Does heart rate variability improve prediction of failed extubation in preterm infants?

Abstract Background Prematurity and its respective comorbidities may result in longer periods of mechanical ventilation in intensive care units (ICU). A method for the assessment of organic maturity would be useful for this population. Heart rate variability (HRV), as an indicator of homeostasis, is a well-established tool for this approach. The objective of the study was to assess HRV in intubated preterm infants in ICU immediately prior to extubation and correlate HRV with clinical evaluation outcomes. Methods A total of 46 preterm infants, 13 (28.2%) males, were prospectively studied and divided into a group with failed extubation (FEG: n=11) and a group with successful extubation (SEG: n=35). HRV was evaluated in time, frequency and nonlinear domains with a Polar RS800 device. HRV measurements were assessed with Kubios HRV Premium Software and statistically analyzed with the StatsDirect Statistical Software, version 1.9.2015 (2002). P<0.05 values were considered as statistically significant. Results There were no significant differences between heart rate variables of failed and successful extubation when analyzing the total group. However, the analysis of the sub-group of preterm infants weighing less than 1000 g showed a clear differentiation between the groups, when the nonlinear variables (approximate entropy, sample entropy and multiscale entropy 1, 2 and 3) were used, demonstrating that the group with successful extubation shows greater complexity and, therefore, relatively greater autonomic stability. Conclusion HRV was effective in predicting failed extubation in preterm infants when evaluated in a nonlinear domain and in preterm infants weighing less than 1000 g.

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Nonlinearities of heart rate variability in animal models of impaired cardiac control: contribution of different time scales

Journal of Applied Physiology ◽

10.1152/japplphysiol.00059.2017 ◽

2017 ◽

Vol 123 (2) ◽

pp. 344-351 ◽

Cited By ~ 14

Author(s):

Luiz Eduardo Virgilio Silva ◽

Renata Maria Lataro ◽

Jaci Airton Castania ◽

Carlos Alberto Aguiar Silva ◽

Helio Cesar Salgado ◽

...

Keyword(s):

Nonlinear Dynamics ◽

Heart Rate ◽

Heart Rate Variability ◽

Time Scales ◽

Multiscale Entropy ◽

Time Frequency ◽

Cardiac Control ◽

Long Time ◽

Nonlinear Features ◽

Short Time

Heart rate variability (HRV) has been extensively explored by traditional linear approaches (e.g., spectral analysis); however, several studies have pointed to the presence of nonlinear features in HRV, suggesting that linear tools might fail to account for the complexity of the HRV dynamics. Even though the prevalent notion is that HRV is nonlinear, the actual presence of nonlinear features is rarely verified. In this study, the presence of nonlinear dynamics was checked as a function of time scales in three experimental models of rats with different impairment of the cardiac control: namely, rats with heart failure (HF), spontaneously hypertensive rats (SHRs), and sinoaortic denervated (SAD) rats. Multiscale entropy (MSE) and refined MSE (RMSE) were chosen as the discriminating statistic for the surrogate test utilized to detect nonlinearity. Nonlinear dynamics is less present in HF animals at both short and long time scales compared with controls. A similar finding was found in SHR only at short time scales. SAD increased the presence of nonlinear dynamics exclusively at short time scales. Those findings suggest that a working baroreflex contributes to linearize HRV and to reduce the likelihood to observe nonlinear components of the cardiac control at short time scales. In addition, an increased sympathetic modulation seems to be a source of nonlinear dynamics at long time scales. Testing nonlinear dynamics as a function of the time scales can provide a characterization of the cardiac control complementary to more traditional markers in time, frequency, and information domains. NEW & NOTEWORTHY Although heart rate variability (HRV) dynamics is widely assumed to be nonlinear, nonlinearity tests are rarely used to check this hypothesis. By adopting multiscale entropy (MSE) and refined MSE (RMSE) as the discriminating statistic for the nonlinearity test, we show that nonlinear dynamics varies with time scale and the type of cardiac dysfunction. Moreover, as complexity metrics and nonlinearities provide complementary information, we strongly recommend using the test for nonlinearity as an additional index to characterize HRV.

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USING DIFFERENT ENTROPIES TO ANALYZE THE HEART RATE VARIABILITY OF CONGESTIVE HEART FAILURE PATIENTS

Biomedical Engineering Applications Basis and Communications ◽

10.4015/s1016237211002530 ◽

2011 ◽

Vol 23 (04) ◽

pp. 253-260 ◽

Cited By ~ 2

Author(s):

Ren-Guey Lee ◽

Chun-Chieh Hsiao ◽

Chieh-Yi Kao

Keyword(s):

Heart Failure ◽

Heart Rate ◽

Congestive Heart Failure ◽

Heart Rate Variability ◽

Analysis Of Variance ◽

Human Body ◽

Approximate Entropy ◽

Young Group ◽

Multiscale Entropy ◽

Heart Failure Patients

The purpose of this paper is to show the influence of congestive heart failure (CHF) on heart by using different entropies to apply on the group of patients with CHF and normal group. Three different entropies are used: approximate entropy (ApEn), multiscale entropy (MSE), and base-scale entropy (BsEn). We use these three entropies to measure the complexity of the heart rate variability (HRV) and also use analysis of variance (ANOVA) to analyze the result of entropies to discuss the feasibility of recognizing CHF patients by utilizing entropies. With the analysis results of different entropies, the influence of CHF on heart has also been clearly demonstrated. The results on the approximate entropy show that the normal young group has a higher approximate entropy value while the CHF group has a lower value. This can be explained as a healthy, strong heart that can change its heart rate freely to adapt the change of the environment or the needs of the human body, therefore the HRV will be more complex. From the ANOVA results of approximate entropy, it can be observed that the F value is larger than 1, but is still small. In other words, the approximate entropy can be used to distinguish the three groups, the effect is, however, not good. It is hard to recognize a CHF patient by using approximate entropy.

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Transient effects of forebrain ischemia on fetal heart rate variability in fetal sheep

AJP Regulatory Integrative and Comparative Physiology ◽

10.1152/ajpregu.00032.2021 ◽

2021 ◽

Author(s):

Yoshiki Maeda ◽

Christopher A. Lear ◽

Michael J. Beacom ◽

Joanne O Davidson ◽

Kelly Q Zhou ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Fetal Heart Rate ◽

Fetal Heart ◽

Sample Entropy ◽

Forebrain Ischemia ◽

Fetal Sheep ◽

Time Frequency ◽

Bilateral Carotid ◽

Fetal Heart Rate Variability

Fetal heart rate variability (FHRV) is a key index of antenatal and intrapartum fetal well-being. FHRV is well established to be mediated by both arms of the autonomic nervous system, but it remains unknown whether higher centers in the forebrain contribute to FHRV. We tested the hypothesis that selective forebrain ischemia would impair the generation of FHRV. 16 chronically instrumented near-term fetal sheep were subjected to either forebrain ischemia induced by bilateral carotid occlusion or sham-ischemia for 30 min. Time, frequency and non-linear measures of FHRV were assessed during and for seven days after ischemia. Ischemia was associated with profound suppression of electroencephalographic (EEG) power, which remained suppressed throughout the recovery period (p<0.001). During the first 5 min of ischemia, multiple time and frequency domain measures were increased (all p<0.05) before returning back to sham levels. A delayed increase in Sample Entropy was observed during ischemia (p<0.05). For the first 3 h after ischemia there was moderate suppression of two measures of FHRV (very-low frequency power and the standard deviation of RR-intervals, both p<0.05) and increased Sample Entropy (p<0.05). Thereafter all measures of FHRV returned to control levels. In conclusion, profound forebrain ischemia sufficient to lead to severe neural injury had only transient effect on multiple measures of FHRV. These findings suggest that the forebrain makes a limited contribution to FHRV. FHRV therefore primarily originates in the hindbrain and is unlikely to provide meaningful information on forebrain neurodevelopment or metabolism.

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The Relationship Between Blood Perfusion in the Lower Extremities and Heart Rate Variability at Different Positions

Frontiers in Physiology ◽

10.3389/fphys.2021.656527 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shuyong Jia ◽

Qizhen Wang ◽

Hongyan Li ◽

Xiaojing Song ◽

Shuyou Wang ◽

...

Keyword(s):

Heart Rate ◽

Blood Flow ◽

Heart Rate Variability ◽

Body Position ◽

Lower Extremities ◽

Blood Perfusion ◽

Sample Entropy ◽

Multiscale Entropy ◽

Local Blood Flow ◽

The Relationship

Previous studies have explored the relationship between the complexity of local blood flow signals and heart rate variability (HRV) under different thermal stimulations. However, the relationship between the complexity of local blood flow signals and HRV in different positions is not clear. In this study, healthy participants were placed in different body positions. The bilateral blood flux and ECG were monitored, and refined composite multiscale entropy (RC MSE) and refined composite multiscale fuzzy entropy (RC MFE) were used to measure the complexity of the local blood flux. The sample entropy was calculated to evaluate the HRV complexity. The change of body position did not affect the time domain or frequency domain of HRV, but did reverse the blood flux laterality of the lower extremities. Furthermore, there was a negative correlation between the complexity of right-side blood flux and sample entropy of HRV when the participant was in the -10 degrees position. These results provide a new perspective of the relationship between skin blood flux signals and cardiac function.

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AGE-BASED ANALYSIS OF HEART RATE VARIABILITY (HRV) FOR PATIENTS WITH CONGESTIVE HEART FAILURE

Fractals ◽

10.1142/s0218348x21501358 ◽

2021 ◽

pp. 2150135

Author(s):

HAMIDREZA NAMAZI ◽

DUMITRU BALEANU ◽

ONDREJ KREJCAR

Keyword(s):

Heart Failure ◽

Heart Rate ◽

Congestive Heart Failure ◽

Heart Rate Variability ◽

Fractal Dimension ◽

Age Groups ◽

Approximate Entropy ◽

Sample Entropy ◽

Heart Activity ◽

Complexity Measures

It is known that heart activity changes during aging. In this paper, we evaluated alterations of heart activity from the complexity point of view. We analyzed the variations of heart rate of patients with congestive heart failure that are categorized into four different age groups, namely 30–39, 50–59, 60–69, and 70–79 years old. For this purpose, we employed three complexity measures that include fractal dimension, sample entropy, and approximate entropy. The results showed that the trend of increment of subjects’ age is reflected in the trend of increment of the complexity of heart rate variability (HRV) since the values of fractal dimension, approximate entropy, and sample entropy increase as subjects get older. The analysis of the complexity of other physiological signals can be further considered to investigate the variations of activity of other organs due to aging.

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Characterization of behavioral activation in non-pathological subjects through Heart Rate Variability monovariate and multivariate multiscale entropy analysis

2014 8th Conference of the European Study Group on Cardiovascular Oscillations (ESGCO) ◽

10.1109/esgco.2014.6847556 ◽

2014 ◽

Cited By ~ 1

Author(s):

Mimma Nardelli ◽

Gaetano Valenza ◽

Ioana A. Cristea ◽

Claudio Gentili ◽

Carmen Cotet ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Behavioral Activation ◽

Multiscale Entropy ◽

Entropy Analysis ◽

Multivariate Multiscale Entropy

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Factors Affecting Heart Rate Variability in Preterm Infants

PEDIATRICS ◽

10.1542/peds.65.1.50 ◽

1980 ◽

Vol 65 (1) ◽

pp. 50-56 ◽

Cited By ~ 1

Author(s):

Luis A. Cabal ◽

Bijan Siassi ◽

Bernardino Zanini ◽

Joan E. Hodgman ◽

Edward E. Hon

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Birth Weight ◽

Preterm Infants ◽

Gestational Age ◽

Distress Syndrome ◽

Good Prognosis ◽

Factors Affecting ◽

Rate Level ◽

Heart Rate Level

Neonatal heart rate variability (NHRV) was studied in 92 preterm infants (birth weight, 750 to 2,500 gm; gestational age, 28 to 36 weeks). Each infant was monitored continuously during the first 6 hours and for one hour at 24, 48, and 168 hours of life. During each hour NHRV was quantified and related to the following parameters: sex, gestational age, postnatal age, heart rate, and the presence and severity of respiratory distress syndrome (RDS). NHRV in healthy preterm infants was inversely related to heart rate level and directly related to the infant's postnatal age. In healthy babies with gestations of 30 to 36 weeks there was no significant correlation between NHRV and gestation. Decrease in NHRV was significantly related to the severity of RDS, and the reappearance of NHRV in infants with RDS was associated with a good prognosis. Decreased NHRV significantly differentiated the infants with RDS who survived after the fifth hour of life. The data reveal that NHRV (1) should be corrected for heart rate level and postnatal age; (2) is decreased in RDS; and (3) can be used as an indicator of morbidity and mortality in preterm infants with RDS.

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