scholarly journals Heart Rate Variability in Adults with Sickle Cell Anemia During a Multitasking Field Test

2021 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Rafael Alexandre de Oliveira Deucher ◽  
Arthur de Sá Ferreira ◽  
Leila Paula Alves da Silva Nascimento ◽  
Mariana Soares da Cal ◽  
Jannis Vasileios Papathanasiou ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sickle Cell ◽  
Sickle Cell Anemia ◽  
Parasympathetic Activity ◽  
High Frequency Component ◽  
Healthy Controls ◽  
Peripheral Muscle ◽  
Sympathovagal Imbalance ◽  
Activity Indices

Background: The integrity of the autonomic nervous system (ANS) is essential for keeping physiological processes stable, even under stress. Since there is growing interest in heart rate variability (HRV) analysis for the noninvasive assessment of the ANS in sickle cell anemia (SCA) patients, we studied the behavior of the ANS in the presence of a stressor that simulates daily-life multitasking, the Glittre ADL test (GA-T). Objectives: To evaluate the involvement of the ANS using HRV in adults with SCA during the GA-T and to quantify the strength of the correlation of HRV with lung and muscle functions. Methods: In this cross-sectional study, 16 adults with SCA and 12 healthy controls without sickle cell disease underwent HRV assessment during the GA-T, pulmonary function tests (spirometry, diffusing capacity for carbon monoxide (DLCO), and respiratory muscle testing). Peripheral muscle function [handgrip strength (HGS) and quadriceps strength (QS)] were also measured. Results: Compared to the healthy controls, adults with SCA showed lower HRV, with worse parasympathetic modulation due to reductions in the following indices: the root-mean-square difference of successive normal iRRs (iRR) (RMSSD); the percentage of pairs of consecutive iRRs whose difference is > 50 m (pNN50); the high-frequency component of heart rate variability (HF); and the standard deviation of instantaneous beat-to-beat variability (SD1) (P < 0.001 for all). Compared to healthy controls, individuals with SCA showed greater sympathovagal imbalance (higher ratio between low-frequency and HF components) and lower complexity of the ANS (lower approximate entropy). The GA-T time was correlated with parasympathetic activity indices: RMSSD (rs = -0.650, P < 0.01); pNN50 (rs = -0.932, P < 0.0001), HF (rs = -0.579, P < 0.01), and SD1 (rs = -0.814, P < 0.0001). Correlations between parasympathetic activity indices and DLCO, HGS, and QS measures were also significant. Conclusions: Adults with SCA have low HRV, with low parasympathetic activity, sympathovagal imbalance, and abnormal ANS complexity. In addition, lower HRV is associated with longer GA-T time, greater impairment of pulmonary diffusion, and greater muscle strength dysfunction.

scholarly journals Association of cardiac autonomic modulation with physical and clinical features of young people with type 1 diabetes

2016 ◽  
Vol 27 (1) ◽  
pp. 37-45 ◽  
Author(s):  
Anne K. F. Silva ◽  
Diego G. D. Christofaro ◽  
Franciele M. Vanderlei ◽  
Marianne P. C. R. Barbosa ◽  
David M. Garner ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Type 1 Diabetes ◽  
Standard Deviation ◽  
Young Patients ◽  
Frequency Component ◽  
Parasympathetic Activity ◽  
High Frequency Component ◽  
Rr Intervals

ObjectiveThe objective of this study was to verify possible associations between heart rate variability indices and physical activity, body composition, and metabolic and cardiovascular parameters in individuals with type 1 diabetes.MethodA total of 39 young patients with type 1 diabetes were included. Body composition, physical activity, cardiovascular parameters, and metabolic parameters were assessed. For the heart rate variability analysis, heart rate was recorded beat-by-beat using a Polar S810i heart rate monitor for 30 minutes, with the volunteers in the supine position; subsequently, the following indices were considered: standard deviation of all normal RR intervals; root-mean square of differences between adjacent normal RR intervals in a time interval; percentage of adjacent RR intervals with a difference of duration >50 ms; high frequency component in milliseconds squared; high frequency component in normalised units; standard deviation of the instantaneous variability beat-to-beat; and standard deviation of the long-term variability. The association between the heart rate variability indices and independent variables was verified through linear regression in unadjusted and adjusted models (considering gender and age). The statistical significance was set at 5% and the confidence interval at 95%.ResultsHigh values of at-rest heart rate were associated with reduced parasympathetic activity and global heart rate variability, and higher values of waist-to-hip ratio were related to lower parasympathetic activity, independent of age or gender.ConclusionFor young patients with type 1 diabetes, increases in at-rest heart rate values are associated with reduced parasympathetic activity and global heart rate variability, whereas higher waist-to-hip ratio values are related to lower parasympathetic activity, both independent of age and gender.

scholarly journals Decreased Heart Rate Variability in Sickle Cell Anemia as Effect of Pulmonary Arterial Hypertension

Kardiologiia ◽  
2019 ◽  
Vol 59 (4) ◽  
pp. 39-44 ◽  
Author(s):  
F. Akgul ◽  
T. A. Batyraliev ◽  
D. V. Fettser ◽  
E. Seyfeli ◽  
A. G. Arystan ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulmonary Arterial Hypertension ◽  
Arterial Hypertension ◽  
Sickle Cell ◽  
Sickle Cell Anemia ◽  
Mortality Risk ◽  
Healthy Subjects ◽  
Pulmonary Arterial ◽  
Frequency Power

Decreased heart rate variability (HRV) is associated with increased mortality risk in various diseases. Theobjective of this investigation:to study HRV in patients with sickle cell anemia (SCA) and to assess the effect of pulmonary arterial hypertension (PAH) on HRV in these patients.Materials and methods. HRV registration and Doppler echocardiographic assessment of systolic pulmonary arterial pressure (PAP) was carried out in 61 stable patients with SCA and 24 healthy subjects.Results. Low frequency power (LFP) and high frequency power (HFP) were decreased in SCA patients compared to healthy subjects. Among SCA patients, PAH patients had lower  LFP and HFP than patients without PAH. In SCA patients, systolic PAP showed significant negative correlation with LFP and HFP. Conclusion.HRV is significantly decreased in SCA patients, especially in those with PAH. HRV may be particularly useful in early detection of PAH patients who may have worse prognosis and higher mortality risk.

Heart Rate Variability, Emotions, and Music

2010 ◽  
Vol 24 (2) ◽  
pp. 112-119 ◽  
Author(s):  
F. Riganello ◽  
A. Candelieri ◽  
M. Quintieri ◽  
G. Dolce
Keyword(s):  
Data Mining ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Vegetative State ◽  
Low Frequency ◽  
Emotional Reactions ◽  
Heart Beat ◽  
Healthy Controls ◽  
Frequency Spectra ◽  
Emotional Value

The purpose of the study was to identify significant changes in heart rate variability (an emerging descriptor of emotional conditions; HRV) concomitant to complex auditory stimuli with emotional value (music). In healthy controls, traumatic brain injured (TBI) patients, and subjects in the vegetative state (VS) the heart beat was continuously recorded while the subjects were passively listening to each of four music samples of different authorship. The heart rate (parametric and nonparametric) frequency spectra were computed and the spectra descriptors were processed by data-mining procedures. Data-mining sorted the nu_lf (normalized parameter unit of the spectrum low frequency range) as the significant descriptor by which the healthy controls, TBI patients, and VS subjects’ HRV responses to music could be clustered in classes matching those defined by the controls and TBI patients’ subjective reports. These findings promote the potential for HRV to reflect complex emotional stimuli and suggest that residual emotional reactions continue to occur in VS. HRV descriptors and data-mining appear applicable in brain function research in the absence of consciousness.

Parasympathetic activity in brain death: effect of apnea on heart rate variability

1998 ◽  
Vol 42 (1) ◽  
pp. 47-51 ◽  
Author(s):  
M. Kawamoto ◽  
A. Sera ◽  
K. Kaneko ◽  
O. Yuge ◽  
M. Ohtani
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Brain Death ◽  
Parasympathetic Activity

scholarly journals A new analysis of heart rate variability in the assessment of fetal parasympathetic activity: An experimental study in a fetal sheep model

PLoS ONE ◽  
2017 ◽  
Vol 12 (7) ◽  
pp. e0180653 ◽  
Author(s):  
C. Garabedian ◽  
C. Champion ◽  
E. Servan-Schreiber ◽  
L. Butruille ◽  
E. Aubry ◽  
...  
Keyword(s):  
Heart Rate ◽  
Experimental Study ◽  
Heart Rate Variability ◽  
Parasympathetic Activity ◽  
Sheep Model ◽  
Fetal Sheep

scholarly journals Preoperative Heart Rate Variability During Sleep Predicts Vagus Nerve Stimulation Outcome Better in Patients With Drug-Resistant Epilepsy

2021 ◽  
Vol 12 ◽  
Author(s):  
Xi Fang ◽  
Hong-Yun Liu ◽  
Zhi-Yan Wang ◽  
Zhao Yang ◽  
Tung-Yang Cheng ◽  
...  
Keyword(s):  
Machine Learning ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Nerve Stimulation ◽  
Vagus Nerve Stimulation ◽  
Outcome Prediction ◽  
Healthy Controls ◽  
Drug Resistant ◽  
Sleep State ◽  
Drug Resistant Epilepsy

Objective: Vagus nerve stimulation (VNS) is an adjunctive and well-established treatment for patients with drug-resistant epilepsy (DRE). However, it is still difficult to identify patients who may benefit from VNS surgery. Our study aims to propose a VNS outcome prediction model based on machine learning with multidimensional preoperative heart rate variability (HRV) indices.Methods: The preoperative electrocardiography (ECG) of 59 patients with DRE and of 50 healthy controls were analyzed. Responders were defined as having at least 50% average monthly seizure frequency reduction at 1-year follow-up. Time domain, frequency domain, and non-linear indices of HRV were compared between 30 responders and 29 non-responders in awake and sleep states, respectively. For feature selection, univariate filter and recursive feature elimination (RFE) algorithms were performed to assess the importance of different HRV indices to VNS outcome prediction and improve the classification performance. Random forest (RF) was used to train the classifier, and leave-one-out (LOO) cross-validation was performed to evaluate the prediction model.Results: Among 52 HRV indices, 49 showed significant differences between DRE patients and healthy controls. In sleep state, 35 HRV indices of responders were significantly higher than those of non-responders, while 16 of them showed the same differences in awake state. Low-frequency power (LF) ranked first in the importance ranking results by univariate filter and RFE methods, respectively. With HRV indices in sleep state, our model achieved 74.6% accuracy, 80% precision, 70.6% recall, and 75% F1 for VNS outcome prediction, which was better than the optimal performance in awake state (65.3% accuracy, 66.4% precision, 70.5% recall, and 68.4% F1).Significance: With the ECG during sleep state and machine learning techniques, the statistical model based on preoperative HRV could achieve a better performance of VNS outcome prediction and, therefore, help patients who are not suitable for VNS to avoid the high cost of surgery and possible risks of long-term stimulation.

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