ABSTRACT
Background: Mood disorders are commonly diagnosed and staged using clinical features that rely merely on subjective data. The concept of digital phenotyping is based on the idea that collecting real-time markers of human behavior allows us to determine the digital signature of a pathology. This strategy assumes that behaviors are quantifiable from data extracted and analyzed through digital sensors, wearable devices, or smartphones. That concept could bring a shift in the diagnosis of mood disorders, introducing for the first time additional examinations on psychiatric routine care. Objective: The main objective of this review was to propose a conceptual and critical review of the literature regarding the theoretical and technical principles of the digital phenotypes applied to mood disorders. Methods: We conducted a review of the literature by updating a previous article and querying the PubMed database between February 2017 and November 2021 on titles with relevant keywords regarding digital phenotyping, mood disorders and artificial intelligence. Results: Out of 884 articles included for evaluation, 45 articles were taken into account and classified by data source (multimodal, actigraphy, ECG, smartphone use, voice analysis, or body temperature). For depressive episodes, the main finding is a decrease in terms of functional and biological parameters [decrease in activities and walking, decrease in the number of calls and SMS messages, decrease in temperature and heart rate variability (HRV)], while the manic phase produces the reverse phenomenon (increase in activities, number of calls and HRV). Conclusion: The various studies presented support the potential interest in digital phenotyping to computerize the clinical characteristics of mood disorders.
ABSTRACT
Obsessive-compulsive disorder (OCD) is a widespread chronic neuropsychiatric disorder characterized by recurrent intrusive thoughts, images, or urges (obsessions) that typically cause anxiety or distress. Even when optimal treatment is provided, 10% of patients remain severely affected chronically. In some countries, deep brain stimulation (DBS) is an approved and effective therapy for patients suffering from treatment-resistant OCD. Hereafter, we report the case of a middle-aged man with a long history of treatment-resistant OCD spanning nearly a decade with Yale-Brown Obsessive Compulsive Scale (Y-BOCS) scores oscillating between 21 and 28. The patient underwent bilateral implantation of ventral striatum/ventral capsule DBS leads attached to a battery-operated implanted pulse generator. After a 3-month postimplantation period, the DBS protocol started. Three months after the onset of DBS treatment, the patient's Y-BOCS score had dropped to 3, and he became steadily asymptomatic. However, inadvertently, at this time, it was found out that the implanted pulse generator battery had discharged completely, interrupting brain stimulation. The medical team carried on with the original therapeutic and evaluation plan in the absence of active DBS current. After 12 additional months under off-DBS, the patient remained at a Y-BOCS score of 7 and asymptomatic. To our knowledge, this is the first report that provides an opportunity to discuss four different hypotheses of long-term recovery induced by DBS in a treatment-refractory OCD patient, notably: (1) A placebo effect; (2) Paradoxical improvements induced by micro-lesions generated by DBS probe implantation procedures; (3) Unexpected late spontaneous improvements; (4) Recovery driven by a combination of active DBS-induction, the effects of medication, and DBS-placebo effects.