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

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).

Automated Speech Analysis in Bipolar Disorder: The CALIBER Study Protocol and Preliminary Results.

: Bipolar disorder (BD) involves significant mood and energy shifts reflected in speech patterns. Detecting these patterns is crucial for diagnosis and monitoring, currently assessed subjectively. Advances in natural language processing offer opportunities to objectively analyze them.

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

Background: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients.

Sleep-wake variations of electrodermal activity in bipolar disorder.

Background: Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities.

Methods: We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h.

Electrodermal activity in bipolar disorder: Differences between mood episodes and clinical remission using a wearable device in a real-world clinical setting.

Background: Bipolar disorder (BD) lacks objective measures for illness activity and treatment response. Electrodermal activity (EDA) is a quantitative measure of autonomic function, which is altered in manic and depressive episodes. We aimed to explore differences in EDA (1) inter-individually: between patients with BD on acute mood episodes, euthymic states and healthy controls (HC), and (2) intra-individually: longitudinally within patients during acute mood episodes of BD and after clinical remission.

[Social determinants of the incidence of Covid-19 in Barcelona: a preliminary ecological study using public data.].

Objective: Social determinants and health inequalities have a huge impact on health of populations. It is important to study their role in the management of the Covid-19 epidemic, especially in cities, as certain variables like the number of tests and the access to health system cannot be assumed as equal. The aim of this work was to determine the relation of social determinants in the incidence of Covid-19 in the city of Barcelona.