Ortiz Abigail, Halabi Ramzi, Alda Martin, DeShaw Alexandra, Husain Muhammad I, Nunes Abraham, O'Donovan Claire, Patterson Rachel, Mulsant Benoit H, Hintze Arend
Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
Campbell Family Research Institute, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.
Int J Bipolar Disord. 2025 Apr 2;13(1):13. doi: 10.1186/s40345-025-00379-6.
Anticipating clinical transitions in bipolar disorder (BD) is essential for the development of clinically actionable predictions. Our aim was to determine what is the earliest indicator of the onset of depressive symptoms in BD. We hypothesized that changes in activity would be the earliest indicator of future depressive symptoms. The study was a prospective, observational, contactless study. Participants were 127 outpatients with a primary diagnosis of BD, followed up for 12.6 (5.7) [(mean (SD)] months. They wore a smart ring continuously, which monitored their daily activity and sleep parameters. Participants were also asked to complete weekly self-ratings using the Patient Health Questionnaire (PHQ-9) and Altman Self-Rating Mania Scale (ASRS) scales. Primary outcome measures were depressive symptom onset detection metrics (i.e., accuracy, sensitivity, and specificity); and detection delay (in days), compared between self-rating scales and wearable data. Depressive symptoms were labeled as two or more consecutive weeks of total PHQ-9 > 10, and data-driven symptom onsets were detected using time-frequency spectral derivative spike detection (TF-SD). Our results showed that day-to-day variability in the number of steps anticipated the onset of depressive symptoms 7.0 (9.0) (median (IQR)) days before they occurred, significantly earlier than the early prediction window provided by deep sleep duration (median (IQR), 4.0 (5.0) days; p <.05). Taken together, our results demonstrate that changes in activity were the earliest indicator of depressive symptoms in participants with BD. Transition to dynamic representations of behavioral phenomena in psychiatry may facilitate episode forecasting and individualized preventive interventions.
预测双相情感障碍（BD）的临床转变对于制定具有临床可操作性的预测至关重要。我们的目的是确定BD中抑郁症状发作的最早指标是什么。我们假设活动变化将是未来抑郁症状的最早指标。该研究是一项前瞻性、观察性、非接触式研究。参与者为127名初步诊断为BD的门诊患者，随访12.6（5.7）[（均值（标准差）]个月。他们持续佩戴智能手环，该手环监测他们的日常活动和睡眠参数。参与者还被要求使用患者健康问卷（PHQ-9）和奥特曼自我评定躁狂量表（ASRS）每周进行自我评定。主要结局指标为抑郁症状发作检测指标（即准确性、敏感性和特异性）；以及自我评定量表和可穿戴数据之间的检测延迟（以天为单位）。抑郁症状被定义为连续两周以上总PHQ-9评分>10，并使用时频频谱导数峰值检测（TF-SD）检测数据驱动的症状发作。我们的结果表明，每日步数的变化比抑郁症状发作提前7.0（9.0）（中位数（四分位距））天预测到抑郁症状的发作，显著早于深度睡眠时间提供的早期预测窗口（中位数（四分位距），4.0（5.0）天；p<0.05）。综上所述，我们的结果表明，活动变化是BD参与者抑郁症状的最早指标。向精神病学中行为现象的动态表征转变可能有助于发作预测和个体化预防干预。
