Heart rate variability in patients with psychiatric disorders from adolescence to adulthood

Age-related variations in heart rate variability profiles among patients with schizophrenia and major depressive disorder

Patients with psychiatric disorders exhibit general autonomic dysregulation and elevated cardiovascular risks, which could be indexed by heart rate variability (HRV). However, HRV is susceptible to age and other patient-specific factors. This study aimed to investigate the HRV profile and age-related variations, as well as the potential influence of sex, BMI, and HR on HRV in psychiatric populations. There were 571 consecutive patients diagnosed with schizophrenia (SZ) (N = 282) or major depressive disorder (MDD) (N = 289) recruited and classified as adolescent (11-21 years) and adult (> 21 years) groups. HRV indices were measured with 3-minute resting ECG recordings. Compared to adolescent subjects, all time-domain and nonlinear HRV indices were notably reduced in adults, while frequency-domain HRV was comparable. Between SZ and MDD groups, only HTI differed significantly. Age and psychiatric disorders exhibited complex interaction effects on HRV. Stratified by age stage, MDD patients exhibited slightly higher HRV in adolescence but slightly lower HRV in adulthood. In logistic regression analysis, HTI and SD2 were significantly distinctive between adolescents and adults in MDD group, while pNN50 was distinctive in SZ group. Moreover, female subjects demonstrated lower time-domain HRV, LF/HF and SD2 than males. HR exhibited inverse relationship with three domain HRV. No significant effect of BMI was observed. In psychiatric populations, compared to adolescents, adults decreased in time-domain and nonlinear HRV, but not in frequency-domain HRV. Age and psychotic disorders exhibited complex interaction effects on HRV. Sex and HR also emerged as important influencing factors of HRV.

Advancements and Future Directions in Prevention Based on Evaluation for Individuals With Clinical High Risk of Psychosis: Insights From the SHARP Study

BACKGROUND AND HYPOTHESIS

This review examines the evolution and future prospects of prevention based on evaluation (PBE) for individuals at clinical high risk (CHR) of psychosis, drawing insights from the SHARP (Shanghai At Risk for Psychosis) study. It aims to assess the effectiveness of non-pharmacological interventions in preventing psychosis onset among CHR individuals.

STUDY DESIGN

The review provides an overview of the developmental history of the SHARP study and its contributions to understanding the needs of CHR individuals. It explores the limitations of traditional antipsychotic approaches and introduces PBE as a promising framework for intervention.

STUDY RESULTS

Three key interventions implemented by the SHARP team are discussed: nutritional supplementation based on niacin skin response blunting, precision transcranial magnetic stimulation targeting cognitive and brain functional abnormalities, and cognitive behavioral therapy for psychotic symptoms addressing symptomatology and impaired insight characteristics. Each intervention is evaluated within the context of PBE, emphasizing the potential for tailored approaches to CHR individuals.

CONCLUSIONS

The review highlights the strengths and clinical applications of the discussed interventions, underscoring their potential to revolutionize preventive care for CHR individuals. It also provides insights into future directions for PBE in CHR populations, including efforts to expand evaluation techniques and enhance precision in interventions.

Correlative relationship between body mass index and heart rate variability in psychiatric disorders

OBJECTIVE

Indicators of heart rate variability (HRV) have been used to assess the autonomic activity. However, the influence of obesity on HRV in these patients remains to be determined. This study aimed to examine how obesity (measured with the body mass index [BMI]) affects HRV and determine whether the effect varies among different psychiatric disorders. We recruited 3159 consecutive patients, including 1744 with schizophrenia, 966 with mood disorders, and 449 with anxiety disorders. Patients were divided into four groups based on BMI: underweight (< 18.5), normal weight (18.5-23.9), overweight (24-27.9), and obese (≥ 28). The cardiovascular status was assessed using several time- and frequency-based HRV indicators, measured via electrocardiogram signals recorded for 5 min. The mean BMI of the participants was 23.6 ± 4.0. The patients in the overweight and obese groups were 29.4% and 13.6% of the total, respectively. The HRV indicators were higher in underweight and normal-weight patients than in the overweight and obese ones. After stratification based on the psychiatric diagnosis, the patients with mood disorders showed lower HRV than those with schizophrenia or anxiety disorder in the normal-weight group. In contrast, in the overweight and obese groups the patients with mood disorders showed higher HRV than those with the other disorders. The HRV variables were significantly associated with BMI, and higher BMI was associated with higher heart rates and lower HRV. These results indicate that weight gain in psychiatric disorders is associated with an imbalance in autonomic nerve activity. However, the relationship between autonomic activity, weight gain, and psychiatric disorders warrants further investigation.

Cardiovascular variations in patients with major depressive disorder versus bipolar disorder

BACKGROUND

Differentiating depression in major depressive disorder and bipolar disorder is challenging in clinical practice. Therefore, reliable biomarkers are urgently needed to differentiate between these diseases. This study's main objective was to assess whether cardiac autonomic function can distinguish patients with unipolar depression (UD), bipolar depression (BD), and bipolar mania (BM).

METHODS

We recruited 791 patients with mood disorders, including 191 with UD, 286 with BD, and 314 with BM, who had been drug free for at least 2 weeks. Cardiovascular status was measured using heart rate variability (HRV) and pulse wave velocity (PWV) indicators via finger photoplethysmography during a 5-min rest period.

RESULTS

Patients with BD showed lower HRV but higher heart rates than those with UD and BM. The PWV indicators were lower in the UD group than in the bipolar disorder group. The covariates of age, sex, and body mass index affected the cardiovascular characteristics. After adjusting for covariates, the HRV and PWV variations among the three groups remained significant. Comparisons between the UD and BD groups showed that the variable with the largest effect size was the frequency-domain indices of HRV, very low and high frequency, followed by heart rate. The area under the receiver operating characteristic curve (AUC) for each cardiovascular variable ranged from 0.661 to 0.714. The High-frequency index reached the highest AUC.

LIMITATIONS

Cross-sectional design and the magnitude of heterogeneity across participants with mood disorders limited our findings.

CONCLUSION

Patients with BD, but not BM, had a greater extent of cardiac imbalance than those with UD. Thus, HRV may serve as a psychophysiological biomarker for the differential diagnosis of UD and BD.