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.
Abstract

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