Circadian Heart Rate Variability Research Articles

The search for optimal nocturnal diurnal heart rate Index targets in ICU patients: a retrospective observational study from large ICU database.

Circadian rhythms play a crucial role in cardiovascular health, with the nocturnal diurnal heart rate index (NDHRI) reflecting significant circadian variations. However, the optimal NDHRI target in Intensive Care Unit (ICU) patients remains undefined. This study aims to establish an evidence-based NDHRI target range and assess its association with mortality. Data from the eICU Collaborative Research Database (n = 32,412) were analyzed. NDHRI was calculated by dividing cumulative nighttime heart rate area by daytime area. Generalized additive models (GAMs) explored the non-linear relationship between mean NDHRI and mortality, adjusting for confounders. Subgroup analyses were conducted based on ethnicity, ICU type, and comorbidities. A U-shaped association was observed between hospital mortality and mean NDHRI (P < 0.001). The optimal NDHRI range (40.0%-45.0%) demonstrated the lowest mortality rates. The duration spent within this range correlated inversely with mortality (P < 0.001). Subgroup analyses consistently supported these findings across diverse patient profiles. Our findings suggest an association between maintaining NDHRI within the 40.0%-45.0% range and lower mortality rates in critically ill patients, highlighting the potential utility of monitoring circadian heart rate variations in the ICU. Further research and future randomized controlled trials are essential to confirm causality and should consider this NDHRI range as a pivotal reference target.

CADCare: Smart System for CHD Identification &amp; Sensor Alerts

INTRODUCTION: Cardiovascular diseases, particularly coronary artery disease (CAD), present a global health challenge, necessitating effective detection and diagnosis methods for early intervention. Various machine learning and deep learning approaches have emerged, utilizing diverse data sources such as electrocardiogram (ECG) signals and clinical features to enhance CAD detection. Additionally, circadian heart rate variability (HRV) has been explored as a potential diagnostic marker for CAD severity. This research aims to contribute to the burgeoning field of medical AI and its application in cardiology.OBJECTIVES: This study seeks to develop a Comprehensive Coronary Artery Disease Detection System integrating real-time heart rate monitoring and CAD prediction via an Android application. The objectives include seamless data transmission, efficient cloud-based data management, and the utilization of AI models, including ANNs, CNNs for ECG images, and hybrid models combining clinical and ECG data, to improve early CAD detection and management.METHODS: The system architecture involves integrating key sensors, an Arduino microcontroller, a Bluetooth module, and AI models to facilitate early CAD detection. An Android application complements the system, offering heart rate monitoring and CAD prediction using various data sources. Cloud computing is employed for efficient data management and analysis.RESULTS: The developed system successfully integrates cutting-edge technology to enhance CAD detection, achieving accurate and efficient results in real-time heart rate monitoring and CAD prediction.CONCLUSION: The Comprehensive Coronary Artery Disease Detection System, leveraging AI and cloud computing, contributes to proactive health monitoring and informed decision-making in CAD management and prevention, thereby addressing a critical need in cardiovascular health care.

The value of circadian heart rate variability for the estimation of obstructive sleep apnea severity in adult males.

Heart rate variability (HRV) is becoming more prevalent as a measurable parameter in wearable sleep-monitoring devices, which are simple and effective instruments for illness evaluation. Currently, most studies on investigating OSA severity and HRV have measured heart rates during wakefulness or sleep. Therefore, the objective of this study was to investigate the circadian rhythm of HRV in male patients with OSA and its value for the estimation of OSA severity using group-based trajectory modeling. Patients with complaints of snoring were enrolled from the Sleep Center of Shandong Qianfoshan Hospital. Patients were divided into 3 groups according to apnea hypopnea index (AHI inevents/h), as follows: (<15, 15≤AHI<30, and ≥30). HRV parameters were calculated using 24 h Holter monitoring, which included time-domain and frequency-domain indices. Circadian differences in the standard deviation of normal to normal (SDNN) were evaluated for OSA severity using analysis of variance, trajectory analysis, and multinomial logistic regression. A total of 228 patients were enrolled, 47 with mild OSA, 48 moderate, and 133 severe.Patients with severe OSA exhibited reduced triangular index and higher very low frequency than those in the other groups. Circadian HRV showed that nocturnal SDNN was considerably higher than daytime SDNN in patients with severe OSA. The difference among the OSA groups was significant at 23, 24, 2, and 3 o'clock sharp between the severe and moderate OSA groups (all P<0.05). The heterogeneity of circadian HRV trajectories in OSA was strongly associated with OSA severity, including sleep structure and hypoxia-related parameters. Among the low-to-low, low-to-high, high-to-low, and high-to-high groups, OSA severity in the low-to-high group was the most severe, especially compared with the low-to-low and high-to-low SDNN groups, respectively. Circadian HRV in patients with OSA emerged as low daytime and high nocturnal in SDNN, particularly in men with severe OSA. The heterogeneity of circadian HRV revealed that trajectories with low daytime and significantly high nighttime were more strongly associated with severe OSA. Thus, circadian HRV trajectories may be useful to identify the severity of OSA.

Measure by measure: Resting heart rate across the 24-hour cycle.

Photoplethysmography (PPG) sensors, typically found in wrist-worn devices, can continuously monitor heart rate (HR) in large populations in real-world settings. Resting heart rate (RHR) is an important biomarker of morbidities and mortality, but no universally accepted definition nor measurement criteria exist. In this study, we provide a working definition of RHR and describe a method for accurate measurement of this biomarker, recorded using PPG derived from wristband measurement across the 24-hour cycle. 433 healthy subjects wore a wrist device that measured activity and HR for up to 3 months. HR during inactivity was recorded and the duration of inactivity needed for HR to stabilise was ascertained. We identified the lowest HR during each 24-hour cycle (true RHR) and examined the time of day or night this occurred. The variation of HR during inactivity through the 24-hour cycle was also assessed. The sample was also subdivided according to daily activity levels for subset analysis. Adequate data was obtained for 19,242 days and 18,520 nights. HR stabilised in most subjects after 4 minutes of inactivity. Mean (SD) RHR for the sample was 54.5 (8.0) bpm (day) and 50.5 (7.6) bpm (night). RHR values were highest in the least active group (lowest MET quartile). A circadian variation of HR during inactivity was confirmed, with the lowest values being between 0300 and 0700 hours for most subjects. RHR measured using a PPG-based wrist-worn device is significantly lower at night than in the day, and a circadian rhythm of HR during inactivity was confirmed. Since RHR is such an important health metric, clarity on the definition and measurement methodology used is important. For most subjects, a minimum rest time of 4 minutes provides a reliable measurement of HR during inactivity and true RHR in a 24-hour cycle is best measured between 0300 and 0700 hours. Funding: This study was funded by Google.

Validation of heart rate spot-check protocol to measure circadian variation and heart rate in healthy dogs and dogs with atrial fibrillation

IntroductionAlternatives for out-of-clinic heart rate (HR) measurement are required to optimise the management of atrial fibrillation (AF) in dogs. Additionally, the presence of circadian variation (CV) in HR in pet dogs remains unknown.We aimed to identify the number and duration of spot-checks required for an accurate estimation of 24-hour HR in canine AF. Circadian variation in HR was examined in healthy dogs and dogs with AF, and spot-check-derived HR was compared with a CV-derived gold standard. Materials and methodsAmbulatory electrocardiogram data from healthy dogs and dogs with AF were retrospectively analysed. Heart rate was calculated from the entire recording and pre-defined periods (spot-checks) of one hour to 30 and 60 s in duration. Circadian variation in HR was determined by cosinor analysis. Bias and limits of agreement of means and median HR with mesor HR were determined by correlation and Bland–Altman analysis. ResultsCircadian variation in HR was identified not only in 18/22 healthy dogs and 14/21 AF dogs but only on ambulatory electrocardiogram recordings.Four-hourly spot-checks provided the most accurate estimate of mesor HR in healthy dogs (bias of the median over 30 s 7.70, limits of agreement 7.48), whereas, in dogs with AF, four, six and eight-hourly spot-checks provided reliable estimates of mesor HR (bias within −1.29 and −29.5). ConclusionsFour, six and eight-hourly HR spot-checks can estimate 24-hourly HR in dogs with AF. There was CV in HR in most healthy pet dogs and dogs with AF. Spot-check protocols cannot identify CV in HR.

Evaluation of a machine learning approach utilizing wearable data for prediction of SARS-CoV-2 infection in healthcare workers.

ObjectiveTo determine whether a machine learning model can detect SARS-CoV-2 infection from physiological metrics collected from wearable devices.Materials and MethodsHealth care workers from 7 hospitals were enrolled and prospectively followed in a multicenter observational study. Subjects downloaded a custom smart phone app and wore Apple Watches for the duration of the study period. Daily surveys related to symptoms and the diagnosis of Coronavirus Disease 2019 were answered in the app.ResultsWe enrolled 407 participants with 49 (12%) having a positive nasal SARS-CoV-2 polymerase chain reaction test during follow-up. We examined 5 machine-learning approaches and found that gradient-boosting machines (GBM) had the most favorable validation performance. Across all testing sets, our GBM model predicted SARS-CoV-2 infection with an average area under the receiver operating characteristic (auROC) = 86.4% (confidence interval [CI] 84–89%). The model was calibrated to value sensitivity over specificity, achieving an average sensitivity of 82% (CI ±∼4%) and specificity of 77% (CI ±∼1%). The most important predictors included parameters describing the circadian heart rate variability mean (MESOR) and peak-timing (acrophase), and age.DiscussionWe show that a tree-based ML algorithm applied to physiological metrics passively collected from a wearable device can identify and predict SARS-CoV-2 infection.ConclusionApplying machine learning models to the passively collected physiological metrics from wearable devices may improve SARS-CoV-2 screening methods and infection tracking.

Consumer-grade wearables identify changes in multiple physiological systems during COVID-19 disease progression

SummaryConsumer-grade wearables are needed to track disease, especially in the ongoing pandemic, as they can monitor patients in real time. We show that decomposing heart rate from low-cost wearable technologies into signals from different systems can give a multidimensional description of physiological changes due to COVID-19 infection. We find that the separate physiological features of basal heart rate, heart rate response to physical activity, circadian variation in heart rate, and autocorrelation of heart rate are significantly altered and can classify symptomatic versus healthy periods. Increased heart rate and autocorrelation begin at symptom onset, while the heart rate response to activity increases soon after symptom onset and increases more in individuals exhibiting cough. Symptom onset is associated with a blunting of circadian variation in heart rate, as measured by the uncertainty in the phase estimate. This work establishes an innovative data analytic approach to monitor disease progression remotely using consumer-grade wearables.

Association between circadian variation of heart rate and mortality among critically ill patients: a retrospective cohort study

BackgroundHeart rate (HR) related parameters, such as HR variability, HR turbulence, resting HR, and nighttime mean HR have been recognized as independent predictors of mortality. However, the influence of circadian changes in HR on mortality remains unclear in intensive care units (ICU). The study is designed to evaluate the relationship between the circadian variation in HR and mortality risk among critically ill patients.MethodsThe present study included 4,760 patients extracted from the Multiparameter Intelligent Monitoring in Intensive Care II database. The nighttime mean HR/daytime mean HR ratio was adopted as the circadian variation in HR. According to the median value of the circadian variation in HR, participants were divided into two groups: group A (≤ 1) and group B (> 1). The outcomes included ICU, hospital, 30-day, and 1-year mortalities. The prognostic value of HR circadian variation was investigated by multivariable logistic regression models and Cox proportional hazards models.ResultsPatients in group B (n = 2,471) had higher mortality than those in group A (n = 2,289). Multivariable models revealed that the higher circadian variation in HR was associated with ICU mortality (odds ratio [OR], 1.393; 95% confidence interval [CI], 1.112–1.745; P = 0.004), hospital mortality (OR, 1.393; 95% CI, 1.112–1.745; P = 0.004), 30-day mortality (hazard ratio, 1.260; 95% CI, 1.064–1.491; P = 0.007), and 1-year mortality (hazard ratio, 1.207; 95% CI, 1.057–1.378; P = 0.005), especially in patients with higher SOFA scores.ConclusionsThe circadian variation in HR might aid in the early identification of critically ill patients at high risk of associated with ICU, hospital, 30-day, and 1-year mortalities.

A circadian clock in the sinus node mediates day-night rhythms in Hcn4 and heart rate

BackgroundHeart rate follows a diurnal variation, and slow heart rhythms occur primarily at night.ObjectiveThe lower heart rate during sleep is assumed to be neural in origin, but here we tested whether a day-night difference in intrinsic pacemaking is involved.MethodsIn vivo and in vitro electrocardiographic recordings, vagotomy, transgenics, quantitative polymerase chain reaction, Western blotting, immunohistochemistry, patch clamp, reporter bioluminescence recordings, and chromatin immunoprecipitation were used.ResultsThe day-night difference in the average heart rate of mice was independent of fluctuations in average locomotor activity and persisted under pharmacological, surgical, and transgenic interruption of autonomic input to the heart. Spontaneous beating rate of isolated (ie, denervated) sinus node (SN) preparations exhibited a day-night rhythm concomitant with rhythmic messenger RNA expression of ion channels including hyperpolarization-activated cyclic nucleotide-gated potassium channel 4 (HCN4). In vitro studies demonstrated 24-hour rhythms in the human HCN4 promoter and the corresponding funny current. The day-night heart rate difference in mice was abolished by HCN block, both in vivo and in the isolated SN. Rhythmic expression of canonical circadian clock transcription factors, for example, Brain and muscle ARNT-Like 1 (BMAL1) and Cryptochrome (CRY) was identified in the SN and disruption of the local clock (by cardiomyocyte-specific knockout of Bmal1) abolished the day-night difference in Hcn4 and intrinsic heart rate. Chromatin immunoprecipitation revealed specific BMAL1 binding sites on Hcn4, linking the local clock with intrinsic rate control.ConclusionThe circadian variation in heart rate involves SN local clock–dependent Hcn4 rhythmicity. Data reveal a novel regulator of heart rate and mechanistic insight into bradycardia during sleep.

Impaired circadian heart rate variability in Parkinson\u2019s disease: a time-domain analysis in ambulatory setting

BackgroundHeart rate variability (HRV) decreases in Parkinson’s disease (PD) and it can be considered a marker for cardiovascular dysautonomia. The purpose of this pilot study is to evaluate long-term time-domain analysis of HRV of PD patients and compare the results with those of matched healthy individuals.MethodsIdiopathic PD patients without comorbidity impairing HRV, and age-matched healthy individuals were recruited in a pilot study. A long-term time domain analysis of HRV using 24-h ambulatory ECG was performed.ResultsOverall, 18 PD patients fulfilling inclusion criteria completed the evaluation (mean age was 55.6 ± 8.8, disease duration: 5.0 ± 4.7). Mean SCOPA-AUT score was 10.1 ± 7.3. Patients were on Hoehn & Yahr stage 1–2 and mean Levodopa Equivalent Dose (LED) was 311 ± 239.9. Mean of the 5-min standard deviation (SD) of R-R intervals distribution (SDNN) for all 5 min segments of the entire recording (ISDNN) was significantly lower in patients compared to controls. ISDNN was significantly different between Parkinson’s disease patients and healthy controls.ConclusionsIn our population characterized by mild to moderate disease severity, time-domain assessment of HRV seemed to be a potential tool to characterize cardiovascular dysautonomia. Decrease of ISDNN in PD may reflect an autonomic derangement extending all day and night long.

Serum endocan and circadian heart rate variability in non-dialysis stage 5 chronic kidney disease patients.

Chronic kidney disease (CKD) is very common now and is associated with high overall and cardiovascular mortality. Numerous studies have reported that elevated heart rate (HR) is a risk factor for cardiovascular mortality. We investigated the link between serum endocan and circadian heart rate variability in non-dialysis stage 5 CKD patients. In a cross-sectional study, we enrolled 54 prevalent n non-dialysis stage 5 CKD patients (32 males, aged 48.2 ± 14.92years). HR was measured with an automatic system. Serum endocan level was analyzed by ELISA. Night/day HR ratio was independently predicted by serum endocan level (P < 0.01) and hypertension history (P < 0.05). Adjusted R2 of the model was 0.222. Increased serum endocan is significantly associated with circadian heart rate variability in non-dialysis stage 5 CKD patients. Further investigation is needed to explore the potential benefits of serum endocan lowering therapy in this patient group.

P6410QT intervals during sleep and circadian heart rate variability in healthy and long QT syndrome (LQTS) infants

P6410QT intervals during sleep and circadian heart rate variability in healthy and long QT syndrome (LQTS) infants

Spontaneous ventricular tachyarrhythmias in β2-adrenoceptor transgenic mice in relation to cardiac interstitial fibrosis.

Myocardial fibrosis is regarded as a pivotal proarrhythmic substrate, but there have been no comprehensive studies showing a correlation between the severity of fibrosis and ventricular tachyarrhythmias (VTAs). Our purpose was to document this relationship in a transgenic (TG) strain of mice with fibrotic cardiomyopathy. TG mice with cardiac overexpression of β2-adrenoceptors (β2-AR mice) and non-TG (NTG) littermates were studied at 4-12 mo of age. VTA was quantified by ECG telemetry. The effect of pharmacological blockade of β2-ARs on VTA was examined. Myocardial collagen content was determined by hydroxyproline assay. NTG and TG mice displayed circadian variation in heart rate, which was higher in TG mice than in NTG mice (P <0.05). Frequent spontaneous ventricular ectopic beats (VEBs) and ventricular tachycardia (VT) were prominent in TG mice but not present in NTG mice. The frequency of VEB and VT episodes in TG mice increased with age (P < 0.01). Ventricular collagen content was greater in TG mice than in NTG mice (P <0.001) and correlated with age (r = 0.71, P < 0.01). The number of VEBs or VT episodes correlated with age (r = 0.83 and r = 0.73) and the content of total or cross-linked collagen (r = 0.62∼0.66, all P <0.01). While having no effect in younger β2-TG mice, β2-AR blockade reduced the frequency of VTA in old β2-TG mice with more severe fibrosis. In conclusion, β2-TG mice exhibit interstitial fibrosis and spontaneous onset of VTA, becoming more severe with aging. The extent of cardiac fibrosis is a major determinant for both the frequency of VTA and proarrhythmic action of β2-AR activation.

PP.12.04

Objective: To evaluate by performing 24-h ambulatory blood pressure monitoring (ABPM) circadian variation of heart rate (HR) with the purpose of establish a classification of the variation of HR according to the frequency and magnitude of its decrease or increase in normotensive and untreated hypertensive patients. Design and method: 561 patients who underwent 24-h ABPM. After performing ABPM the total sample was classified in 02 groups: Normotensive patients (NP): (n = 302, 63.4% female, 49.59 ± 14.84 years, BMI: 28.03 ± 4.93 Kg/m2) and hypertensive patients (HP): (n = 259, 58.6% male, 48.94 ± 14.06 years, BMI: 29.72 ± 6.24 Kg/m2). The circadian variation of HR was calculated as the difference percentage between the average of HR during the day and night. The development of a scale of variation of HR by absolute and percentage frequencies has been the method used to classify the variation of the same. Results: In this study it was found a decrease of average heart rate during the day to night of 10 to 19% was the most frequent circadian variation in normotensive and hypertensive patients (55% and 56%, respectively), (Table 1, 2).Conclusions: Our results suggest that the circadian variation of the mean of HR between 10 to 19% represent the cutoff to establish normal range of this variable in normotensive and hypertensive patients.

Flexible and waterproof micro-sensors to uncover zebrafish circadian rhythms: The next generation of cardiac monitoring for drug screening.

Flexible electronics are the next generation of sensors for mobile health and implantation. Zebrafish (Danio rerio) is an emergent strategy for pre-clinical drug development and toxicity testing. To address the confounding effects from sedation of fish and removal from the aquatic habitat for micro-electrocardiogram (µECG) measurements, we developed waterproof and wearable sensors to uncover the circadian variation in heart rate (HR) and heart rate variability (HRV) (Massin et al., 2000). The parylene-C based ECG sensor consisted of an ultra-soft silicone integrated jacket designed to wrap around the fish during swimming. The Young's modulus of this silicone jacket matched with the fish surface, and an extended parylene cable connected the underwater chest electrodes with the out-of water electronics. In addition, embedded micro-glass spheres in the silicone effectively reduced the effective density of the jacket to ~1 g cm(-3). These innovations enabled physiological ECG telemetry in the fish's natural habitat without the need for sedation. Furthermore, a set of non-linear signal processing techniques filtered out the breathing and electromagnetic artifacts from the recorded signals. We observed a reduction in mean HR and an increase in HRV over 24h at 10 dpa, accompanied by QT prolongation as well as diurnal variations, followed by normalization in mean HR and QT intervals at 26 days post ventricular amputation (dpa). We revealed Amiodarone-mediated QTc prolongation, HR reduction and HRV increase otherwise masked by sedation. The novel features of the flexible silicon jacket for µECG telemetry unraveled the biological clock and normalization of QT intervals at 26 dpa, providing the first evidence of new physiological phenomena during cardiac injury and repair as well as cardiac drug-mediated aberrant rhythms. Thus, the light weight and waterproof design holds promise to advance the next generation of mobile health and drug discovery.

Circadian Rhythm of Autonomic Cardiovascular Control During Mars500 Simulated Mission to Mars

The Mars500 project was conceived to gather knowledge about the psychological and physiological effects of living in an enclosed environment during 520 d as would be required for a real mission to Mars. Our objective was to investigate the circadian profile of heart rate variability (HRV) in the context of the Mars500 study. Before, during, and after confinement, 24-h EKG records were obtained from the six crewmembers who participated in the mission. Autonomic activity was evaluated through time and frequency domain indexes of HRV analysis. Circadian rhythmicity was assessed both by averaging hourly HRV along wake and sleep scheduled periods and by fitting a 24-h harmonic to the hourly means. During confinement, wake HRV showed (mean +/- SE) a progressive increase in mean RR interval (from 778 +/- 24 ms to 916 +/- 42 ms), and in the amplitude (values are wavelet power coefficients) of very low (from 13.3 +/- 0.3 to 14.1 +/- 0.2) and high (from 7.8 +/- 0.4 to 8.3 +/- 0.3) frequency components. During sleep, the relative amplitude of the high frequency component of HRV decreased (from 11.8 +/- 1.6 to 9.4 +/- 1.8 normalized units). Overall, sleep-wake differences of HRV showed a progressive decrease of the relative amplitude of the high frequency component. Also, circadian HRV rhythms were dampened during confinement. Data revealed diminished amplitude of the rest-activity pattern of the autonomic nervous system parasympathetic function. Reduced daylight exposure and mood changes could account for this observation.

The cardiomyocyte molecular clock, regulation of Scn5a, and arrhythmia susceptibility

The molecular clock mechanism underlies circadian rhythms and is defined by a transcription-translation feedback loop. Bmal1 encodes a core molecular clock transcription factor. Germline Bmal1 knockout mice show a loss of circadian variation in heart rate and blood pressure, and they develop dilated cardiomyopathy. We tested the role of the molecular clock in adult cardiomyocytes by generating mice that allow for the inducible cardiomyocyte-specific deletion of Bmal1 (iCSΔBmal1). ECG telemetry showed that cardiomyocyte-specific deletion of Bmal1 (iCSΔBmal1(-/-)) in adult mice slowed heart rate, prolonged RR and QRS intervals, and increased episodes of arrhythmia. Moreover, isolated iCSΔBmal1(-/-) hearts were more susceptible to arrhythmia during electromechanical stimulation. Examination of candidate cardiac ion channel genes showed that Scn5a, which encodes the principle cardiac voltage-gated Na(+) channel (Na(V)1.5), was circadianly expressed in control mouse and rat hearts but not in iCSΔBmal1(-/-) hearts. In vitro studies confirmed circadian expression of a human Scn5a promoter-luciferase reporter construct and determined that overexpression of clock factors transactivated the Scn5a promoter. Loss of Scn5a circadian expression in iCSΔBmal1(-/-) hearts was associated with decreased levels of Na(V)1.5 and Na(+) current in ventricular myocytes. We conclude that disruption of the molecular clock in the adult heart slows heart rate, increases arrhythmias, and decreases the functional expression of Scn5a. These findings suggest a potential link between environmental factors that alter the cardiomyocyte molecular clock and factors that influence arrhythmia susceptibility in humans.

Abstract 8823: Abnormal Cardiac Innervation in Ventricular Fibrillation Patients with and Without Brugada Syndrome

Abnormal cardiac innervation in patients with ventricular fibrillation (VF) has been reported. We investigated autonomic function in 48 successfully resuscitated VF patients using heart rate variability (HRV) as measured by Holter ECG and 123 I-metaiodobenzylguanidine ( 123 I-MIBG) scintigraphy. Eight patients were excluded because of hypertrophic cardiomyopathy (N = 2), arrhythmogenic right ventricular cardiomyopathy (N = 3), catecholamine-sensitive ventricular tachycardia (N = 1), and long QT syndrome (N = 2). Patients who could not discontinue internal remedies (N = 5) were also excluded. Fifteen patients (42 ± 14 years, 15 males) were diagnosed with Brugada syndrome (BS), and the remaining 20 patients (47 ± 6 years, 8 males) were diagnosed with idiopathic VF (IVF). QTc time was longer in the IVF patients than in the BS patients (450.1 ± 10.1 ms vs. 389.4 ± 21.0 ms, P &lt; 0.05). RMS40 was lower in the BS patients than in the IVF patients (13.9 ± 2.2 mV vs. 20.9 ± 3.6 mV, P &lt; 0.05). Parameters of HRV were similar in both groups, but abnormal circadian variations of HRV were observed in 53.3% of BS patients and 13.3% of IVF patients. The washout ratio was higher in the IVF patients than in the BS patients (36.3 ± 4.3 vs. 26.0 ± 2.1). The 123 I-MIBG uptake was increased in lateral regions in BS patients. Regionally reduced 123 I-MIBG uptake was observed with many variations in all patients, but no significant difference was observed between groups. These results demonstrated impairment of sympathetic innervation or enhanced activity of the sympathetic nervous system in patients with VF, particularly indicating sympathetic hypertonia in IVF and imbalance of circadian HRV in BS. These findings may have an impact on the arrhythmogenesis of such patients.

Povezanost intraventrikularnih poremećaja provođenja i cirkadijalnih promena varijabilnosti srčane frekvencije kod bolesnika sa ishemijskom miokardiopatijom

Introdaction:Left bundle branch block (LBBB) and intraventricular conduction delay (IVCD) are associated with an increased arrhythmic risk in post-infarction patients with left ventricular (LV) dysfunction. The incidence of arrhythmic death is highest in the morning, possibly reflecting an autonomic imbalance. AIM: analysis of circadian heart rate variability changes (HRV) in post- infarction patients with LVEF ≤35%, with and without LBBB/IVCD. METHOD: 2 groups were included: Group-1 (n=27) with narrow QRS complexes (<110 ms), and Group-2 (n=28) with LBBB/ IVCD. Spectral HRV analysis was performed to obtain measures of total variability (total power-TP), low-frequency (LF) and high-frequency (HF) components, and LF/HF ratio. Comparisons between the groups were made using mean day-time (08 am - 08 pm) and night-time (08 pm - 08 am) HRV measures. RESULTS: no differences were found regarding clinical characteristics or LVEF (31.2±3.3 vs. 30.8±3.8%) (p>0.05 for all). Daytime (1986±635 vs. 1284±411 ms; p=0.016) and night-time (2042±701 vs. 1202±318 ms; p=0.001) TP values were higher in Group-1, as well as day-time (39.4±11.9 vs. 24.8±8.8 n.u; p<0.001) and night-time (27.5±7.3 vs. 32.8±6.6 n.u; p=0.014) LF measures, with preserved diurnal variability. Group-2 demonstrated increase in night-time LF component, lower day-time (21.5±11.7 vs. 14.5±4.4 n.u; p=0.021) and night-time (24.5±10.1 vs. 11.4±4.1 n.u; p<0.001) HF and unexpected night-time HF decrease and an increase in LF/HF ratio (p=0.002). CONCLUSION: LBBB/IVCD patients demonstrate reduced total HRV and disturbed circadian HRV pattern. Night-time LF increase and HF decrease and raised LF/HF ratio indicate augmented sympathetic and diminished parasympathetic modulation, possibly reflecting an increased arrhythmic risk.

Impact of Muscarinic M2 Receptor Loss of Function on Circadian Variation in Heart Rate

Impact of Muscarinic M2 Receptor Loss of Function on Circadian Variation in Heart Rate