BACKGROUND: We recently described an association between reduced heart rate variability (HRV) and illness burden in bipolar disorder (BD) using a novel Illness Burden Index (IBI). We aimed to further characterize this association by using spectral analyses to assess whether the IBI is also associated with autonomic imbalance in BD patients. METHODS: In this cross-sectional study, 53 participants with BD wore a device for 24 h to assess association between HRV spectral measures and the IBI or each of its components (age of onset, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, co-morbid psychiatric disorders, and family history). We ran both unadjusted models and models controlling for age, sex, years of education, marital status, BMI, pharmacotherapy, and baseline functional cardiovascular capacity. RESULTS: HRV low-frequency (LF) normalized values were almost twice as high as published in healthy controls. Higher IBI was associated with higher LF and lower High Frequency (HF) values, resulting in a higher LF/HF ratio, indicating an increased sympathetic tone. Four individual components of the IBI were similarly associated with measures of increased sympathetic tone: earlier age of onset, number of depressive episodes, co-morbid anxiety disorders, and family history of suicide. Adjusted and unadjusted models had similar results. LIMITATIONS: Our models used mean LF and HF and do not consider their dynamic variations over 24 h or phase of the illness. CONCLUSIONS: Burden of illness is associated with increased sympathetic tone in patients with BD, putting them at risk for arrythmias and sudden death.
BACKGROUND: Understanding the underlying architecture of mood regulation in bipolar disorder (BD) is important, as we are starting to conceptualize BD as a more complex disorder than one of recurring manic or depressive episodes. Nonlinear techniques are employed to understand and model the behavior of complex systems. Our aim was to assess the underlying nonlinear properties that account for mood and energy fluctuations in patients with BD; and to compare whether these processes were different in healthy controls (HC) and unaffected first-degree relatives (FDR). We used three different nonlinear techniques: Lyapunov exponent, detrended fluctuation analysis and fractal dimension to assess the underlying behavior of mood and energy fluctuations in all groups; and subsequently to assess whether these arise from different processes in each of these groups. RESULTS: There was a positive, short-term autocorrelation for both mood and energy series in all three groups. In the mood series, the largest Lyapunov exponent was found in HC (1.84), compared to BD (1.63) and FDR (1.71) groups [F (2, 87) = 8.42, p < 0.005]. A post-hoc Tukey test showed that Lyapunov exponent in HC was significantly higher than both the BD (p = 0.003) and FDR groups (p = 0.03). Similarly, in the energy series, the largest Lyapunov exponent was found in HC (1.85), compared to BD (1.76) and FDR (1.67) [F (2, 87) = 11.02; p < 0.005]. There were no significant differences between groups for the detrended fluctuation analysis or fractal dimension. CONCLUSIONS: The underlying nature of mood variability is in keeping with that of a chaotic system, which means that fluctuations are generated by deterministic nonlinear process(es) in HC, BD, and FDR. The value of this complex modeling lies in analyzing the nature of the processes involved in mood regulation. It also suggests that the window for episode prediction in BD will be inevitably short.
- Publikační typ
- časopisecké články MeSH
BACKGROUND: Bipolar disorder (BD) is associated with premature death and ischemic heart disease is the main cause of excess mortality. Heart rate variability (HRV) predicts mortality in patients with or without cardiovascular disease. While several studies have analyzed the association between HRV and BD, none has analyzed the association of HRV with illness burden in BD. METHODS: 53 participants with BD I and II used a wearable device to assess the association between HRV and factors characterizing illness burden, including illness duration, number and type of previous episode(s), duration of the most severe episode, history of suicide attempts or psychotic symptoms during episodes, and co-morbid psychiatric disorders. We ran unadjusted models and models controlling statistically for age, sex, pharmacotherapy, baseline functional cardiovascular capacity, BMI, years of education, and marital status. We also explored the association between HRV and an overall illness burden index (IBI) integrating all these factors using a weighted geometric mean. RESULTS: Adjusted and unadjusted models had similar results. Longer illness duration, higher number of depressive episodes, longer duration of most severe manic/hypomanic episode, co-morbid anxiety disorders, and family history of suicide were associated with reduced HRV, as was bipolar depression severity in the participants experiencing a depressive episode. Finally, a higher IBI score was associated with lower HRV. CONCLUSIONS: High illness burden is associated with reduced HRV in BD. While the IBI needs to be validated in a larger sample, it may provide an overall measure that captures illness burden in BD.
