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Journal of Clinical Monitoring and... Feb 2024Background- Subarachnoid hemorrhage (SAH) is one of the most devastating diseases with a high rate of morbidity and mortality. The heart rate variability (HRV) is a... (Review)
Review
Background- Subarachnoid hemorrhage (SAH) is one of the most devastating diseases with a high rate of morbidity and mortality. The heart rate variability (HRV) is a non-invasive method of monitoring various components of the autonomic nervous system activity that can be utilized to delineate autonomic dysfunctions associated with various physiological and pathological conditions. The reliability of HRV as a predictor of clinical outcome in aneurysmal subarachnoid hemorrhage (aSAH) is not yet well investigated in literature. Methods- A systematic review and in depth analysis of 10 articles on early HRV changes in SAH patients was performed. Results- This systematic review demonstrates a correlation between early changes in HRV indices (time and frequency domain) and the development of neuro-cardiogenic complications and poor neurologic outcome in patients with SAH. Conclusions- A correlation between absolute values or changes of the LF/HF ratio and neurologic and cardiovascular complications was found in multiple studies. Because of significant limitations of included studies, a large prospective study with proper handling of confounders is needed to generate high-quality recommendations regarding HRV as a predictor of post SAH complications and poor neurologic outcome.
Topics: Humans; Subarachnoid Hemorrhage; Heart Rate; Prospective Studies; Reproducibility of Results; Autonomic Nervous System
PubMed: 37335412
DOI: 10.1007/s10877-023-01043-z -
Pacing and Clinical Electrophysiology :... Jun 2024There are important physiological changes in the heart rate autonomic modulation in pregnant women and these changes may affect the way their bodies respond to exercise... (Review)
Review
BACKGROUND
There are important physiological changes in the heart rate autonomic modulation in pregnant women and these changes may affect the way their bodies respond to exercise stimulus. The objective of this review is to verify the physical exercise influence on autonomic modulation of heart rate in pregnant women.
METHODS
This study is a Systematic Review. The electronic databases used to search for the studies were Cochrane Library, MEDLINE via PUBMED, Regional Health Portal and EMBASE. Experimental studies that evaluated heart-rate variability in pregnant women practicing physical exercises were included. And articles that addressed only fetal heart-rate variability, case reports, congress abstracts, clinical trial protocols without results, preprints, and gray literature were excluded. There were no language or publication year restrictions. The descriptors used in the Search were Cardiac Chronotropism, Sympathetic Nervous System, Pregnancy, and Physical Exercise. For statistical analysis, the fixed effect model was used.
RESULTS
A total of 3106 articles were found, and 12 studies were included, which 5 were nonrandomized clinical trials, 4 were randomized clinical trials, and 3 were cross-sectional studies. Three hundred and four pregnant women were included in the studies. The application of physical exercise was varied, but in general they used aerobic exercises and with increased variability of the heart rate and reflex on the autonomic modulation of heart rate.
CONCLUSION
Most studies demonstrate benefits heart rate in pregnant women, but limited research makes it hard to compare specific types of exercise and larger studies are needed to identify the best exercise.
Topics: Female; Humans; Pregnancy; Autonomic Nervous System; Exercise; Heart Rate
PubMed: 38577940
DOI: 10.1111/pace.14976 -
International Journal of... Oct 2023Evidence suggests affective disorders such as depression and bipolar disorder are characterised by dysregulated autonomic nervous system (ANS) activity. These findings... (Review)
Review
Evidence suggests affective disorders such as depression and bipolar disorder are characterised by dysregulated autonomic nervous system (ANS) activity. These findings suggest ANS dysregulation may be involved in the pathogenesis of affective disorders. Different affective states are characterised by different ANS activity patterns (i.e., an increase or decrease in sympathetic or parasympathetic activity). To understand how ANS abnormalities are involved in the development of affective disorders, it is important to understand how affective states correlate with ANS activity before their onset. Using heart rate variability (HRV) as a tool to measure ANS activity, this review aimed to look at associations between affective states and HRV in non-clinical populations (i.e., in those without medical and psychiatric disorders). Searches on PubMed and Google Scholar were completed using the following search terms: heart rate variability, autonomic nervous system, sympathetic nervous system, parasympathetic nervous system, affective state, mood and emotion in all possible combinations. All but one of the studies examined (N = 13), demonstrated significant associations between affect and HRV. Findings suggest negative affect, encompassing both diffused longer-term experiences (i.e., mood) as well as more focused short-term experiences (i.e., emotions), may be associated with a reduction in parasympathetic activity as measured through HRV parameters known to quantify parasympathetic activity (e.g., high frequency (HF)-HRV). HRV measures typically linked to reduction in parasympathetic activity appear to be linked to negative affective states in non-clinical populations. However, given the complex and possibly non-linear relationship between HRV and parasympathetic activity, further studies need to clarify specificity of these findings. Future studies should investigate the potential utility of HRV measures as biomarkers for monitoring changes in affective states and for early detection of onset and relapse of depression in patients with affective disorders.
Topics: Humans; Heart Rate; Autonomic Nervous System; Parasympathetic Nervous System; Sympathetic Nervous System; Affect
PubMed: 37543289
DOI: 10.1016/j.ijpsycho.2023.08.001 -
Polish Journal of Veterinary Sciences Dec 2023The symbolic analysis of heart rate variability (biomarker of cardiac autonomic homeostasis) is a nonlinear and effective tool for pattern extraction and classification...
The symbolic analysis of heart rate variability (biomarker of cardiac autonomic homeostasis) is a nonlinear and effective tool for pattern extraction and classification in a series analysis, which implies the transformation of an original time series into symbols, represented by numbers. Autonomic heart rate control is influenced by different factors, and better indicators of heart rate variability are found in healthy young individuals than in older and sicker individuals. The aim of this study was to compare the indicators of heart rate variability among healthy dogs in different age groups and in health status using the nonlinear method of symbolic analysis to evaluate the diagnostic accuracy of this method for the risk of death in dogs. An increase in cardiac sympathetic modulation was observed in puppies and dogs at risk of death, which was evidenced by a marked increase of 0 V% (without variation - associated with sympathetic modulation) and a decrease in patterns of 2 V% (two variations - associated with parasympathetic modulation), while the opposite was observed in young adult dogs with increased parasympathetic modulation. Elderly dogs showed a gradual decrease in parasympathetic activity, which tended to worsen with loss of health. It is concluded that the variables of symbolic analysis may be useful to evaluate autonomic modulation in dogs and assist in the differentiation between health states, advanced disease and death throughout the life cycle and have been shown to be indices with high specificity, sensitivity and diagnostic accuracy to help identify dogs at risk of death.
Topics: Dogs; Animals; Heart Rate; Autonomic Nervous System; Heart; Health Status
PubMed: 38088302
DOI: 10.24425/pjvs.2023.148278 -
Biosensors Feb 2024Pulse Wave Velocity (PWV) analysis is valuable for assessing arterial stiffness and cardiovascular health and potentially for estimating blood pressure cufflessly....
Pulse Wave Velocity (PWV) analysis is valuable for assessing arterial stiffness and cardiovascular health and potentially for estimating blood pressure cufflessly. However, conventional PWV analysis from two transducers spaced closely poses challenges in data management, battery life, and developing the device for continuous real-time applications together along an artery, which typically need data to be recorded at high sampling rates. Specifically, although a pulse signal consists of low-frequency components when used for applications such as determining heart rate, the pulse transit time for transducers near each other along an artery takes place in the millisecond range, typically needing a high sampling rate. To overcome this issue, in this study, we present a novel approach that leverages the Nyquist-Shannon sampling theorem and reconstruction techniques for signals produced by bioimpedance transducers closely spaced along a radial artery. Specifically, we recorded bioimpedance artery pulse signals at a low sampling rate, reducing the data size and subsequently algorithmically reconstructing these signals at a higher sampling rate. We were able to retain vital transit time information and achieved enhanced precision that is comparable to the traditional high-rate sampling method. Our research demonstrates the viability of the algorithmic method for enabling PWV analysis from low-sampling-rate data, overcoming the constraints of conventional approaches. This technique has the potential to contribute to the development of cardiovascular health monitoring and diagnosis using closely spaced wearable devices for real-time and low-resource PWV assessment, enhancing patient care and cardiovascular disease management.
Topics: Humans; Pulse Wave Analysis; Arteries; Blood Pressure; Heart Rate
PubMed: 38392011
DOI: 10.3390/bios14020092 -
Bio Systems Mar 2024The paper aims to examine the hyperbolic system of equations governing one-dimensional haemodynamics and its relevance in analysing blood flow under mechanical...
The paper aims to examine the hyperbolic system of equations governing one-dimensional haemodynamics and its relevance in analysing blood flow under mechanical influences, with particular emphasis on the impact of altering the angle of the leg axis. Methods and approaches for solving hyperbolic equations have been developed in light of their properties and characteristics. The primary objective of this study was to investigate the interplay between vein pressure, pulse wave velocity, and vascular distension. The study revealed an inverse relationship between vein pressure and pulse wave velocity. A decrease in pulse wave velocity occurs when vein pressure rises, and vice versa. Both real measurements and modelling results confirmed this dependence. The pressure in the veins is between 10.8 and 13.6 kPa, and the speed of the pulse wave is between 0.061 and 0.27 kPa. The agreement between real and model data was high. The modelled venous pressure and pulse wave velocity values are close to the actual values. However, it is essential to acknowledge the limitations of this paper. These limitations include the utilisation of one-dimensional haemodynamic models, which fail to consider the three-dimensional structure of the circulatory system. Additionally, the analysis is restricted to examining changes solely in the leg axis angle. The research helps to clarify the relationship between mechanical actions and haemodynamic parameters. The findings may help research and develop new methods for identifying and treating conditions associated with the cardiovascular system.
Topics: Pulse Wave Analysis; Blood Flow Velocity; Hemodynamics; Heart Rate
PubMed: 38382825
DOI: 10.1016/j.biosystems.2024.105160 -
European Journal of Clinical... Sep 2023QT interval varies with the heart rate (HR), so a correction in QT calculation is needed (QTc). Atrial fibrillation (AF) is associated with elevated HR and beat-to-beat...
BACKGROUND
QT interval varies with the heart rate (HR), so a correction in QT calculation is needed (QTc). Atrial fibrillation (AF) is associated with elevated HR and beat-to-beat variation.
AIM
To find best correlation between QTc in atrial fibrillation (AF) versus restored sinus rhytm (SR) after electrical cardioversion (ECV) (primary end point) and to determine which correction formula and method are the best to determine QTc in AF (secondary end point).
METHODS
During a 3-month period, we considered patients who underwent 12-lead ECG recording and received an AF diagnosis with indication for ECV. Exclusion criteria were as follows: QRS duration >120 ms, therapy with QT-prolonging drugs, a rate control strategy and a nonelectrical cardioversion. The QT interval was corrected using Bazzett's, Framingham, Fridericia and Hodges formulas during the last ECG during AF and the first one immediately after ECV. QTc mean was calculated as mQTc (average of 10 QTc calculated beat per beat) and as QTcM (QTc calculated from the average of 10 raw QT and RR for each beat).
RESULTS
Fifty consecutive patients were enrolled in the study. Bazett's formula showed a significant change in mean QTc value between the two rhythms (421.5 ± 33.9 vs. 446.1 ± 31.9; p < 0.001 for mQTc and 420.9 ± 34.1 vs. 441.8 ± 30.9; p = 0.003 for QTcM). On the contrary, in patients with SR, QTc assessed by the Framingham, Fridericia, and Hodges formulas was similar to that in AF. Furthermore, good correlations between mQTc and QTcM are present for each formula, even in AF or SR.
CONCLUSIONS
During AF, Bazzett's formula, seems to be the most imprecise in QTc estimation.
Topics: Humans; Atrial Fibrillation; Heart Rate; Electrocardiography; Electric Countershock
PubMed: 37144525
DOI: 10.1111/eci.14013 -
Sensors (Basel, Switzerland) Sep 2023Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential...
Cardio-mechanical monitoring techniques, such as Seismocardiography (SCG) and Gyrocardiography (GCG), have received an ever-growing interest in recent years as potential alternatives to Electrocardiography (ECG) for heart rate monitoring. Wearable SCG and GCG devices based on lightweight accelerometers and gyroscopes are particularly appealing for continuous, long-term monitoring of heart rate and its variability (HRV). Heartbeat detection in cardio-mechanical signals is usually performed with the support of a concurrent ECG lead, which, however, limits their applicability in standalone cardio-mechanical monitoring applications. The complex and variable morphology of SCG and GCG signals makes the ECG-free heartbeat detection task quite challenging; therefore, only a few methods have been proposed. Very recently, a template matching method based on normalized cross-correlation (NCC) has been demonstrated to provide very accurate detection of heartbeats and estimation of inter-beat intervals in SCG and GCG signals of pathological subjects. In this study, the accuracy of HRV indices obtained with this template matching method is evaluated by comparison with ECG. Tests were performed on two public datasets of SCG and GCG signals from healthy and pathological subjects. Linear regression, correlation, and Bland-Altman analyses were carried out to evaluate the agreement of 24 HRV indices obtained from SCG and GCG signals with those obtained from ECG signals, simultaneously acquired from the same subjects. The results of this study show that the NCC-based template matching method allowed estimating HRV indices from SCG and GCG signals of healthy subjects with acceptable accuracy. On healthy subjects, the relative errors on time-domain indices ranged from 0.25% to 15%, on frequency-domain indices ranged from 10% to 20%, and on non-linear indices were within 8%. The estimates obtained on signals from pathological subjects were affected by larger errors. Overall, GCG provided slightly better performances as compared to SCG, both on healthy and pathological subjects. These findings provide, for the first time, clear evidence that monitoring HRV via SCG and GCG sensors without concurrent ECG is feasible with the NCC-based template matching method for heartbeat detection.
Topics: Humans; Heart Rate; Electrocardiography; Heart; Monitoring, Physiologic; Heart Rate Determination
PubMed: 37836942
DOI: 10.3390/s23198114 -
Physiological Measurement Oct 2023Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure-volume... (Review)
Review
Continuous monitoring of mean intracranial pressure (ICP) has been an essential part of neurocritical care for more than half a century. Cerebrospinal pressure-volume compensation, i.e. the ability of the cerebrospinal system to buffer changes in volume without substantial increases in ICP, is considered an important factor in preventing adverse effects on the patient's condition that are associated with ICP elevation. However, existing assessment methods are poorly suited to the management of brain injured patients as they require external manipulation of intracranial volume. In the 1980s, studies suggested that spontaneous short-term variations in the ICP signal over a single cardiac cycle, called the ICP pulse waveform, may provide information on cerebrospinal compensatory reserve. In this review we discuss the approaches that have been proposed so far to derive this information, from pulse amplitude estimation and spectral techniques to most recent advances in morphological analysis based on artificial intelligence solutions. Each method is presented with focus on its clinical significance and the potential for application in standard clinical practice. Finally, we highlight the missing links that need to be addressed in future studies in order for ICP pulse waveform analysis to achieve widespread use in the neurocritical care setting.
Topics: Humans; Intracranial Pressure; Artificial Intelligence; Blood Pressure; Brain; Heart Rate
PubMed: 37793420
DOI: 10.1088/1361-6579/ad0020 -
Journal of Medical Internet Research Nov 2023Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity... (Meta-Analysis)
Meta-Analysis Review
BACKGROUND
Recent studies have linked low heart rate variability (HRV) with COVID-19, indicating that this parameter can be a marker of the onset of the disease and its severity and a predictor of mortality in infected people. Given the large number of wearable devices that capture physiological signals of the human body easily and noninvasively, several studies have used this equipment to measure the HRV of individuals and related these measures to COVID-19.
OBJECTIVE
The objective of this study was to assess the utility of HRV measurements obtained from wearable devices as predictive indicators of COVID-19, as well as the onset and worsening of symptoms in affected individuals.
METHODS
A systematic review was conducted searching the following databases up to the end of January 2023: Embase, PubMed, Web of Science, Scopus, and IEEE Xplore. Studies had to include (1) measures of HRV in patients with COVID-19 and (2) measurements involving the use of wearable devices. We also conducted a meta-analysis of these measures to reduce possible biases and increase the statistical power of the primary research.
RESULTS
The main finding was the association between low HRV and the onset and worsening of COVID-19 symptoms. In some cases, it was possible to predict the onset of COVID-19 before a positive clinical test. The meta-analysis of studies reported that a reduction in HRV parameters is associated with COVID-19. Individuals with COVID-19 presented a reduction in the SD of the normal-to-normal interbeat intervals and root mean square of the successive differences compared with healthy individuals. The decrease in the SD of the normal-to-normal interbeat intervals was 3.25 ms (95% CI -5.34 to -1.16 ms), and the decrease in the root mean square of the successive differences was 1.24 ms (95% CI -3.71 to 1.23 ms).
CONCLUSIONS
Wearable devices that measure changes in HRV, such as smartwatches, rings, and bracelets, provide information that allows for the identification of COVID-19 during the presymptomatic period as well as its worsening through an indirect and noninvasive self-diagnosis.
Topics: Humans; Heart Rate; COVID-19; Wearable Electronic Devices
PubMed: 37820372
DOI: 10.2196/47112