使用新型可穿戴设备（TIMEBASE）识别双相情感障碍中疾病活动和治疗反应的数字生物标志物：一项实用观察性临床研究的方案
Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study.
作者信息
Anmella Gerard, Corponi Filippo, Li Bryan M, Mas Ariadna, Garriga Marina, Sanabra Miriam, Pacchiarotti Isabella, Valentí Marc, Grande Iria, Benabarre Antoni, Giménez-Palomo Anna, Agasi Isabel, Bastidas Anna, Cavero Myriam, Bioque Miquel, García-Rizo Clemente, Madero Santiago, Arbelo Néstor, Murru Andrea, Amoretti Silvia, Martínez-Aran Anabel, Ruiz Victoria, Rivas Yudit, Fico Giovanna, De Prisco Michele, Oliva Vincenzo, Solanes Aleix, Radua Joaquim, Samalin Ludovic, Young Allan H, Vergari Antonio, Vieta Eduard, Hidalgo-Mazzei Diego
机构信息
Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain; Department of Psychiatry and Psychology, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Biomedical Research Networking Centre Consortium on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Department of Medicine, School of Medicine and Health Sciences, University of Barcelona, Spain; and Institute of Neurosciences (UBNeuro), University of Barcelona, Spain.
School of Informatics, University of Edinburgh, UK.
出版信息
BJPsych Open. 2024 Aug 1;10(5):e137. doi: 10.1192/bjo.2024.716.
BACKGROUND
Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions.
AIMS
The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder.
METHOD
We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania ( = 12), depression ( = 12 with bipolar disorder and = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features ( = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients.
RESULTS
Recruitment is ongoing.
CONCLUSIONS
This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.
背景
双相情感障碍极为常见，由躁狂和抑郁的双相复发性情绪发作组成，这会导致情绪、睡眠和活动改变及其生理表现。
目的
使用新型可穿戴设备识别双相情感障碍疾病活动和治疗反应的数字生物标志物（TIMEBASE）项目旨在识别双相情感障碍疾病活动和治疗反应的数字生物标志物。
方法
我们设计了一项纵向观察性研究，纳入84名个体。A组包括躁狂急性发作患者（n = 12）、抑郁症患者（双相情感障碍患者12例，重度抑郁症（MDD）患者12例）以及具有混合特征的双相情感障碍患者（n = 12）。将使用研究级可穿戴设备（Empatica E4）在48小时内连续四个时间点（急性发作期、反应期、缓解期和发作恢复期）记录生理数据。B组包括12例心境正常的双相情感障碍患者和12例MDD患者，C组包括12名健康对照者，将对其进行横断面记录。将使用标准化心理测量量表评估精神病理症状、疾病严重程度、功能和身体活动。生理数据将包括加速度、温度、血容量脉搏、心率和皮肤电活动。将开发机器学习模型，将生理数据与疾病活动和治疗反应联系起来。将在未见过的患者数据中测试泛化性能。
结果
招募工作正在进行中。
结论
该项目应有助于理解情感障碍的病理生理学。双相情感障碍疾病活动和治疗反应的潜在数字生物标志物可在现实临床环境中用于临床监测和前驱症状的识别。这将有助于早期干预和预防情感复发，以及治疗的个性化。
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