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The usability of daytime and night-time heart rate dynamics as digital biomarkers of depression severity
S Siddi1, R Bailon2,3, I Giné-Vázquez1
1Parc Sanitari Sant Joan de Déu, Fundació Sant Joan de Déu, CIBERSAM, Universitat de Barcelona, Barcelona, Spain.
Insights
Heart rate (HR) changes during rest, particularly decreased daytime HR variation and increased nighttime resting HR, correlate with major depressive disorder (MDD) severity. These HR alterations may signal worsening depression.
Area of Science:
- Cardiology
- Psychiatry
- Digital Health
Background:
- Heart rate (HR) variations may indicate physiological markers of depression.
- Recurrent major depressive disorder (MDD) impacts physiological functions.
- Understanding HR patterns can offer insights into depression severity.
Purpose of the Study:
- To investigate the relationship between intra-individual heart rate (HR) variations and depression severity.
- To explore HR parameters as potential biomarkers for MDD.
- To analyze HR data collected remotely over two years.
Main Methods:
- Utilized data from 510 participants in the remote assessment of disease and relapse-MDD study.
- Collected HR data (all day, resting, activity) using Fitbit devices.
- Employed linear mixed models to analyze HR parameters against Patient Health Questionnaire-8 depression scores, controlling for covariates.
Main Results:
- Reduced HR variation during daytime rest was linked to increased depression severity.
- Higher mean HR during nighttime rest correlated with more severe depressive symptoms.
- Both univariate and multivariate analyses supported these findings.
Conclusions:
- Alterations in resting heart rate (HR) throughout the day and night are associated with depression severity.
- HR changes may serve as an early warning system for worsening depression.
- This could enable timely clinical intervention and treatment adjustments.
Background:
Alterations in heart rate (HR) may provide new information about physiological signatures of depression severity. This 2-year study in individuals with a history of recurrent major depressive disorder (MDD) explored the intra-individual variations in HR parameters and their relationship with depression severity.
Methods:
Data from 510 participants (Number of observations of the HR parameters = 6666) were collected from three centres in the Netherlands, Spain, and the UK, as a part of the remote assessment of disease and relapse-MDD study. We analysed the relationship between depression severity, assessed every 2 weeks with the Patient Health Questionnaire-8, with HR parameters in the week before the assessment, such as HR features during all day, resting periods during the day and at night, and activity periods during the day evaluated with a wrist-worn Fitbit device. Linear mixed models were used with random intercepts for participants and countries. Covariates included in the models were age, sex, BMI, smoking and alcohol consumption, antidepressant use and co-morbidities with other medical health conditions.
Results:
Decreases in HR variation during resting periods during the day were related with an increased severity of depression both in univariate and multivariate analyses. Mean HR during resting at night was higher in participants with more severe depressive symptoms.
Conclusions:
Our findings demonstrate that alterations in resting HR during all day and night are associated with depression severity. These findings may provide an early warning of worsening depression symptoms which could allow clinicians to take responsive treatment measures promptly.
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