Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder

Sponsor
National Taiwan University Hospital (Other)
Overall Status
Recruiting
CT.gov ID
NCT05828056
Collaborator
(none)
100
1
58
1.7

Study Details

Study Description

Brief Summary

Mood disorders (including bipolar disorder and major depressive disorder) are chronic mental disorders with high recurrent rate. The more the number of recurrence is, the worse long-term prognosis is. This study aims to establish a prediction model of recurrence of manic and depressive episodes in mood disorders, with a hope to detect recurrence relapse as early as possible for timely clinical intervention. We will adopt wearable smart watch to collect heart rate, sleep pattern, activity level, as well as emotional status for one year long in 100 patients with bipolar disorder, and annotated their mood status (i.e., manic episode, depressive episode, and euthymic state). We expect to establish prediction models to predict the recurrence of mood episodes.

Condition or Disease Intervention/Treatment Phase
  • Device: Wearable activity tracker

Study Design

Study Type:
Observational
Anticipated Enrollment :
100 participants
Observational Model:
Case-Only
Time Perspective:
Prospective
Official Title:
Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder
Actual Study Start Date :
Mar 2, 2020
Anticipated Primary Completion Date :
Dec 31, 2024
Anticipated Study Completion Date :
Dec 31, 2024

Arms and Interventions

Arm Intervention/Treatment
BP

100 patients with mood disorders from the psychiatric ward and outpatient services of the Department of Psychiatry, National Taiwan University Hospital

Device: Wearable activity tracker
Garmin smartwatch will record features, such as activities, heart rate, sleep, through smartphone App

Outcome Measures

Primary Outcome Measures

  1. Prediction Model [1 year]

    Collected data will apply to learning algorithm, random forest, which constructs a multitude of decision trees at training time and outputting a class that is the mode of the classes of the individual trees

Eligibility Criteria

Criteria

Ages Eligible for Study:
20 Years to 60 Years
Sexes Eligible for Study:
All
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • DSM-5 Bipolar disorder or depressive disorder

  • 20~60 years old

  • Willing to carry smartwatch and smartphone most of the time

Exclusion Criteria:
  • Comorbid with substance use disorder

  • Unable to use smartwatch and smartphone

Contacts and Locations

Locations

Site City State Country Postal Code
1 National Taiwan University Hospital Taipei Taiwan

Sponsors and Collaborators

  • National Taiwan University Hospital

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
National Taiwan University Hospital
ClinicalTrials.gov Identifier:
NCT05828056
Other Study ID Numbers:
  • 202002006RINA
First Posted:
Apr 25, 2023
Last Update Posted:
Apr 25, 2023
Last Verified:
Mar 1, 2023
Individual Participant Data (IPD) Sharing Statement:
No
Plan to Share IPD:
No
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by National Taiwan University Hospital
Additional relevant MeSH terms:

Study Results

No Results Posted as of Apr 25, 2023