Predictive values of heart rate variability, deceleration and acceleration capacity of heart rate in post-infarction patients with LVEF ≥35

Ambulatory electrocardiographic longitudinal monitoring in a canine model for Duchenne muscular dystrophy identifies decreased very low frequency power as a hallmark of impaired heart rate variability

Duchenne muscular dystrophy (DMD) patients exhibit a late left ventricular systolic dysfunction preceded by an occult phase, during which myocardial fibrosis progresses and some early functional impairments can be detected. These latter include electrocardiographic (ECG) and heart rate variability (HRV) abnormalities. This longitudinal study aimed at describing the sequence of ECG and HRV abnormalities, using Holter ECG in the GRMD (Golden retriever muscular dystrophy) dog model, known to develop a DMD-like disease, including cardiomyopathy. Most of the known ECG abnormalities described in DMD patients were also found in GRMD dogs, including increased heart rate, prolonged QT and shortened PR intervals, ventricular arrhythmias, and several of them could be detected months before the decrease of fractional shortening. The HRV was impaired like in DMD patients, one of the earliest evidenced abnormalities being a decrease in the very low frequency (VLF) component of the power spectrum. This decrease was correlated with the further reduction of fractional shortening. Such decreased VLF probably reflects impaired autonomic function and abnormal vasomotor tone. This study provides new insights into the knowledge of the GRMD dog model and DMD cardiomyopathy and emphasizes the interest to monitor the VLF power in DMD patients, still unexplored in this disease, whilst it is highly predictive of deleterious clinical events in many other pathological conditions.

Heart rate variability is reduced in COVID-19 survivors and associated with physical activity and fatigue

Reduced heart rate variability (HRV) and fatigue are common after COVID-19 infection and both are potentially influenced by physical activity (PA). We compared resting HRV, PA from accelerometers and questionnaires, and self-reported fatigue in 41 COVID-19 survivors (~8 months postinfection, 38 ± 17 years) with 41 matched controls. Differences in HRV were observed on acceleration capacity (p = 0.041), deceleration capacity (p = 0.032), high-frequency peak frequency (p = 0.019), absolute low-frequency power (p = 0.042), relative very low-frequency power (p = 0.012), SD2 (from Poincare plot; p = 0.047), and DFA2 (slope of long-term detrended fluctuation analysis; p = 0.004). Fatigue was greater in COVID-19 survivors (p < 0.001) with no differences in PA. Moderate-vigorous physical activity (MVPA) (Standardized Beta = -0.427, p = 0.003) and steps per day (Standardized Beta = -0.402, p = 0.007) were associated with DFA2 in COVID-19 survivors after controlling for age, sex, and body fat percentage. Fatigue was correlated to less MVPA (Spearman's rho = 0.342, p = 0.031) and fewer steps per day (rho = 0.329, p = 0.038) in COVID-19 survivors, and was indirectly linked to HRV through these PA mediators (Estimate = -0.20; p = 0.040). We present a model showing the complex relations between HRV, PA, and fatigue that provides the foundation for strategies to improve outcomes and rehabilitation after COVID-19 infection.

Heart rhythm complexity analysis in patients with inferior ST-elevation myocardial infarction

Heart rhythm complexity (HRC), a subtype of heart rate variability (HRV), is an important tool to investigate cardiovascular disease. In this study, we aimed to analyze serial changes in HRV and HRC metrics in patients with inferior ST-elevation myocardial infarction (STEMI) within 1 year postinfarct and explore the association between HRC and postinfarct left ventricular (LV) systolic impairment. We prospectively enrolled 33 inferior STEMI patients and 74 control subjects and analyzed traditional linear HRV and HRC metrics in both groups, including detrended fluctuation analysis (DFA) and multiscale entropy (MSE). We also analyzed follow-up postinfarct echocardiography for 1 year. The STEMI group had significantly lower standard deviation of RR interval (SDNN), and DFAα2 within 7 days postinfarct (acute stage) comparing to control subjects. LF power was consistently higher in STEMI group during follow up. The MSE scale 5 was higher at acute stage comparing to control subjects and had a trend of decrease during 1-year postinfarct. The MSE area under scale 1-5 showed persistently lower than control subjects and progressively decreased during 1-year postinfarct. To predict long-term postinfarct LV systolic impairment, the slope between MSE scale 1 to 5 (slope 1-5) had the best predictive value. MSE slope 1-5 also increased the predictive ability of the linear HRV metrics in both the net reclassification index and integrated discrimination index models. In conclusion, HRC and LV contractility decreased 1 year postinfarct in inferior STEMI patients, and MSE slope 1-5 was a good predictor of postinfarct LV systolic impairment.

Evaluation of measurement accuracy of wearable devices for heart rate variability

This paper proposed a method based on heart rate variability (HRV) for evaluating the accuracy of wearable devices in measuring heart rate. HRV refers to the variation in time intervals between successive heartbeats, widely used in many fields such as clinical and sports fields. Wearable devices such as Electrocardiogram (ECG) electrode patches have gained popularity due to their portability and ease of use. However, they can be prone to measurement interference caused by environmental noise, human respiration, etc. The proposed method consists of four main components: selection of "gold standard measurement devices", identification of HRV measurement metrics, construction of an HRV evaluation framework, and quantification of measurement errors. The method is validated through simulated experiments using ECG patches. The evaluation framework and quantification model established in this method have significant implications in establishment of industry standards and diagnosis of diseases in clinical practice.

A case report of autoimmune GFAP astrocytopathy presenting with abnormal heart rate variability and blood pressure variability

BACKGROUND

Autonomic dysfunctions including bladder dysfunction, gastrointestinal dysfunction and orthostasis are common symptoms of autoimmune glial fibrillary acidic protein astrocytopathy (A-GFAP-A); however, cardiac autonomic dysfunction and abnormal circadian rhythm of blood pressure, which can lead to poor prognosis and even sudden cardiac death, has never been reported in A-GFAP-A patient.

CASE PRESENTATION

A 68-year-old male Chinese patient presented to our hospital with headache, fever, progressive disturbance of consciousness, dysuria, and limb weakness. Abnormal heart rate variability and non-dipper circadian rhythm of blood pressure gradually developed during hospitalization, which is rare in A-GFAP-A. He had positive GFAP IgG in cerebrospinal fluid (CSF). Enhanced brian MRI showed uneven enhancement and T2 hyperintense lesions of medulla oblongata; Cervical spine MRI showed T2 hyperintense lesions in medulla oblongata and upper margin of the T2 vertebral body. A contrast-enhanced thoracic spine MRI showed uneven enhancement and T2 hyperintense lesions of T1 to T6 vertebral segments. After treatment with intravenous immunoglobulin and corticosteroids, the patient's symptoms, including autonomic dysfunction, alleviated dramatically. Finally, his heart rate variability and blood pressure variability became normal.

CONCLUSIONS

Our case broadens the spectrum of expected symptoms in A-GFAP- A syndromes as it presented with heart rate variability and blood pressure variability.

Impact of Short-Term Heart Rate Variability in Patients with STEMI Treated by Delayed versus Immediate Stent in Primary Percutaneous Coronary Intervention: A Prospective Cohort Study

Objective

Patients with ST-segment elevated myocardial infarction (STEMI) have been treated with the delayed stent strategy to reduce the occurrence of postoperative no-reflow and improve the recovery of postoperative cardiac function. However, the effects of electrocardiac activity and autonomic nerve function after primary percutaneous coronary intervention (pPCI) have been rarely reported. The purpose of this study was to investigate the effects of short-term heart rate variability (HRV) in patients with STEMI treated by immediate stent (IS) and delayed stent (DS) strategy.

Methods

A total of 178 patients with STEMI were divided into 124 cases (69.66%) in the IS group and 54 cases (30.34%) in the DS group from July 2019 to September 2021. The mean heart rate, premature ventricular contraction (PVC), left ventricular ejection fraction (LVEF), left ventricular end-diastolic diameter (LVED), and HRV indexes were compared between the two groups.

Results

In terms of cardiac electrical stability, the number of PVCs, the percentage of PVCs, and the number of paired PVCs in the DS group were lower than those in the IS group. In terms of HRV, high frequency (HF) and standard deviation of all NN (SDNN) intervals were higher in the patients with DS strategy than IS strategy. There were no significant differences in the LVED and LVEF between the two groups.

Conclusion

Compared to the IS strategy, the DS strategy in pPCI in patients with STEMI has advantages in postoperative cardiac electrical stability and short-term cardiac autonomic nerve function, with no difference in postoperative short-term cardiac function.

Enhanced detection of abnormalities in heart rate variability and dynamics by 7-day continuous ECG monitoring

Background

The analysis of heart rate variability (HRV) and heart rate (HR) dynamics by Holter ECG has been standardized to 24 hs, but longer‐term continuous ECG monitoring has become available in clinical practice. We investigated the effects of long‐term ECG on the assessment of HRV and HR dynamics.

Methods

Intraweek variations in HRV and HR dynamics were analyzed in 107 outpatients with sinus rhythm. ECG was recorded continuously for 7 days with a flexible, codeless, waterproof sensor attached on the upper chest wall. Data were divided into seven 24‐h segments, and standard time‐ and frequency‐domain HRV and nonlinear HR dynamics indices were computed for each segment.

Results

The intraweek coefficients of variance of HRV and HR dynamics indices ranged from 2.9% to 26.0% and were smaller for frequency‐domain than for time‐domain indices, and for indices reflecting slower HR fluctuations than faster fluctuations. The indices with large variance often showed transient abnormalities from day to day over 7 days, reducing the positive predictive accuracy of the 24‐h ECG for detecting persistent abnormalities over 7 days. Conversely, 7‐day ECG provided 2.3‐ to 6.5‐fold increase in sensitivity to detect persistent plus transient abnormalities compared with 24‐h ECG. It detected an average of 1.74 to 2.91 times as many abnormal indices as 24‐h ECG.

Conclusions

Long‐term ECG monitoring increases the accuracy and sensitivity of detecting persistent and transient abnormalities in HRV and HR dynamics and allows discrimination between the two types of abnormalities. Whether this discrimination improves risk stratification deserves further studies.

Survival Predictors of Heart Rate Variability After Myocardial Infarction With and Without Low Left Ventricular Ejection Fraction

Background

Heart rate variability (HRV) and heart rate (HR) dynamics are used to predict the survival probability of patients after acute myocardial infarction (AMI), but the association has been established in patients with mixed levels of left ventricular ejection fraction (LVEF).

Objective

We investigated whether the survival predictors of HRV and HR dynamics depend on LVEF after AMI.

Methods

We studied 687 post-AMI patients including 147 with LVEF ≤35% and 540 with LVEF >35%, of which 23 (16%) and 22 (4%) died during the 25 month follow-up period, respectively. None had an implanted cardioverter-defibrillator. From baseline 24 h ECG, the standard deviation (SDNN), root mean square of successive difference (rMSSD), percentage of successive difference >50 ms (pNN50) of normal-to-normal R-R interval, ultra-low (ULF), very-low (VLF), low (LF), and high (HF) frequency power, deceleration capacity (DC), short-term scaling exponent (α₁), non-Gaussianity index (λ_25s), and the amplitude of cyclic variation of HR (Acv) were calculated.

Results

The predictors were categorized into three clusters; DC, SDNN, α₁, ULF, VLF, LF, and Acv as Cluster 1, λ_25s independently as Cluster 2, and rMSSD, pNN50, and HF as Cluster 3. In univariate analyses, mortality was best predicted by indices belonging to Cluster 1 regardless of LVEF. In multivariate analyses, however, mortality in patients with low LVEF was best predicted by the combinations of Cluster 1 predictors or Cluster 1 and 3 predictors, whereas in patients without low LVEF, it was best predicted by the combinations of Cluster 1 and 2 predictors.

Conclusion

The mortality risk in post-AMI patients with low LVEF is predicted by indices reflecting decreased HRV or HR responsiveness and cardiac parasympathetic dysfunction, whereas in patients without low LVEF, the risk is predicted by a combination of indices that reflect decreased HRV or HR responsiveness and indicator that reflects abrupt large HR changes suggesting sympathetic involvement.

Predictive values of heart rate variability, deceleration and acceleration capacity of heart rate in post-infarction patients with LVEF ≥35

Background and aims

The aim was to investigate the predictive values of heart rate variability, deceleration, and acceleration capacity of heart rate in sudden cardiac death in postinfarction patients with left ventricular ejection fraction (LVEF) ≥ 35%.

Methods

We enrolled 138 acute myocardial infarction patients (MI) randomly in sinus rhythm with LVEF ≥ 35% after myocardial infarction. Data on heart rate variability, deceleration runs, deceleration, and acceleration capacity were obtained from 24h‐dynamic electrocardiogram recordings. Clinical characteristics, medications, and echocardiography data were noted. The endpoints were sudden cardiac arrhythmias (SCA), including malignant arrhythmias in the hospital and viewed sudden death out of the hospital. Relationships between autonomic parameters and endpoints were evaluated.

Results

During follow‐up for over 24 months in MI patients, 10 patients occurred sudden cardiac arrhythmias. Subjects with SCA showed lower levels of SDNN (p = .018), TP (p = .007), VLF (p < .001), DC (p < .001), and low‐risk DRs (p < .001) than those without SCA. A low SDNN level (HR: 8.888, p = .006), low VLF level (HR: 14.699, p = .016), low DC level (HR: 4.430, p = .045), and higher risk DRs (HR: 3.81, p = .040) were identified as independent risk factors of SCA for postinfarction patients with LVEF ≥ 35%. The area under the ROC curve (AUC) of SDNN, VLF, and DC for identification of SCA were, respectively, 0.724 (p = .019), 0.807 (p < .001), and 0.804 (p = .002). SDNN, VLF, and DC combined assessment area under the ROC curve were 0.828 (p < .001).

Conclusion

Decreased SDNN, VLF, DC, and abnormal DRs are independently associated with increased risks of sudden cardiac arrhythmias in post‐MI patients with LVEF ≥ 35%. Combined SDNN, VLF, and DC may help identify a high‐risk group of malignant arrhythmias in postinfarction patients.