A Bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder

Npj mental health research Pub Date : 2024-10-03 DOI:10.1038/s44184-024-00090-x

Filippo Corponi, Bryan M. Li, Gerard Anmella, Clàudia Valenzuela-Pascual, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antonio Benabarre, Marina Garriga, Eduard Vieta, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari

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Abstract

Bipolar disorder (BD) involves autonomic nervous system dysfunction, detectable through heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute mania or depression episodes are poorly understood. Using a Bayesian approach, we developed a probabilistic model of HRV changes in BD, measured by the natural logarithm of the Root Mean Square of Successive RR interval Differences (lnRMSSD). Patients were assessed three to four times from episode onset to euthymia. Unlike previous studies, which used only two assessments, our model allowed for more accurate tracking of changes. Results showed strong evidence for a positive lnRMSSD change during symptom resolution (95.175% probability of positive direction), though the sample size limited the precision of this effect (95% Highest Density Interval [−0.0366, 0.4706], with a Region of Practical Equivalence: [-0.05; 0.05]). Episode polarity did not significantly influence lnRMSSD changes.

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对双相情感障碍急性发作期心率变异性变化的贝叶斯分析

双相情感障碍（BD）涉及自律神经系统功能紊乱，可通过心率变异性（HRV）检测到。心率变异是一种很有前景的生物标志物，但人们对其在急性躁狂症或抑郁症发作期间的动态变化知之甚少。利用贝叶斯方法，我们建立了一个关于 BD 中心率变异性变化的概率模型，该模型以连续 RR 间期差的均方根自然对数（lnRMSSD）来测量。患者从发病到痊愈期间要接受三到四次评估。与之前仅使用两次评估的研究不同，我们的模型可以更准确地跟踪变化。结果表明，在症状缓解期间，lnRMSSD 发生正向变化的证据确凿（正向概率为 95.175%），尽管样本量限制了这一效应的精确度（95% 最高密度区间 [-0.0366, 0.4706]，实际等效区域：[-0.05; 0.05]).情节极性对 lnRMSSD 的变化影响不大。

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Npj mental health research

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