Dataset Information

Imbalance Model of Heart Rate Variability and Pulse Wave Velocity in Psychotic and Nonpsychotic Disorders.

ABSTRACT:

Objectives

Patients with psychiatric disorders have an increased risk of cardiovascular pathologies. A bidirectional feedback model between the brain and heart exists widely in both psychotic and nonpsychotic disorders. The aim of this study was to compare heart rate variability (HRV) and pulse wave velocity (PWV) functions between patients with psychotic and nonpsychotic disorders and to investigate whether subgroups defined by HRV and PWV features improve the transdiagnostic psychopathology of psychiatric classification.

Methods

In total, 3448 consecutive patients who visited psychiatric or psychological health services with psychotic (N = 1839) and nonpsychotic disorders (N = 1609) and were drug-free for at least 2 weeks were selected. HRV and PWV indicators were measured via finger photoplethysmography during a 5-minute period of rest. Canonical variates were generated through HRV and PWV indicators by canonical correlation analysis (CCA).

Results

All HRV indicators but none of the PWV indicators were significantly reduced in the psychotic group relative to those in the nonpsychotic group. After adjusting for age, gender, and body mass index, many indices of HRV were significantly reduced in the psychotic group compared with those in the nonpsychotic group. CCA analysis revealed 2 subgroups defined by distinct and relatively homogeneous patterns along HRV and PWV dimensions and comprising 19.0% (subgroup 1, n = 655) and 80.9% (subgroup 2, n = 2781) of the sample, each with distinctive features of HRV and PWV functions.

Conclusions

HRV functions are significantly impaired among psychiatric patients, especially in those with psychosis. Our results highlight important subgroups of psychiatric patients that have distinct features of HRV and PWV which transcend current diagnostic boundaries.

SUBMITTER: Zhang TH

PROVIDER: S-EPMC8781329 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Imbalance Model of Heart Rate Variability and Pulse Wave Velocity in Psychotic and Nonpsychotic Disorders.

Zhang Tian Hong TH Tang Xiao Chen XC Xu Li Hua LH Wei Yan Yan YY Hu Ye Gang YG Cui Hui Ru HR Tang Ying Ying YY Chen Tao T Li Chun Bo CB Zhou Lin Lin LL Wang Ji Jun JJ

Schizophrenia bulletin 20220101 1

<h4>Objectives</h4>Patients with psychiatric disorders have an increased risk of cardiovascular pathologies. A bidirectional feedback model between the brain and heart exists widely in both psychotic and nonpsychotic disorders. The aim of this study was to compare heart rate variability (HRV) and pulse wave velocity (PWV) functions between patients with psychotic and nonpsychotic disorders and to investigate whether subgroups defined by HRV and PWV features improve the transdiagnostic psychopath ...[more]

PMID: 34313787

Similar Datasets

Project description:Background: Orthostatic hypotension (OH) is a common disease of the elderly. It is generally believed that the pathogenesis of OH is related to the impairment of autonomic nerve function and the decreased vascular capacity regulation. This study aims to explore the relationship between OH and heart rate variability (HRV) parameters, which reflects autonomic nerve function; ankle-brachial pressure index (ABI), which reflects the degree of vascular stenosis; pulse wave velocity (PWV) index, which reflects vascular stiffness; and frailty index (FI), which reflects the overall health status of the elderly. Methods: From January to September 2018, 24-h HOLTER monitoring, PWV, and ABI were performed in 108 elderly patients with OH and 64 elderly patients who underwent physical examination in our hospital. Analysis software was used to record the subject's standard deviation of the cardiac cycle (SDNN), the standard deviation of the 5-min average cardiac cycle (SDANN), the square root of the average square sum of consecutive n-interval differences (rMSSD), the percentage of the number of adjacent cardiac interval differences >50 ms (pNN50), low frequency (LF), high frequency (HF), very low frequency (VLF), and low frequency/high frequency ratio (LF/HF). Then, FI was evaluated qualitatively and quantitatively in the form of a scale. Results: There was no statistical difference between the two groups on the basis of age, sex, body mass index (BMI), low-density lipoprotein (LDL), resting heart rate, blood pressure, fasting blood glucose, long-term medication, etc. There were significant differences in PWV, SDNN, LF, VLF, and LF/HF between the two groups (P < 0.05). The risk factor of OH in the qualitative (P = 0.04) and quantitative (P = 0.007) index FI was higher in the OH group than in the control group. The risk factors of OH were PWV, SDNN, VLF, LF/HF, and FI, where FI was positively correlated and LF/HF was negatively correlated. Conclusions: The pathogenesis of OH is related to vascular stiffness, imbalance of autonomic nerve regulation, and its comprehensive health status in the elderly. However, arteriosclerosis has not been confirmed as an independent risk factor. Clinical Trial Registration: Retrospectively registered, http://www.chictr.org.cn.

Project description:Introduction: Heart Rate Variability (HRV) and Pulse Rate Variability (PRV), are non-invasive techniques for monitoring changes in the cardiac cycle. Both techniques have been used for assessing the autonomic activity. Although highly correlated in healthy subjects, differences in HRV and PRV have been observed under various physiological conditions. The reasons for their disparities in assessing the degree of autonomic activity remains unknown. Methods: To investigate the differences between HRV and PRV, a whole-body cold exposure (CE) study was conducted on 20 healthy volunteers (11 male and 9 female, 30.3 ± 10.4 years old), where PRV indices were measured from red photoplethysmography signals acquired from central (ear canal, ear lobe) and peripheral sites (finger and toe), and HRV indices from the ECG signal. PRV and HRV indices were used to assess the effects of CE upon the autonomic control in peripheral and core vasculature, and on the relationship between HRV and PRV. The hypotheses underlying the experiment were that PRV from central vasculature is less affected by CE than PRV from the peripheries, and that PRV from peripheral and central vasculature differ with HRV to a different extent, especially during CE. Results: Most of the PRV time-domain and Poincaré plot indices increased during cold exposure. Frequency-domain parameters also showed differences except for relative-power frequency-domain parameters, which remained unchanged. HRV-derived parameters showed a similar behavior but were less affected than PRV. When PRV and HRV parameters were compared, time-domain, absolute-power frequency-domain, and non-linear indices showed differences among stages from most of the locations. Bland-Altman analysis showed that the relationship between HRV and PRV was affected by CE, and that it recovered faster in the core vasculature after CE. Conclusion: PRV responds to cold exposure differently to HRV, especially in peripheral sites such as the finger and the toe, and may have different information not available in HRV due to its non-localized nature. Hence, multi-site PRV shows promise for assessing the autonomic activity on different body locations and under different circumstances, which could allow for further understanding of the localized responses of the autonomic nervous system.

Dataset Information

Imbalance Model of Heart Rate Variability and Pulse Wave Velocity in Psychotic and Nonpsychotic Disorders.

Objectives

Methods

Results

Conclusions

Publications

Imbalance Model of Heart Rate Variability and Pulse Wave Velocity in Psychotic and Nonpsychotic Disorders.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets