Heart Rate Variability Monitoring Research Articles

Simultaneous monitoring of activity and heart rate variability in depressed patients: A pilot study using a wearable monitor for 3 consecutive days.

Reduced activity and sleep-wake rhythm disturbances are essential features of depressive episodes. In addition, alterations in heart rate variability (HRV) have been implicated in depression. By using a wearable sensor that monitors 3-dimensional acceleration and HRV simultaneously, we examined the activity and HRV indices in depressive episode of mood disorders. Participants were 19 patients (13 major depressive disorder [MDD] and 6 bipolar depression; 11 females) and 18 controls (9 females) matched for age and ethnicity (all Japanese) who completed 3 consecutive days of all-day monitoring by a small and light device attached to the chest. Activity magnitude was significantly reduced while lying/resting time was increased in depressed patients, compared with controls. When males and females were examined separately, male, but not female, patients showed significant reduction in activity. HRV indices such as R-R interval and high-frequency power (a parameter for the parasympathetic system) were significantly decreased in patients than in controls. Significant differences in activity and HRV indices were seen only in males. Sympathetic load during sleep significantly correlated with damped rest-activity rhythm in depressed patients. The number of participants was small, and the majority of the participants were taking psychotropic medications. We obtained evidence for reduced activity, increased lying/resting time, and reduced HRV indices in male depressed patients. The simultaneous monitoring for activity and HRV suggested greater sympathetic load during sleep is associated with damped rest-activity rhythm (increased activity during sleep and decreased daytime activity), which might be a characteristic pathology of depression.

Contactless Monitoring of Heart Rate Variability During Respiratory Maneuvers

Heart rate variability (HRV) is a noninvasive marker for the cardiovascular system and the substantial influence of this system on the autonomous nervous system (ANS). Contact and remote photoplethysmography (PPG) proved to be a reliable means of pulse rate variability (PRV) measurement as in wearable devices or imaging PPG using video cameras with evolved technical specifications. However, PRV effectiveness remains unclear during controlled breathing rate. Specifically, respiratory rate, among other physiological factors, applies profound effects on ANS balance. In this study, we demonstrated that PRV can be a reliable marker, as HRV, during various controlled breathing rates. We evaluated the proposed PRV monitoring study against reference HRV obtained from an ECG measurement device. PRV was measured from video streams captured using a smartphone and a webcam for the upper abdominal section of healthy volunteers while in standing position and performing six different respiratory maneuvers. We evaluated frequency and nonlinear HRV indices. Agreement between all indices was tested for camera-based devices and ground truth for all performed tasks. The agreement presented a consistent mean close to 95% limit of agreement (LoA). Also, we employed spectral analysis and measured the spectral divergences, normalized root mean squared error (NRMSE), and correlation. Kullback-Leibler Divergence median and percentiles results indicate congruent spectrums, where the maximum median was 0.18. A significant spectral correlation with minimum value of 0.98, and relatively low spectrum NRMSE of 0.24 were observed. Moreover, the results led to HRV physiological related phenomena which agreed with physiologically interpretations found in the literature.

Employee Wellness in a Changing Climate: Environmental Heat Stress Driving Need for Targeted Health Promotion and Risk Reduction

Objectives: Evaluate the effects of increased ambient temperatures among outdoor workers on physiological heat stress through continuous monitoring of heart rate variability. Methods: A digital smartphone health promotion application was deployed to engage and educate construction workers about stress and other risk reduction; to determine body mass index; and to measure the impact of elevated temperatures on physiological stress measured by tracking continuous non-exertional heart rate variability using a wearable device over 24 hours. Results: Post-program self-rating of health status improved among 56% of participants. A linear relationship was observed between external ambient temperature and physiological stress. Healthy weight people demonstrated less dynamic HRV change and stress with rising temperature compared to those obese/overweight. Physiological stress levels peaked during the hottest hours of the day, with high BMI workers having the greatest increases in stress. Conclusions: Physiological heat stress is impacting outdoor workers in the construction industry, with greater severity observed as BMI increases. Framing climate change as an occupational health issue will help employers understand and mitigate the negative impact of a changing climate on outdoor workers. Use of personal mobile digital technology enables employers to effectively monitor and target physiological heat stress and mental stress among at-risk employees.

Introducing heart rate variability monitoring combined with biomarker screening into a level IV NICU: a prospective implementation study

The aim of this study was to investigate the association between the implementation of a local heart rate variability (HRV) monitoring guideline combined with determination of inflammatory biomarkers and mortality, measures of sepsis severity, frequency of sepsis testing, and antibiotic usage, among very preterm neonates. In January 2018, a guideline was implemented for early detection of late-onset neonatal sepsis using HRV monitoring combined with determination of inflammatory biomarkers. Data on all patients admitted with a gestational age at birth of < 32 weeks were reviewed in the period January 2016–June 2020 (n = 1,135; n = 515 pre-implementation, n = 620 post-implementation). Outcomes of interest were (sepsis-related) mortality, sepsis severity (neonatal sequential organ failure assessment (nSOFA)), sepsis testing, and antibiotic usage. Differences before and after implementation of the guideline were assessed using logistic and linear regression analysis for binary and continuous outcomes respectively. All analyses were adjusted for gestational age and sex. Mortality within 10 days of a sepsis episode occurred in 39 (10.3%) and 34 (7.6%) episodes in the pre- and post-implementation period respectively (P = 0.13). The nSOFA course during a sepsis episode was significantly lower in the post-implementation group (P = 0.01). We observed significantly more blood tests for determination of inflammatory biomarkers, but no statistically significant difference in number of blood cultures drawn and in antibiotic usage between the two periods.Conclusion: Implementing HRV monitoring with determination of inflammatory biomarkers might help identify patients with sepsis sooner, resulting in reduced sepsis severity, without an increased use of antibiotics or number of blood cultures.What is Known:• Heart rate variability (HRV) monitoring might be used as an early warning system to diagnose preterm neonates at risk of developing sepsis.• It has already been shown that HRV monitoring could reduce mortality; however, there are concerns that HRV monitoring alone could lead to higher rates of blood cultures and overuse of antibiotics.What is New:• Implementing HRV monitoring with determination of inflammatory biomarkers might help identify patients with sepsis sooner, resulting in reduced sepsis severity, without an increased use of antibiotics or number of blood cultures.

Continuous mHealth Patch Monitoring for the Algorithm-Based Detection of Atrial Fibrillation: Feasibility and Diagnostic Accuracy Study.

BackgroundThe detection of atrial fibrillation (AF) is a major clinical challenge as AF is often paroxysmal and asymptomatic. Novel mobile health (mHealth) technologies could provide a cost-effective and reliable solution for AF screening. However, many of these techniques have not been clinically validated.ObjectiveThe purpose of this study is to evaluate the feasibility and reliability of artificial intelligence (AI) arrhythmia analysis for AF detection with an mHealth patch device designed for personal well-being.MethodsPatients (N=178) with an AF (n=79, 44%) or sinus rhythm (n=99, 56%) were recruited from the emergency care department. A single-lead, 24-hour, electrocardiogram-based heart rate variability (HRV) measurement was recorded with the mHealth patch device and analyzed with a novel AI arrhythmia analysis software. Simultaneously registered 3-lead electrocardiograms (Holter) served as the gold standard for the final rhythm diagnostics.ResultsOf the HRV data produced by the single-lead mHealth patch, 81.5% (3099/3802 hours) were interpretable, and the subject-based median for interpretable HRV data was 99% (25th percentile=77% and 75th percentile=100%). The AI arrhythmia detection algorithm detected AF correctly in all patients in the AF group and suggested the presence of AF in 5 patients in the control group, resulting in a subject-based AF detection accuracy of 97.2%, a sensitivity of 100%, and a specificity of 94.9%. The time-based AF detection accuracy, sensitivity, and specificity of the AI arrhythmia detection algorithm were 98.7%, 99.6%, and 98.0%, respectively.ConclusionsThe 24-hour HRV monitoring by the mHealth patch device enabled accurate automatic AF detection. Thus, the wearable mHealth patch device with AI arrhythmia analysis is a novel method for AF screening.Trial RegistrationClinicalTrials.gov NCT03507335; https://clinicaltrials.gov/ct2/show/NCT03507335

The Influence of Physical Exercise, Stress and Body Composition on Autonomic Nervous System: A Narrative Review

The heart rate variability (HRV) changes under different situations such as physical exercise, stress and in obese/ overweight subjects. It is considered a noninvasive marker of autonomic nervous system function. The aim of this narrative review was to discuss the relationship between HRV and physical exercise. Moreover, we will make an overview about HRV and stress, and HRV and body composition. There are a large number of studies dealing with HRV, however, few of them explain relationship between HRV and physical exercise, stress and body composition. HRV has proved to be a valuable tool to investigate the sympathetic and parasympathetic function of the ANS. Nonlinear parameters can be used to analyze the health of the subjects and is also used to investigate the stress and the physical exercise level. Despite the underlying mechanisms remain to be elucidated, these finding can be used as a starting point to determine a non-invasive index of cardiac wellness for clinical and nutritional application. Thus, physiological feedback via monitoring HRV would prove useful for addressing the individual’s present capability, be it during selection processes or returning to duty following injury or illness but should not be used to diagnose any pathological conditions.

Chest-Worn Heart Rate Variability Monitor With a Self-Injection-Locked Oscillator Tag

This article presents a chest-worn device for monitoring the heart rate variability (HRV) of a person in motion without direct contact with the skin. The device operates at 5.8 GHz and mainly consists of a self-injection-locked oscillator (SILO) and a tag antenna. The device transmits the output signal of an SILO that is frequency-modulated (FM) by the Doppler effect of the physiological movement of the chest via the tag antenna to a remote FM receiver. Accordingly, the heartbeat is detected and the HRV can be estimated. The tag antenna comprises a circularly polarized ring slot antenna and a split-ring resonator (SRR) array in stack to enhance sensing directivity while reducing the moving clutter in the joint sensing and transmission process. For validation, an HRV monitoring system was developed, based on the proposed device, to detect the cardiac intervals of a wearer who performs various activities, including walking and running. The results thus obtained agree closely with electrocardiogram (ECG) measurements.

Autonomous balance is a factor of changes in the components of the body composition of football players

Objective: To investigate the nature of the relationship between the indicators of heart rate variability (HRV), reflecting the state of autonomous balance and the parameters of the component composition of the body of football players.Materials and methods: We studied n = 80 football players living in the north­western region of the Russian Federation. Group data: 16.9 ± 0.8 years; weight 73.1 ± 4.7 kg; height 181.1 ± 4.9 cm. Monitoring of heart rate variability was carried out by the hardware and software complex “Omega-Sport, St.Petersburg”. The bioelectric activity of the heart was recorded in the II standard lead from the sitting position in the morning (9:00–10:00). The assessment of the body composition of football players was carried out four times (January, April, August, November) using the Inbody 770 analyzer, Japan.Results: SI has a strong direct correlation with the indicators: “total fat content” (r = 0.994, P = 0.011); “total water content” (r = 0.811, P = 0.013). A direct strong correlation was established between SDNN and “total fat content” (r = 0.933, P = 0.009) and an inverse strong correlation with “total muscle mass” (r = -0.877, P = 0.006). pNN50 has a strong direct correlation with “total fat content” (r = 0.889, P = 0.011), in addition, there is a strong inverse correlation with “total muscle mass” (r = ­0.767, P = 0.012). HF and “total fat content” (r = 0.733, P = 0.008) have a strong direct correlation; and with the indicator “total water content” of skeletal muscle mass (r = -0.874, P = 0.011) a strong inverse. A strong inverse relationship is shown between LF and “total fat content” (r = –0.766, P = 0.011), as well as a strong direct correlation with “total muscle mass” (r = 0.951, P = 0.013), “total water content” (r = 0.917, P = 0.008).Conclusions: There is a close correlation of the indicators “total muscle mass”, “total fat content”, “total water content” with a limited number of HRV parameters: SI, SDNN, pNN50, HF, LF. The study showed a significant (p &lt; 0.05) predominance of: the activity of the parasympathetic ANS department — the competitive period, in which there was a significant (p &lt; 0.05) increase in “total muscle mass”, a decrease in “total fat content” in the 1st, 2nd and 3rd diagnostics; the activity of the sympathetic ANS department — the recovery period, which significantly (p &lt; 0.05) affected: a decrease in “total muscle mass”, “total water content”; an increase in “total fat content” in the 4th diagnosis.

Examining weekly heart rate variability changes: a comparison between monitoring methods

Monitoring heart rate variability has been commonly performed by different devices which differ in their methods (i.e., night recording vs. upon awakening measure, pulse vs. R waves, and software signal processing), Thus, the purpose of this study was to determine the level of agreement between different methods of heart rate variability monitoring, represented in two different systems (i.e., the Polar Nightly Recharge™ function present in Polar sport watches and the Polar H10 chest strap synchronized with the Kubios app). A group of 11 recreational athletes performed a concurrent training program for eight weeks and heart rate variability was daily monitored through both devices. Very large correlation (r = 0.714) and good reliability (ICC = 0.817) were obtained between devices through the entire training program. The magnitude-based inference method was also applied to determine the likelihood of the change concerning the smallest worthwhile change. From a baseline corresponding to the first two weeks of the training program, the weekly heart rate variability changes of the following six weeks were determined for each participant with each device. Despite the large correlation and good reliability between devices, there was a 60.6% of discordance in the likelihood interpretation of the change for the 66 weeks evaluated, explained by the random errors found. Thus, practitioners should be aware of these differences if their training groups use different devices or if an athlete interchanges them. The different nuances of each device can condition the heart rate variability data variation which could compromise the interpretation of the autonomic nervous system modulation.

Validation of a smart shirt for heart rate variability measurements at rest and during exercise.

Heart rate variability (HRV) monitoring is a promising option to estimate the autonomic nervous system regulation responding to exercise. Textiles with embedded sensors recording heartbeat intervals are a simple tool for data collection. The so-called smart shirts offer comfort fordaily use and are managed easily. Their measurement accuracy for HRV calculation at rest is promising, but remains questionable during exercise. Therefore, the present study validated the Ambiotex smart shirt using HRV indices (root mean square of successive differences, rel. HF power [high-frequency power percentage of total power] and rel. LF [low-frequency power percentage of total power] power) during exercise. Eighty-three healthy participants (31 ± 6 years; 39 females, 44 males) completed an incremental exercise test on a bicycle ergometer wearing the smart shirt and an electrocardiogram simultaneously. We compared HRV indices of segments at rest (5 min), at warm-up (3 min) and twice at the exercise test (each 5 min). At rest and at warm-up, we observed excellent linear relationship (r > 0.96; R2 ​​​​​ > 0.94), excellent relative reliability (intraclass correlation coefficient ≥ 0.98; α ≥ 0.98) and acceptable agreement (bias < 10%). During the exercise test, measurement accuracy declined with increasing intensity but remained high (>0.8), although results for partial HRV indices were insufficient. In addition, percentage bias was unacceptable during an exercise test. However, the findings support the validity of the smart shirt for measuring HRV, especially at rest and at warm-up. We suggest using the smart shirt for monitoring HRV indices on a daily basis, but caution should be taken in the interpretation of HRV indices obtained during moderate to vigorous exercise intensities.

Heart Rate Variability Monitoring during a Padel Match.

Padel, an increasingly popular sport, presents some associated cardiovascular risks, which can be prevented by heart rate variability (HRV) monitoring. However, there is no study worldwide that characterizes HRV during padel games. Therefore, this study aims to monitor HRV responses and characterize them using linear and non-linear metrics at three timepoints: at baseline, during a game, and during recovery. Twenty-seven amateur participants had their HRV monitored before, during, and after a 90 min padel game. We extracted time, frequency, and non-linear measures with MATLAB for baseline, rest period, and at three periods of 5 min during the game. The differences in measures were assessed through an ANOVA. The autonomic modulation was affected by the padel match in amateur players. In this regard, the root mean square of successive differences between normal heartbeats (RMSsd), Poincaré plot (perpendicular standard deviation (SD1) and horizontal standard deviation (SD2)), sample entropy (SampEn), low frequencies (LF), and very low frequencies (VLF) were significantly reduced during the game, whereas alpha-2, high frequencies (HF), and the ratio between low and high frequencies (LF/HF) increased during the game. Furthermore, an abrupt change was found in the autonomic modulation between game and recovery assessments, which suggests the need to rethink the practices of cool-down protocols. The multiple timepoints analyzed during this study allow us to investigate the evolution of different HRV measures in the time, frequency, and non-linear domains, clarifying the interpretation of the variables, especially the less-investigated ones such as the non-linear measures.

Early neonatal heart rate variability patterns in different subtypes of perinatal hypoxic-ischemic brain injury.

This study aims to compare the longitudinal changes in heartrate variability (HRV) during therapeutic hypothermia in neonates with different subtypes of hypoxic-ischemic brain injury. HRV was computed from 1 hour time-epochs q6 hours for the first 48 hours. Primary outcome was brain-injury pattern on MRI at 4(3-5) days. We fitted linear mixed-effect regression models with HRV metric, brain injury subtype and postnatal age. Among 89 term neonates, 40 neonates had abnormal brain MRI (focal infarct 15 (38%), basal-ganglia predominant 8 (20%), watershed-predominant 5 (13%), and mixed pattern 12 (30%)). There was no significant difference in the HRV metrics between neonates with normal MRI, focal infarcts and basal ganglia pattern. At any given postnatal age, the degree of HRV suppression(HRV measure in the brain-injury subtype group/HRV measure in Normal MRI group) was significant in neonates with watershed pattern (SDNN(0.63, p = 0.08), RMSSD(0.74, p = 0.04)) and mixed pattern injury (SDNN (0.64, p < 0.001), RMSSD (0.75, p = 0.02)). HRV suppression was most profound at the postnatal age of 24-30 h in all brain injury subtypes. Neonates with underlying watershed injury with or without basal-ganglia injury demonstrates significant HRV suppression during first 48 hour of hypothermia therapy. Our study suggests that suppression of heartrate variability in neonates during therapeutic hypothermia varies according to the pattern of underlying hypoxic-ischemic brain injury. Neonates with watershed predominant pattern and mixed pattern of brain injury have the most severe suppression of heartrate variability measures. Heartrate variability monitoring may provide early insights into the pattern of hypoxic-ischemic brain injury in neonates undergoing therapeutic hypothermia earlier than routine clinical MRI.

Heart Rate Variability measured during rest and after orthostatic challenge to detect autonomic dysfunction in Type 2 Diabetes Mellitus using the Classification and Regression Tree model.

According to the World Health Organization, one in ten adults will have Type 2 Diabetes Mellitus (T2DM) in the next few years. Autonomic dysfunction is one of the significant complications of T2DM. Autonomic dysfunction is usually assessed by standard Ewing's test and resting Heart Rate Variability (HRV) indices. Resting HRV has limited use in screening due to its large intra and inter-individual variations. Therefore, a combined approach of resting and orthostatic challenge HRV measurement with a machine learning technique was used in the present study. A total of 213 subjects of both genders between 20 to 70 years of age participated in this study from March 2018 to December 2019 at Smt. Kashibai Navale Medical College and General Hospital (SKNMCGH) in Pune, India. The volunteers were categorized according to their glycemic status as control (n= 51 Euglycemic) and T2DM (n= 162). The short-term ECG signal in the resting and after an orthostatic challenge was recorded. The HRV indices were extracted from the ECG signal as per HRV-Taskforce guidelines. We observed a significant difference in time, frequency, and non-linear resting HRV indices between the control and T2DM groups. A blunted autonomic response to an orthostatic challenge quantified by percentage difference was observed in T2DM compared to the control group. HRV patterns during rest and the orthostatic challenge were extracted by various machine learning algorithms. The Classification and Regression Tree (CART) model has shown better performance among all the machine learning algorithms. It has shown an accuracy of 84.04%, the sensitivity of 89.51%, a specificity of 66.67%, with an Area Under Receiver Operating Characteristic Curve (AUC) of 0.78 compared to resting HRV alone with 75.12% accuracy, 86.42% sensitivity, 39.22% specificity, with an AUC of 0.63 for differentiating autonomic dysfunction in non-diabetic control and T2DM. It was possible to develop a Classification and Regression Tree (CART) model to detect autonomic dysfunction. The technique of percentage difference between resting and orthostatic challenge HRV indicates the blunted autonomic response. The developed CART model can differentiate the autonomic dysfunction using both resting and orthostatic challenge HRV data compared to only resting HRV data in T2DM. Thus, monitoring HRV parameters using the CART model during rest and after orthostatic challenge may be a better alternative to detect autonomic dysfunction in T2DM as against only resting HRV.

CamSense: A camera-based contact-less heart activity monitoring

Remote Photoplythysmograpy (rPPG) systems enable contactless heart activities (heart rate, heart rate variability) monitoring by estimating Photoplethysmogram (PPG) signal, blood’s volumetric variation in the skin tissues, leveraging the occurred diffused reflection from the exposed skin in skin video. They can primarily monitor heart activities using off-the-shelf video sensors while ensuring the safety of concerned individuals during contagious diseases. However, developing the rPPG systems is challenging due to the marginal presence of PPG signal in the video stream, data variations, limited and noisy rPPG data. In this regard, we propose an end-to-end deep learning-based approach for camera-based contactless sensing CamSense for recovering PPG signals from consecutive raw video frames. Firstly, we design and validate a personalized model to bypass data variation and noise across data collection with a modified objective function under realistic settings. Secondly, we explore and design multi-task learning (MTL) network to address the rPPG data variabilities for learning generalized rPPG representations. We also propose a transfer learning approach that integrates an efficient weight initialization to scale the rPPG systems under different domains and settings for fast and generalized training and inferences. Finally, we offer a new dataset, MPSC-rPPG dataset, containing multiple RGB videos and corresponding PPG ground truth for end–end rPPG network training. We evaluate CamSense on two public datasets and our MPSC-rPPG dataset across multiple subjects and heterogeneous camera sensors such as DSLR and near-infrared sensors with different ground truth provider PPG sensors (wrist, finger) to showcase its’ generalizability. We further validate our components’ design choices by performing ablation studies using different settings. Our developed model approximates accurate PPG signals with an average root mean square error (RMSE) of 0.08, 0.10, and 0.06 for personalized models, MTL model, and transfer learnings on the held-out test videos.

Assessing the Clinical Utility of a Wearable Device for Physiological Monitoring of Heart Rate Variability in Military Service Members with Traumatic Brain Injury.

Introduction: Autonomic dysfunction has been implicated as a consequence of traumatic brain injury (TBI). Heart rate variability (HRV) may be a viable measure of autonomic dysfunction that could enhance rehabilitative interventions for individuals with TBI. This pilot study sought to assess the feasibility and validity of using the Zeriscope™ platform system in a real-world clinical setting to measure HRV in active-duty service members with TBI who were participating in an intensive outpatient program. Methods: Twenty-five service members with a history of mild, moderate, or severe TBI were recruited from a military treatment facility. A baseline assessment was conducted in the cardiology clinic where point validity data were obtained by comparing a 5-min recording of a standard 12-lead electrocardiogram (ECG) output against the Zeriscope platform data. Results: Compared with the ECG device, the Zeriscope device had a concordance coefficient (rc) of 0.16, falling below the standard deemed to represent acceptable accuracy in HR measurement (i.e., 0.80). Follow-up analyses excluding outliers did not significantly improve the concordance coefficient to an acceptable standard for the total participant sample. System Usability Survey responses showed that participants rated the Zeriscope system as easy to use and something that most people would learn to use quickly. Conclusions: This study demonstrated promise in ambulatory HRV measurement in a representative military TBI sample. Future research should include further refinement of such ambulatory devices to meet the specifications required for use in a military active-duty TBI population.

An Assessment of Stress Status in Fattening Steers by Monitoring Heart Rate Variability: A Case of Dietary Vitamin A Restriction

Heart rate variability (HRV), heart beat-to-beat variations, is a measure of cardiac autonomic functions, and HRV monitoring using sensor technology can be a non-invasive way to assess stress of animals. The objective of this study was to investigate the effect of dietary vitamin A (VA) restriction to enhance beef quality on the physiological status of fattening steers by HRV analysis. Six Japanese Black steers were equally allocated into VA-restricted (RES) and VA-supplemented (SUP) groups. The RES steers were fed VA-restricted diets from 11 to 20 months of age. The inter-beat intervals and blood VA concentration were measured at 18 and 24 months of age. HRV parameters in time, frequency, and non-linear domains were calculated using the inter-beat intervals. Blood VA concentration was significantly lower in RES steers than in SUP steers at 18 months of age (P &amp;lt; 0.05) but did not differ between the groups at 24 months of age. The HRV analysis indicated greater sympathetic and lower parasympathetic activities in RES steers than in SUP steers (P &amp;lt; 0.05). However, there were significant interactions of the group and age on HRV parameters (P &amp;lt; 0.05), indicating that although RES steers at 18 months of age might suffer from slight stress, the response could recover to a level similar to SUP steers at 24 months of age by the increase in blood VA concentration.

Inappropriate sinus tachycardia in post-COVID-19 syndrome

Inappropriate sinus tachycardia (IST) is a common observation in patients with post-COVID-19 syndrome (PCS) but has not yet been fully described to date. To investigate the prevalence and the mechanisms underlying IST in a prospective population of PCS patients. Consecutive patients admitted to the PCS Unit between June and December 2020 with a resting sinus rhythm rate ≥ 100 bpm were prospectively enrolled in this study and further examined by an orthostatic test, 2D echocardiography, 24-h ECG monitoring (heart rate variability was a surrogate for cardiac autonomic activity), quality-of-life and exercise capacity testing, and blood sampling. To assess cardiac autonomic function, a 2:1:1 comparative sub-analysis was conducted against both fully recovered patients with previous SARS-CoV-2 infection and individuals without prior SARS-CoV-2 infection. Among 200 PCS patients, 40 (20%) fulfilled the diagnostic criteria for IST (average age of 40.1 ± 10 years, 85% women, 83% mild COVID-19). No underlying structural heart disease, pro-inflammatory state, myocyte injury, or hypoxia were identified. IST was accompanied by a decrease in most heart rate variability parameters, especially those related to cardiovagal tone: pNN50 (cases 3.2 ± 3 vs. recovered 10.5 ± 8 vs. non-infected 17.3 ± 10; p < 0.001) and HF band (246 ± 179 vs. 463 ± 295 vs. 1048 ± 570, respectively; p < 0.001). IST is prevalent condition among PCS patients. Cardiac autonomic nervous system imbalance with decreased parasympathetic activity may explain this phenomenon.

Effectiveness of Stress Inoculation Training on Heart Rate Variability, Salivary Cortisol, Anxiety, Stress, and Depression after Coronary Artery Bypass Graft Surgery

Aims: This study aims to evaluate the effect of Stress Inoculation Training (SIT) on Heart Rate Variability (HRV), salivary cortisol and psychological complications (anxiety, stress and depression) after Coronary Artery Bypass Graft (CABG) surgery. Methods &amp; Materials: This is a quasi-experimental study with a pretest/posttest/follow-up phase. The study population consists of all patients who had underwent CABG surgery and referred to the Cardiac Rehab center of Tehran Heart Hospital in Iran. Of these, 30 patients were selected using a random sampling method and divided into two intervention and control groups. The instruments were a cortisol salvia ELISA kit, a HRV monitor, and the 21-item Depression, Anxiety and Stress Scale. The intervention group received SIT at 10 sessions of 90 minutes. Findings: The results of multivariate analysis of covariance showed a significant difference in depression (P&lt;0.001), anxiety (P&lt;0.001), stress (P&lt;0.001), salivary cortisol level (P&lt;0.001) and HRV (P&lt;0.001) between the two groups. The mean HRV was significantly higher in the intervention group than in the control group. In other variables, the mean scores were lower in the intervention group than in the control group. Conclusion: Reduced negative emotions following SIT plays an important role in preventing the severe complications of heart disease. Interventions based on the SIT method are recommended for patients with heart disease.

Аssessment of vegetative regulation of the heart rate in patients with pulmonary TB

SummaryAim. To evaluate features of vegetative regulation of the heart rate in patients with pulmonary TB. Methods. The authors analyzed examination results of 109 patients with different forms of pulmonary TB (the main group). The comparison group consisted of 63 individuals with-out TB or heart disease. To identify features of vegetative regulation of the heart rate, all patients underwent 3-lead 24-hour ECG monitoring and assessment of heart rate variability (HRV) indices using spectral and time-domain analyses. The results were processed using MS Excel 2016 for Windows and Statistica 10 software programmes; nonparametric methods were used. Results. According to our research data, pulmonary TB patients had signifi-cantly lower values of the time-domain analysis of HRV: SDNN in 28% of cases (р&lt;0.05); RMSSD in 22% of cases (р&lt;0.05). The spectral analysis data showed HF in 91% of cases (р&lt;0.05), LF in 61% of cases (р&lt;0.05), a rigid circa-dian rhythm of the heart rate in 55% of cases (p&lt;0.05), and the increased index of vagosympathetic balance in 93% of cases (р&lt;0.05). The sympathicotonic type of vegetative regulation was detected in 93% of cases, the balanced initial vegetative type of HRV — in 5% of cases, and the parasympathicotonic type — in 2% of cases. The authors established a direct strong correlation between indices of RMSSD and HF, r=0.81 (p&lt;0.05). The changes in HRV parameters were not linked with clinical forms of TB (р&gt;0.05). Conclusion. Initial sympathicotonia prevails in patients with pulmonary TB, which indicates intensive work of the cardiovascular system, which in its turn leads to the increased risk of adverse cardiac events. Patients with pulmonary TB should undergo dynamic 24-hour Holter monitoring for timely correction of vegetative re-gulation of the heart rate.

Effects of Brief Mental Skills Training on Emergency Medicine Residents' Stress Response During a Simulated Resuscitation: A Prospective Randomized Trial.

BackgroundAcute stress impairs physician decision-making and clinical performance in resuscitations. Mental skills training, a component of the multistep, cognitive-behavioral technique of stress inoculation, modulates stress response in high-performance fields.ObjectiveWe assessed the effects of mental skills training on emergency medicine (EM) residents’ stress response in simulated resuscitations as well as residents’ perceptions of this intervention.MethodsIn this prospective, educational intervention trial, postgraduate year-2 EM residents in seven Chicago-area programs were randomly assigned to receive either stress inoculation training or not. One month prior to assessment, the intervention group received didactic training on the “Breathe, Talk, See, Focus” mental performance tool. A standardized, case-based simulation was used for assessment. We measured subjective stress response using the six-item short form of the Spielberger State-Trait Anxiety Inventory (STAI-6). Objective stress response was measured through heart rate (HR) and heart rate variability (HRV) monitoring. We measured subjects’ perceptions of the training via survey.ResultsOf 92 eligible residents, 61 participated (25 intervention; 36 control). There were no significant differences in mean pre-/post-case STAI-6 scores (−1.7 intervention, 0.4 control; p = 0.38) or mean HRV (−3.8 milliseconds [ms] intervention, −3.8 ms control; p = 0.58). Post-assessment surveys indicated that residents found this training relevant and important.ConclusionThere was no difference in subjective or objective stress measures of EM resident stress response after a didactic, mental performance training session, although residents did value the training. More extensive or longitudinal stress inoculation curricula may provide benefit.