucidate the complexity in health and diseases, including the features of emergence, nonlinearity, self-organization, and adaptation. As all diseases have the dynamical elements, nonlinear time-series analyses are necessary to characterize the system dynamics at various levels to elucidate the physiological and pathological rhythms, oscillations, and feedback loops. Such analyses can help detect patterns across multiple scales in both the spatial (e.g., from molecules to cells, from organisms to psychosocial environments) and the temporal (e.g., from nanoseconds to hours, from years to decades) dimensions. Based on such understanding, systems and dynamical medicine can be developed with the emphasis on the whole systems that change over time to address the nonlinearity and interconnectivity toward a holistic and proactive care. Accurate and robust biomarkers with predictive values can be discovered to reflect the systemic conditions and disease stages. Network and dynamical models may support individualized risk analysis, presymptomatic diagnosis, precise prognosis, and integrative interventions. Systems and dynamical medicine may provide the root for the achievement of predictive, preventive, personalized, and participatory (P4) medicine.

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Nonlinear heart rate dynamics: Circadian profile and influence of age and gender

Cited by 37 publications

References 55 publications

Effect of the Postural Challenge on the Dependence of the Cardiovascular Control Complexity on Age

Effect of the Postural Challenge on the Dependence of the Cardiovascular Control Complexity on Age

Heart rate variability is related to training load variables in interval running exercises

From Pharmacogenomics and Systems Biology to Personalized Care: A Framework of Systems and Dynamical Medicine

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