Heart rate variability and incidence of depression during the first six months following first myocardial infarction

Meta-analysis on inflammation and autonomic nervous system of coronary heart disease combined with depression

OBJECTIVES

This meta-analysis aimed to explore the association between inflammatory factors, heart rate variability (HRV) and the coexistence of coronary heart disease (CHD) and depression.

DESIGN

Systematic review and meta-analysis. Complying with the Meta-analysis Of Observational Studies in Epidemiology statement.

DATA SOURCES

We searched PubMed, Web of Science and EMBASE for the data from the inception date to 16 March 2023.

ELIGIBILITY CRITERIA

We included cross-sectional and cohort studies with inclusion criteria: (1) patients with CHD; (2) depression measurement and (3) including inflammatory factors or cardiac biomarkers or HRV.

DATA EXTRACTION AND SYNTHESIS

Two authors searched the databases independently. The effect estimates and heterogeneity were synthesised by Review Manager V.5.3. Sensitivity analysis and publication bias were analysed by STATA software. The quantitative synthesis outcomes were presented by mean difference (MD) or standard MD (SMD) with 95% CI.

RESULTS

By searching the databases, we identified a total of 6750 articles. There were 22 articles left after selection, including 6344 participants. This meta-analysis indicated that patients with CHD with depression had higher levels of C reaction protein (CRP) (SMD 0.50, 95% CI (0.19 to 0.81), p=0.001), high-sensitivity C reactive protein (hs-CRP) (SMD 0.28, 95% CI (0.07 to 0.48), p=0.008), IL-6 (SMD 0.49, 95% CI (0.05 to 0.92), p=0.03) and a lower level of the mean RR interval and the SD of all RR intervals (SMD -0.64, 95% CI (-1.11 to -0.17), p=0.008), SD of the 5 min averages of all normal RR intervals (MD -12.77 ms, 95% CI (-21.20 to -4.33), p=0.003), overage of the SD of all normal RR intervals for each 5 min segment (MD -13.83 ms, 95% CI (-15.94 to -11.72), p<0.00001), root mean square of successive differences (MD: -8.02 ms, 95% CI (-13.62 to -2.43), p=0.005), proportion of adjacent cycles differing by >50 ms (pNN50) (SMD -0.86, 95% CI (-1.41 to -0.31), p=0.002), than those without depression.

CONCLUSIONS

This study underscores the association between elevated CRP, hs-CRP, IL-6 and lower HRV in patients with CHD with depression. It emphasises the importance of clinicians assessing CRP, hs-CRP, IL-6 and HRV in patients with CHD to potentially identify depressive conditions.

Shuangxinfang Prevents S100A9-Induced Macrophage/Microglial Inflammation to Improve Cardiac Function and Depression-Like Behavior in Rats After Acute Myocardial Infarction

Background: Depression is a common complication of cardiovascular disease, which deteriorates cardiac function. Shuangxinfang (psycho-cardiology formula, PCF) was reported to alleviate myocardial ischemia injury and improve depression-like behavior. Interestingly, our previous proteomics study predicted that the protein S100A9 appeared as an important target, and macrophage/microglial inflammation might be involved in the process of PCF improving depression induced by acute myocardial infarction (AMI). This study aims to validate the proteomics results.

Methods: AMI rat models were established in vivo, followed by the administration of PCF or ABR-215757 (also named paquinimod, inhibiting S100A9 binding to TLR4) for 5 days. Forced swimming test (FST) and open field test (OFT) were applied to record depression-like behavior, and echocardiography was employed to evaluate cardiac function. Morphological changes of cardiomyocytes were assessed by HE staining and TUNEL staining on day 7 after cardiac surgery, as well as Masson trichrome staining on day 21. Hippocampal neurogenesis was determined by Nissl staining, while 5-hydroxytryptamine (5-HT), tryptophan/kynurenine ratio, and brain-derived neurotrophic factor (BDNF) in the hippocampus were analyzed as biochemical indicators of depression. We employed RT-qPCR, western blotting, and immunofluorescence to detect the expression of pathway-related genes and proteins. Myocardial and hippocampal expression of inflammatory factors were performed by ELISA. The activation of macrophage and microglia was assessed via immunoreaction using CD68 and Iba1, respectively. For in vitro confirmation, BV2 cells were primed with recombinant protein S100A9 and then treated with PCF serum or ferulic acid to determine alterations in microglial inflammation.

Results: Rats in the AMI group showed heart function deterioration and depression-like behavior. Coronary ligation not only brought about myocardial inflammation, cell apoptosis, and fibrosis but also reduced the neurogenesis, elevated the tryptophan/kynurenine ratio, and decreased the content of 5-HT. PCF could ameliorate the pathological and phenotypic changes in the heart and brain and inhibit the expression of the S100A9 protein, the activation of the microglial cell, and the secretion of IL-1β and TNF-α raised by AMI. ABR-215757 showed therapeutic effect and molecular biological mechanisms similar to PCF. Treatment with PCF serum or ferulic acid in vitro was proved to efficiently block the hyperactivation of BV2 cells and increment of cytokine contents induced by recombinant protein S100A9.

Conclusion: We identify S100A9 as a novel and potent regulator of inflammation in both the heart and brain. Macrophage/microglia inflammation mediated by S100A9 is considered a pivotal pathogenic in depression after AMI and a major pathway for the treatment of PCF, suggesting that PCF is a promising therapeutic candidate for psycho-cardiology disease.

A particle swarm optimization improved BP neural network intelligent model for electrocardiogram classification

BACKGROUND

As proven to reflect the work state of heart and physiological situation objectively, electrocardiogram (ECG) is widely used in the assessment of human health, especially the diagnosis of heart disease. The accuracy and reliability of abnormal ECG (AECG) decision depend to a large extent on the feature extraction. However, it is often uneasy or even impossible to obtain accurate features, as the detection process of ECG is easily disturbed by the external environment. And AECG got many species and great variation. What's more, the ECG result obtained after a long time past, which can not reach the purpose of early warning or real-time disease diagnosis. Therefore, developing an intelligent classification model with an accurate feature extraction method to identify AECG is of quite significance. This study aimed to explore an accurate feature extraction method of ECG and establish a suitable model for identifying AECG and the diagnosis of heart disease.

METHODS

In this research, the wavelet combined with four operations and adaptive threshold methods were applied to filter the ECG and extract its feature waves first. Then, a BP neural network (BPNN) intelligent model and a particle swarm optimization (PSO) improved BPNN (PSO-BPNN) intelligent model based on MIT-BIH open database was established to identify ECG. To reduce the complexity of the model, the principal component analysis (PCA) was used to minimize the feature dimension.

RESULTS

Wavelet transforms combined four operations and adaptive threshold methods were capable of ECG filtering and feature extraction. PCA can significantly deduce the modeling feature dimension to minimize the complexity and save classification time. The PSO-BPNN intelligent model was suitable for identifying five types of ECG and showed better effects while comparing it with the BPNN model.

CONCLUSION

In summary, it was further concluded that the PSO-BPNN intelligent model would be a suitable way to identify AECG and provide a tool for the diagnosis of heart disease.

Impact of Water Temperature on Heart Rate Variability during Bathing

Background: Heart rate variability (HRV) is affected by many factors. This paper aims to explore the impact of water temperature (WT) on HRV during bathing. Methods: The bathtub WT was preset at three conditions: i.e., low WT (36–38 °C), medium WT (38–40 °C), and high WT (40–42 °C), respectively. Ten subjects participated in the data collection. Each subject collected five electrocardiogram (ECG) recordings at each preset bathtub WT condition. Each recording was 18 min long with a sampling rate of 200 Hz. In total, 150 ECG recordings and 150 WT recordings were collected. Twenty HRV features were calculated using 1-min ECG segments each time. The k-means clustering analysis method was used to analyze the rough trends based on the preset WT. Analyses of the significant differences were performed using the multivariate analysis of variance of t-tests, and the mean and standard deviation (SD) of each HRV feature based on the WT were calculated. Results: The statistics show that with increasing WT, 11 HRV features are significantly (p < 0.05) and monotonously reduced, four HRV features are significantly (p < 0.05) and monotonously rising, two HRV features are rising first and then reduced, two HRV features (fuzzy and approximate entropy) are almost unchanged, and vLF power is rising. Conclusion: The WT has an important impact on HRV during bathing. The findings in the present work reveal an important physiological factor that affects the dynamic changes of HRV and contribute to better quantitative analyses of HRV in future research works.

Effect of voluntary breathing exercises on stable coronary artery disease in heart rate variability and rate-pressure product: a study protocol for a single-blind, prospective, randomized controlled trial

Background

At present, China has more than 11 million patients with stable coronary heart disease and this is becoming a major public health problem. The pathological changes of coronary heart disease can lead to dysfunction of the cardiac autonomic nervous system, which increases the risk of complications such as malignant arrhythmia (ventricular flutter, ventricular fibrillation, etc.), heart rate, systolic blood pressure, and rate-pressure product (RPP), which is highly correlated with myocardial oxygen consumption and indirectly reflects myocardial blood supply and oxygen consumption. Although the guidelines recommend that such patients take drugs to reduce heart rate and myocardial oxygen consumption, the clinical control of heart rate is still not ideal. Thus, in this trial, we will use voluntary breathing exercises as the strategy of exercise rehabilitation for patients with stable coronary artery disease (SCAD), in order to increase the vagus nerve activity and/or reduce the sympathetic nervous activity, help maintain or rebuild the balance of plant nerve system, improve the time-domain index of heart rate variability, reduce the burden on the heart, and relieve patients’ anxiety and other negative emotions.

Methods

This is a 6-month single-blind, randomized controlled clinical trial that will be conducted in the First Affiliated Hospital of Soochow University. A total of 140 patients who fill out the Informed Consent Form are registered and randomized 1:1 into the Voluntary Breathing Exercises (VBE)-based clinical trial monitoring group (n = 70) or the Routine follow-up group (n = 70). The VBE-based clinical trial monitoring group is given VBE training on the basis of conventional treatment and health education, while the control group received conventional health education and follow-up. The primary outcomes will be measured heart rate variability and RPP. Secondary outcomes will include changes in Self-rating Anxiety Scale, total cholesterol, triglyceride, high-density lipoprotein, low-density lipoprotein, weight, and body mass index.

Discussion

This trial will carry out scientific respiratory exercise for patients with SCAD, which belongs to the category of active secondary prevention for patients, and changes from remedial to pre-protective. VBE is easy to operate and is not limited by time and place. It is important and meaningful to carry out VBE for patients with SCAD. This study will provide considerable evidence for further large-scale trials and alternative strategies for the rehabilitation nursing of patients with SCAD.

Trial registration

Chinese Clinical Trials Registry, 1900024043. Registered on 23 June 2019.

Mechanisms supporting potential use of bone marrow-derived mesenchymal stem cells in psychocardiology

Despite great efforts made in recent years, globally cardiovascular disease (CVD) remains the most common and devastating disease. Pharmacological, interventional and surgical treatments have proved to be only partly satisfactory for the majority of patients. A major underlying cause of poor prognosis is a high comorbidity rate between CVD and mental illness, which calls for the approaches of psychocardiology. As psychiatric disorders and CVD can influence each other bidirectionally, it is necessary to develop novel therapies targeting both systems simultaneously. Therefore, innovative stem cell (SC) therapy has become the most promising treatment strategy in psychocardiology. Bone marrow-derived mesenchymal stem/stromal cells (BM-MSCs), among all different types of SCs, have drawn the most attention due to unique advantages in terms of ethical considerations, low immunogenicity and simplicity of preparation. In this review, we survey recent publications and clinical trials to summarize the knowledge and progress gained so far. Moreover, we discuss the feasibility of the clinical application of BM-MSCs in the area of psychocardiology.