Identifying Digital Biomarkers in Bipolar Disorder
Author Information
Author(s): 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
Primary Institution: Digital Innovation Group, Bipolar and Depressive Disorders Unit, Institute of Neuroscience, Department of Psychiatry and Psychology, Hospital Clínic de Barcelona, Spain
Hypothesis
Physiological data captured through a wearable device will accurately reflect illness activity during acute affective episodes in bipolar disorder, differentiate between different acute affective episodes, and predict treatment response.
Conclusion
The study aims to identify digital biomarkers that could help in the clinical monitoring and early intervention of bipolar disorder.
Supporting Evidence
- Bipolar disorder affects approximately 1% of the world's population and is a leading source of disability.
- Current treatments for bipolar disorder often rely on trial and error, leading to poor responses in 30-55% of patients.
- Digital biomarkers could improve the management and prognosis of bipolar disorder by enabling personalized treatments.
Takeaway
This study is trying to find new ways to measure how people with bipolar disorder are feeling by using a special device that tracks their body signals.
Methodology
A longitudinal observational study with 84 individuals divided into three groups, using a wearable device to collect physiological data over 48 hours.
Potential Biases
Selection bias may occur, but efforts will be made to mitigate it through age- and gender-matched recruitment.
Limitations
The study has limitations inherent to observational studies and the novel method of capturing physiological data, including potential loss to follow-up and participant non-compliance with device usage.
Participant Demographics
Participants include individuals aged 18-75 with bipolar disorder, major depressive disorder, and healthy controls.
Digital Object Identifier (DOI)
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