Background: Cardiovascular diseases (CVD) are the leading causes of morbidity and mortality. Heart rate variability (HRV) represents the modulatory capacity of the autonomous nervous system and influences mortality. By surveying this meta-analysis, we investigated the impact of physical activity on HRV. Methods: Databases, online journal libraries and clinical trial registries were searched for publications of randomized controlled and non-randomized controlled trials concerning adults with coronary artery disease (CAD)/ischemic heart disease (IHD), congestive heart failure (CHF), peripheral arterial disease (PAD) or after acute coronary syndrome (ACS) joining an intervention group with physical activity or a control group with usual care or no intervention. Extracted time-domain and frequency-domain parameter of HRV were analyzed in a meta-analysis using a random effect model. Subgroup analyses concerning intervention type, study design and type of heart disease and sensitivity analysis were performed. Results: Significant results were obtained for RR-Interval (p = 0.05) and standard deviation of Normal-to-Normal intervals (SDNN) (p = 0.01) for short-term assessment and for the ratio of low-frequency power (LF) to high-frequency power (HF) (p = 0.05) for 24-hour assessment. Subgroup analyses also resulted significant: root-mean-square difference of successive normal R-R intervals (RMSSD) (p = 0.01), SDNN (p = 0.02) and HF (p < 0.01) concerning CHF. Conclusion: We were able to demonstrate the positive impact of physical activity on HRV, especially in patients with CHF. Cardiac rehabilitation exercise programs need to be individualized to identify the most beneficial method of training for improving the prognosis of patients with CVD.

Stress is recognized as a significant trigger and exacerbator of various medical conditions, particularly in the field of cardiovascular disease (CVD). Given that heart rate variability (HRV) offers insight into the functioning of the autonomic nervous system and has been identified as a predictive factor for increased cardiovascular mortality, exploring the correlation between stress and HRV is pertinent. We systematically reviewed trials where researchers investigated the effects of stress-reducing interventions on biomarkers and time-domain/frequency-domain parameters of HRV in CVD. Eligible studies underwent meta-analysis utilizing a random-effects model. The meta-analysis showed overall beneficial effects of stress-reducing interventions on HRV for the standard deviation of Normal-to-Normal intervals (SDNN) in short-term and 24 h assessments, as well as for the low-frequency power (LF) in short-term assessment. Overall effect sizes were notably high and showed significant p-values (short-term SDNN: MD = 6.43, p = 0.01; 24 h SDNN: MD = 10.92, p = 0.004; short-term LF: MD = 160.11, p < 0.001). Our findings highlight the significant impact of stress-reducing interventions in modulating HRV by influencing short-term SDNN and LF parameters, as well as the 24 h assessment of SDNN. These results emphasize the importance of stress-reducing measures in lowering the risk of further progression in CVD and improving patient outcomes.

Background: Chronic stress is a critical factor influencing both physical and mental health. It can weaken the immune system, affect cardiovascular health, and lower quality of life, often leading to psychological disorders like anxiety and depression. Objective: This study aims to evaluate the effectiveness of eHealth stress management interventions on psychological health parameters, specifically anxiety, depression, stress, and quality of life in patients with cardiovascular disease (CVD). Methods: A comprehensive search was conducted across several databases, including the Cochrane Library, APA PsycInfo, Web of Science, PubMed, Embase, and clinical trial registers. Randomized controlled trials assessing the impact of eHealth stress management interventions, namely internet-based cognitive behavioral therapy (CBT), telephone-delivered CBT, internet-based stress management training, or telephone-delivered stress management training, on the specified psychological outcomes in patients with CVD were included. The control group comprised no intervention, a waitlist, (enhanced) usual care, or a web-based intervention not focusing on stress management. To evaluate potential bias, the Risk-of-Bias 2 tool was applied. A random-effects meta-analysis was performed using standard mean difference (SMD) as the effect size, with a sensitivity analysis using mean difference (MD). Results: A total of 6 randomized controlled studies were considered in the meta-analysis. In 5 studies internet-based CBT interventions were examined, while one study used an eHealth intervention based on a CBT approach. The control groups received either usual care, were placed on a waitlist, or participated in a web-based discussion forum. After the intervention period, which ranged from 8 weeks to 6 months, a significant reduction in depressive symptoms (SMD=−0.46, MD=−2.33; P<.001), as assessed by the Patient Health Questionnaire-9, was observed in the intervention group compared with the control group. Mental health–related quality of life, assessed by the subscale of the 12-Item Short-Form Health Survey, showed significant improvement (SMD=0.38, MD=3.89; P<.001) in the intervention group in comparison to the control group following the intervention period. Conclusions: The meta-analysis demonstrates that eHealth stress management interventions substantially improve psychological health parameters in patients with CVD. Given the significant positive impact, health care providers should consider integrating eHealth stress management programs into standard care for patients with CVD. These programs can be a valuable tool in mitigating the psychological burdens associated with chronic cardiovascular conditions, ultimately improving overall patient outcomes and quality of life.