Psychological Traits, Heart Rate Variability, and Risk of Coronary Heart Disease in Healthy Aging Women-The Women's Health Initiative

Association between instantaneous heart rate sequence during the awake period and cardiovascular events: a study based on Sleep Heart Health Study

BACKGROUND

Heart rate variability (HRV) has been reported to be associated with cardiovascular diseases (CVD), while few studies focused on the instantaneous heart rate (IHR). This study aimed to establish models to predict the occurrence of cardiovascular events based on the IHR sequence.

METHODS

A total of 2977 participants with useful electrocardiogram (ECG) data and free of CVD events at baseline from the Sleep Heart Health Study (SHHS) database were included in this retrospective cohort study. All IHR indicators were measured during the awake period before sleep. The logistic regression, random forest, and XGBoost methods were used to develop the predictive models. The model performance was quantified by calculating the area under the curve (AUC).

RESULTS

Of theses 2977 participants, 1460 (49.04%) participants had CVD events during the 15-year follow-up. Higher standard deviation of IHR (SDHR) (OR=0.906; 95% CI, 0.832-0.986), coefficient of variation of IHR (CVHR) (OR=0.910; 95% CI, 0.835-0.990), power in low frequency (LF) (OR=0.896; 95% CI, 0.822-0.975), power in high frequency (HF) (OR=0.872; 95% CI, 0.796-0.955), and total power (TP) (OR=0.887; 95% CI, 0.813-0.967) were associated with the lower risk of CVD events, while ratio of semi-minor axis and semi-major axis in Poincare plot (SDratio) (OR=1.105; 95% CI, 1.012-1.206) was related to the higher risk of CVD events. The AUCs of the logistic regression, random forest, and the XGBoost models were 0.734 (95% CI, 0.701-0.767), 0.794 (95% CI, 0.764-0.823) and 0.828 (95% CI, 0.801-0.855) in the testing set, respectively.

CONCLUSIONS

IHR sequences were important predictors of cardiovascular events. The IHR indicators should be paid more attention to in future clinical researches on CVD.

Effects of stress management interventions on heart rate variability in adults with cardiovascular disease: a systematic review and meta-analysis

Meta-analysis was used to investigate the potential benefits of stress management interventions (SMIs) on vagally-mediated heart rate variability (HRV) in adults with cardiovascular disease. Electronic bibliographic databases were searched through August 2022. Randomized controlled trials and quasi-experimental studies assessing effects of SMIs on HRV were included. Methodological quality was assessed with a standardized checklist. A pooled effect size was calculated for vagally-mediated HRV indices (standard deviation of normal-to-normal intervals, root mean square of the successive differences, and high frequency power) using random effects models. Fourteen studies (1202 participants, Mage: 59 ± 6.25 years; 25% ± 16% women; 61% ± 22% White) were included. Ten studies (11 effects) reported short-term HRV assessment; a small between-group difference emerged for vagally-mediated HRV (d+ = .27, 95% confidence interval [CI] 0.01-0.52, k = 11). Most interventions examined biofeedback; these studies yielded a small between-group difference on vagally-mediated HRV (d+ = 0.31, 95% CI 0.09-0.53, k = 7, Q [6] = 3.82, p = .70, I2 = 11%). This is the first systematic examination of the effect of SMIs on HRV in adults with CVD. Findings suggest a small effect of SMIs on vagally-mediated HRV, with biofeedback likely driving the effect. More research is required to fully understand whether this benefit on vagally-mediated HRV applies to other SMIs.

A New Target of Electroacupuncture Pretreatment Mediated Sympathetic Nervous to Improve MIRI: Glutamatergic Neurons in Fastigial Nucleus of the Cerebellum

Ischemic heart disease is a fatal cardiovascular disease that irreversibly impairs the function of the heart, followed by reperfusion leading to a further increase in infarct size. Clinically, we call it myocardial ischemia-reperfusion injury (MIRI). A growing number of clinical observations and experimental studies have found electroacupuncture (EA) to be effective in alleviating MIRI. This study attempts to investigate whether glutamatergic neurons in fastigial nucleus (FN) of the cerebellum are involved in EA pretreatment to alleviate MIRI via sympathetic nerves, and the potential mechanisms of EA pretreatment process. A MIRI model was established by ligating the coronary artery of the left anterior descending branch of the heart for 30 minutes, followed by 2 hours of reperfusion. Multichannel physiological recordings, electrocardiogram, cardiac ultrasound, chemical genetics, enzyme-linked immunosorbent assay and immunofluorescence staining methods were combined to demonstrate that EA pretreatment inhibited neuronal firing and c-Fos expression in FN of the cerebellum and reduced cardiac sympathetic firing. Meanwhile, EA pretreatment significantly reduced cardiac ejection fraction (EF), shortening fraction (SF), percentage infarct area, decreased myocardial norepinephrine (NE), creatine kinase isoenzyme MB (CK-MB) concentrations, and improved MIRI-induced myocardial tissue morphology. The results were similar to the inhibition of glutamatergic neurons in FN. However, the activation of glutamatergic neurons in FN diminished the aforementioned effects of EA pretreatment. This study revealed that glutamatergic neurons in FN of the cerebellum is involved in EA pretreatment mediated sympathetic nervous and may be a potential mediator for improving MIRI.

Associations between affective factors and high-frequency heart rate variability in primary care patients with depression

OBJECTIVE

Depression is a risk factor for cardiovascular disease (CVD), and subgroups of people with depression may be at particularly elevated CVD risk. Lower high-frequency heart rate variability (HF HRV), which reflects diminished parasympathetic activation, is a candidate mechanism underlying the depression-CVD relationship and predicts cardiovascular events. Few studies have examined whether certain depression subgroups - such as those with co-occurring affective factors - exhibit lower HF HRV. The present study sought to assess associations between co-occurring affective factors and HF HRV in people with depression.

METHODS

Utilizing baseline data from the 216 primary care patients with depression in the eIMPACT trial, we examined cross-sectional associations of depression's co-occurring affective factors (i.e., anxiety symptoms, hostility/anger, and trait positive affect) with HF HRV. HF HRV estimates were derived by spectral analysis from electrocardiographic data obtained during a supine rest period.

RESULTS

Individual regression models adjusted for demographics and depressive symptoms revealed that anxiety symptoms (standardized regression coefficient β = -0.24, p = .002) were negatively associated with HF HRV; however, hostility/anger (β = 0.02, p = .78) and trait positive affect (β = -0.05, p = .49) were not. In a model further adjusted for hypercholesterolemia, hypertension, diabetes, body mass index, current smoking, CVD prevention medication use, and antidepressant medication use, anxiety symptoms remained negatively associated with HF HRV (β = -0.19, p = .02).

CONCLUSION

Our findings suggest that, in adults with depression, those with comorbid anxiety symptoms have lower HF HRV than those without. Co-occurring anxiety may indicate a depression subgroup at elevated CVD risk on account of diminished parasympathetic activation.

Balance of Autonomic Nervous Activity, Exercise, and Sleep Status in Older Adults: A Review of the Literature

While older people are frequently known to experience sleep disturbances, there are also many older people who have a good quality of sleep. However, little is known about the balance of autonomic nervous activity, exercise habits, and sleep status in healthy older adults. This study reviews the literature regarding balance of the autonomic nervous activity, exercise, and sleep in healthy older adults. Relevant articles were searched from electronic databases using the combination of the following keywords: "Autonomic nervous activity", "sleep status", "sleep", "healthy older adults", "aging", "heart rate variability (HRV)" and "exercise". Articles were included if they met inclusion criteria: (1) Published in English, (2) Article types: research and review articles, (3) Main outcome was related to the autonomic nervous activity, lifestyle, sleep, and/or healthy aging, and (4) Fully accessed. From 877 articles that were identified, 16 articles were included for review. Results showed that the autonomic nervous activity changes with increasing age, particularly a constant decline in cardiac vagal modulation due to the significant decrease in the nocturnal parasympathetic activity. In addition, the autonomic nervous activity was also related to sleep status and lifestyle, particularly the capability to exercise. In preparing older people toward a healthy aging, maintaining good sleep quality and exercise is suggested.

Mental Health Monitoring Based on Multiperception Intelligent Wearable Devices

In order to improve the accuracy of the evaluation results of multiperception intelligent wearable devices, the mathematical statistical characteristics based on speech, behavior, environment, and physical signs are proposed; first, the PCA feature compression algorithm was used to reduce the dimension of these features, and the differences among different training samples were compared and analyzed; then, three weak classifiers are designed using the logistic regression algorithm, and finally, a strong classifier with higher prediction accuracy is designed according to the boosting decision fusion method and ensemble learning idea. The results showed that the accuracy of the logistic regression model trained with the feature data of voice PCA was 0.964, but the recall rate and crossover results were significantly reduced to 0.844 and 0.846, respectively. The accuracy, accuracy and recall of the decision fusion model based on the boosting method and integrated learning are 0.969, and the prediction accuracy of K-folds cross-validation is also as high as 0.956; the superposition fusion results of three weak classifiers achieve a better classification effect.

Mind-Body and Psychosocial Interventions May Similarly Affect Heart Rate Variability Patterns in Cancer Recovery: Implications for a Mechanism of Symptom Improvement

Background:

Advancements in early detection and treatment of cancer have led to increased survival rates and greater need to identify effective supportive care options for resolving symptoms of survivorship. Many non-pharmacological approaches to symptom management during and after cancer treatment involve emotional self-regulation as a central strategy for improving well-being. Identifying commonalities among these strategies’ mechanisms of action may facilitate understanding of what might be useful for optimizing intervention effects. Heart rate variability (HRV) parameters are indicative of improved autonomic nervous system (ANS) balance and resiliency and reduced emotional distress and are thus identified as a mechanism to discuss as a marker of potential for intervention efficacy and a target for optimization.

Methods:

HRV data from 2 studies, 1 examining a mind-body intervention and 1 examining a psychosocial intervention, are presented as a point of discussion about preliminary associations between the interventions, change in HRV, and emotional distress reduction.

Results:

HRV significantly decreased in sympathetic activity in response to a mind-body intervention (Qigong/Tai Chi), and increased vagal tone in response to a psychosocial (storytelling) intervention. In both, these changes in HRV parameters were associated with improved emotional states.

Conclusion:

Our preliminary data suggest that HRV may serve as an important marker of underlying changes that mediate emotional regulation; this observation deserves further investigation. If identified as a worthy target, focusing on interventions that improve HRV within the context of interventions for cancer patients may be important to key outcomes and clinical practice.

Positive psychological well‐being and cardiovascular disease: Exploring mechanistic and developmental pathways

Empirical research regarding the health benefits of positive psychological well‐being (e.g., positive emotions, life satisfaction, purpose in life, and optimism) has flourished in recent years, particularly with regard to cardiovascular disease. This paper reviews the state of evidence for well‐being's association with cardiovascular disease in both healthy individuals and those diagnosed with a disease. Prospective studies consistently indicate well‐being reduces cardiovascular events in healthy and, to a lesser extent, patient populations. Potential pathways that link well‐being with cardiovascular disease are discussed (including health behaviors, physiological processes, and stress buffering), although the existing evidence is mostly cross‐sectional which limits conclusions about directionality. Issues related to development across the lifespan are considered and childhood is identified as a crucial period for establishing healthy cardiovascular trajectories. Outstanding questions for future research are provided with recommendations to focus on well‐powered and prospective study designs with rigorous assessment of both well‐being and cardiovascular‐related outcomes.

Multiscale based nonlinear dynamics analysis of heart rate variability signals

Acceleration change index (ACI) is a fast and easy to understand heart rate variability (HRV) analysis approach used for assessing cardiac autonomic control of the nervous systems. The cardiac autonomic control of the nervous system is an example of highly integrated systems operating at multiple time scales. Traditional single scale based ACI did not take into account multiple time scales and has limited capability to classify normal and pathological subjects. In this study, a novel approach multiscale ACI (MACI) is proposed by incorporating multiple time scales for improving the classification ability of ACI. We evaluated the performance of MACI for classifying, normal sinus rhythm (NSR), congestive heart failure (CHF) and atrial fibrillation subjects. The findings reveal that MACI provided better classification between healthy and pathological subjects compared to ACI. We also compared MACI with other scale-based techniques such as multiscale entropy, multiscale permutation entropy (MPE), multiscale normalized corrected Shannon entropy (MNCSE) and multiscale permutation entropy (IMPE). The preliminary results show that MACI values are more stable and reliable than IMPE and MNCSE. The results show that MACI based features lead to higher classification accuracy.