European Journal of Cardiovascular Medicine

Heart rate variability (HRV), defined as the fluctuation in the time intervals between consecutive heartbeats (R–R intervals), serves as a non-invasive marker of autonomic nervous system (ANS) activity. Alterations in HRV have been linked to a variety of medical conditions such as diabetic neuropathy, sepsis, myocardial infarction, and are increasingly recognized in the context of psychiatric illnesses due to the strong association between autonomic dysfunction and mental health disorders [1,2,3].

Among psychiatric disorders, bipolar disorder (BD) is of particular interest due to its well-documented association with increased cardiovascular morbidity and mortality [4,5]. Given that HRV reflects the balance between sympathetic and parasympathetic branches of the ANS, it offers a valuable window into the physiological dysregulation that often accompanies BD. [6-8] Understanding HRV patterns in this population may help elucidate underlying mechanisms of disease, and potentially identify physiological biomarkers for disease monitoring or therapeutic targeting.

Previous research has suggested that psychiatric conditions, including depression and schizophrenia, are frequently accompanied by autonomic imbalance, reflected in reduced HRV [2,3]. However, studies specifically examining HRV in individuals with bipolar disorder, particularly in drug-naïve patients, remain limited. Medications commonly used in psychiatric treatment can significantly influence autonomic function, and thus, studying non-medicated individuals is critical to avoid pharmacological confounders.

In this context, the present study aims to evaluate autonomic function in non-medicated patients with bipolar disorder through comprehensive HRV analysis. By assessing HRV parameters across time-domain, frequency-domain, and non-linear measures, and comparing them with those of healthy controls, we seek to deepen our understanding of autonomic dysregulation in BD.

Study Design and Setting

This study was a cross-sectional observational study conducted over a period of 18 months in the Department of Physiology in collaboration with Department of Psychiatry at Indira Gandhi Institute of Medical Sciences (IGIMS), Patna. The primary objective was to assess heart rate variability (HRV) as a measure of autonomic nervous system function in non-medicated patients with bipolar disorder and to compare the findings with healthy control subjects.

Study Population

A total of 160 participants were enrolled in the study, including 60 drug-naïve patients diagnosed with bipolar disorder and 100 age- and sex-matched healthy individuals from the community who served as the control group. All participants were within the age range of 18 to 60 years.

Inclusion Criteria

The patient group included individuals diagnosed with bipolar disorder according to DSM-5 criteria who attended the Psychiatry Outpatient Department of IGIMS, Patna. Only drug-naïve patients, who had not taken any psychotropic medication for at least two weeks prior to the study, were included. Healthy controls had no history of psychiatric, cardiovascular, or neurological illness and were matched with patients for age and sex.

Exclusion Criteria

Participants were excluded if they had any of the following: pregnancy, diabetes mellitus, hypertension, cancer, neuropathy, cardiac arrhythmia, or any other cardiovascular disease. Individuals with a history of schizophrenia, schizotypal or delusional disorders were also excluded. Additionally, participants who were smokers, engaged in regular physical training exceeding 10 hours per week, or had used any medication that could affect autonomic nervous system function—including antipsychotics, antidepressants, anxiolytics, anticonvulsants, oral contraceptives, cerebral metabolic activators, or vasodilators—within two weeks prior to the study were excluded. Exclusions were confirmed through questionnaire screening, clinical examination, and medical record review.

Clinical Assessment Tools

All participants underwent standardized clinical assessment using the Young Mania Rating Scale (YMRS), Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and Clinical Global Impression – Severity (CGI-S) scale.

HRV Measurement Protocol

Heart rate variability was recorded using the AD Instruments system (Australia), a validated tool for physiological data acquisition. Participants were instructed to avoid caffeine, alcohol, and vigorous physical activity for at least 12 hours prior to the recording. HRV was recorded while participants were in a resting, supine position in a quiet environment to minimize external interference. Electrocardiogram (ECG) signals were collected for a duration of five minutes, and R–R intervals were extracted for HRV analysis.

HRV Analysis

Heart rate variability was analyzed through time-domain, frequency-domain, and non-linear methods based on the guidelines of the Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology.

Time-domain parameters included standard deviation of NN intervals (SDNN), root mean square of successive differences (RMSSD), NN50, and pNN50. Frequency-domain parameters included low frequency (LF), high frequency (HF), and LF/HF ratio. Non-linear methods involved Poincaré plot analysis and approximate entropy to assess variability and complexity of heart rate signals.

Statistical Analysis

All data were presented as mean ± standard deviation (SD). Comparisons between the bipolar disorder group and control group were made using two-tailed Student’s t-test. A p-value of less than 0.05 was considered statistically significant. Additional statistical methods, such as analysis of variance and correlation analysis, were employed as required by the nature of the data. Data analysis was carried out using standard statistical software.

The following tables present the results of the heart rate variability (HRV) analysis conducted on 60 non-medicated patients with bipolar disorder (BD) and 100 age- and sex-matched healthy controls. The analysis encompasses time-domain, frequency-domain, and non-linear HRV parameters, as well as clinical assessment scores and their correlations with HRV measures.

Table 1 presents the demographic and clinical characteristics of the study participants. No statistically significant differences were observed between the bipolar disorder (BD) group and the healthy controls in terms of age, sex distribution, or body mass index (BMI), confirming that the groups were well matched demographically (p > 0.05 for all). However, clinical rating scores differed significantly between groups. Patients with bipolar disorder had markedly elevated scores on the Young Mania Rating Scale (YMRS), Hamilton Depression Rating Scale (HAM-D), Hamilton Anxiety Rating Scale (HAM-A), and Clinical Global Impression – Severity (CGI-S) scale compared to healthy controls, with all differences reaching high statistical significance (p < 0.001). These findings confirmed the clinical symptomatology in the BD group and validated the absence of psychiatric symptoms in controls.

Table 1: Demographic and Clinical Characteristics

*Statistically significant (p < 0.05).

Table 2 illustrates the time-domain parameters of HRV. The bipolar disorder group demonstrated significantly lower HRV across all measured time-domain indices compared to healthy controls. Specifically, SDNN, RMSSD, NN50 count, and pNN50 percentage were all significantly reduced in BD patients (p < 0.001 for all), indicating diminished autonomic flexibility and reduced parasympathetic activity. These findings suggest a clear autonomic imbalance in individuals with bipolar disorder, even in the absence of medication.

Table 2: Time-Domain HRV Parameters

*Statistically significant (p < 0.05).

Table 3 summarizes the frequency-domain HRV parameters. Consistent with the time-domain analysis, bipolar patients exhibited significantly lower values for both LF and HF power compared to controls (p < 0.001). Notably, the LF/HF ratio was significantly elevated in the BD group (1.72 ± 0.41 vs. 1.31 ± 0.28; p < 0.001), reflecting a shift toward sympathetic dominance and reduced vagal tone. This heightened sympathovagal imbalance may underlie the increased cardiovascular risk observed in bipolar populations.

Table 3: Frequency-Domain HRV Parameters

*Statistically significant (p < 0.05).

Table 4 details the non-linear HRV parameters. The bipolar disorder group showed significantly lower values for SD1 and SD2, as well as for approximate entropy, compared to healthy controls (p < 0.001 for all). Lower SD1 and SD2 suggest decreased short- and long-term HRV, while reduced approximate entropy indicates less complexity and more regularity in heart rate dynamics. Together, these findings support the presence of significant autonomic dysregulation and reduced physiological adaptability in individuals with BD.

Table 4: Non-Linear HRV Parameters

*Statistically significant (p < 0.05).

Table 5 examines the correlation between HRV parameters and clinical symptom scores in bipolar disorder patients. There were significant negative correlations between HRV measures such as SDNN, RMSSD, HF power, and approximate entropy with YMRS, HAM-D, HAM-A, and CGI-S scores (p < 0.05 for all), indicating that higher severity of mood symptoms was associated with lower autonomic function. Conversely, the LF/HF ratio showed a significant positive correlation with all clinical scores, suggesting that increased sympathetic dominance was linked to greater clinical symptom burden. These findings imply a strong inverse relationship between autonomic flexibility and psychiatric symptom severity in BD patients.

Table 5: Correlation Between HRV Parameters and Clinical Scores in BD Patients

*Statistically significant correlation (p < 0.05).

Table 6 presents a subgroup analysis comparing HRV parameters between patients experiencing manic versus depressive episodes. Although most HRV parameters did not differ significantly between the two subgroups, the LF/HF ratio was significantly higher in manic patients compared to those in a depressive episode (p = 0.024), suggesting greater sympathetic dominance during manic states. Other parameters such as SDNN, RMSSD, HF power, and approximate entropy trended toward lower values in the manic group but did not reach statistical significance. This suggests that while autonomic dysfunction is evident across bipolar episodes, the manic phase may be characterized by slightly greater sympathetic activation.

Table 6: Subgroup Analysis by BD Episode Type

*Statistically significant (p < 0.05).

The present study aimed to evaluate autonomic nervous system functioning through heart rate variability (HRV) analysis in non-medicated patients with bipolar disorder (BD) and to compare these findings with healthy, age- and sex-matched control participants. The results consistently demonstrated significant reductions in HRV across time-domain, frequency-domain, and non-linear measures in the bipolar group, suggesting marked autonomic dysregulation. Importantly, these changes were observed in drug-naïve individuals, eliminating the confounding effects of psychotropic medications known to influence autonomic function.

Demographically, the bipolar and control groups were well matched in terms of age, sex, and BMI, ruling out these factors as potential contributors to differences in HRV. Clinically, BD patients had significantly higher scores across all psychiatric rating scales (YMRS, HAM-D, HAM-A, CGI-S), reflecting active mood symptomatology. These elevated scores validate the clinical status of the sample and provided a reliable basis for correlating symptom severity with physiological dysregulation.[8,9]

Time-domain HRV parameters such as SDNN, RMSSD, NN50, and pNN50 were significantly reduced in bipolar patients. These measures primarily reflect parasympathetic activity and overall autonomic flexibility. The observed reductions suggest that individuals with BD may experience a persistent state of autonomic inflexibility, likely contributing to both their emotional instability and increased risk for cardiovascular morbidity. These findings are in line with prior literature suggesting a parasympathetic deficit or autonomic hypo-reactivity in psychiatric populations, particularly in mood and psychotic disorders.[10-12]

In the frequency-domain analysis, both LF and HF power were significantly lower in the BD group, with a notable increase in the LF/HF ratio. While LF power is often associated with both sympathetic and parasympathetic influences, HF power is a well-established marker of vagal (parasympathetic) tone. The increased LF/HF ratio observed in BD patients therefore reflects a sympathovagal imbalance characterized by heightened sympathetic dominance and reduced vagal control. This shift may underlie the physiological hyperarousal and emotional reactivity frequently observed in bipolar disorder. Additionally, the elevated LF/HF ratio aligns with evidence of increased cardiovascular risk in BD, as sympathovagal imbalance is a known predictor of adverse cardiac outcomes.[11-13]

Non-linear HRV measures, including SD1, SD2, and approximate entropy, were also significantly reduced in the bipolar group. These indices assess the complexity and adaptability of heart rate dynamics. Reduced non-linear variability suggests a more rigid and less adaptive autonomic state in individuals with BD, potentially rendering them more vulnerable to internal and external stressors. Decreased entropy, in particular, indicates a loss of dynamic complexity, often interpreted as reduced physiological resilience. These results support the hypothesis that autonomic rigidity may be a core physiological feature of bipolar disorder.

The correlation analysis further reinforced these findings. Negative correlations between HRV parameters (SDNN, RMSSD, HF power, and approximate entropy) and clinical symptom severity scores suggest that greater psychiatric symptom burden is associated with poorer autonomic regulation. Conversely, the positive correlation of LF/HF ratio with mood rating scales indicates that increased sympathetic dominance is linked to greater clinical severity. These relationships highlight the potential utility of HRV as a physiological marker for tracking symptom intensity in bipolar disorder. This aligns with existing research suggesting that HRV may serve not only as a diagnostic adjunct but also as a real-time biomarker for emotional and physiological regulation.[12-14]

The subgroup analysis between manic and depressive episodes revealed interesting patterns. Although most HRV parameters did not differ significantly between the two subtypes, the LF/HF ratio was significantly higher in the manic group, suggesting relatively greater sympathetic dominance during manic episodes. This aligns with the clinical presentation of mania, which often includes increased psychomotor activity, agitation, and heightened arousal—states commonly associated with elevated sympathetic tone. While differences in other parameters such as RMSSD and HF power trended toward significance, the lack of statistical difference may be due to the modest sample size and intra-group variability. Nevertheless, this analysis underscores the potential for autonomic profiling to distinguish between mood states within bipolar disorder.

Taken together, the findings of this study provide strong evidence for autonomic dysregulation in non-medicated individuals with bipolar disorder. The consistency of reduced HRV across multiple domains and its correlation with clinical symptomatology support the notion that impaired autonomic functioning is a core physiological component of the disorder, independent of medication effects. These findings have several important implications. First, they suggest that HRV could serve as a useful biomarker in both research and clinical practice for assessing physiological health and emotional regulation in BD. Second, the presence of autonomic dysfunction in drug-naïve patients highlights the need for early screening and possible preventive interventions for cardiovascular health in this population.

The study also emphasizes the relevance of psychophysiological assessment in psychiatric research. Interventions aimed at improving autonomic balance—such as biofeedback, mindfulness, exercise, and other non-pharmacological strategies—could potentially play a role in comprehensive treatment plans for bipolar disorder. Further longitudinal research is needed to determine whether HRV measures can predict treatment response, relapse risk, or transition between mood states.

Despite the strengths of this study, including its focus on drug-naïve patients and the use of comprehensive HRV analysis, certain limitations must be acknowledged. The cross-sectional design limits causal interpretations, and the sample size, though adequate for initial analysis, may have limited the power to detect subtler differences, particularly in the subgroup comparisons. Additionally, while efforts were made to control for lifestyle and physiological variables, residual confounding cannot be entirely ruled out.

T In conclusion, this study provides compelling evidence of significant autonomic nervous system dysregulation in non-medicated patients with bipolar disorder, as reflected by consistently reduced heart rate variability across time-domain, frequency-domain, and non-linear parameters. These alterations, independent of medication influence, were strongly associated with the severity of mood symptoms, suggesting that autonomic imbalance may be an intrinsic physiological feature of bipolar disorder. The observed pattern of reduced parasympathetic activity and increased sympathetic dominance, particularly during manic episodes, highlights a potential link between emotional dysregulation and cardiovascular risk in this population. These findings underscore the clinical relevance of HRV as a non-invasive biomarker for assessing physiological health, monitoring symptom progression, and informing treatment strategies in bipolar disorder. Future longitudinal studies are warranted to explore the prognostic value of HRV in predicting mood state transitions, treatment outcomes, and long-term cardiovascular implications in this vulnerable group.

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