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

NCT05828056 | Unknown

• 1 other identifier: 202002006RINA
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

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.

Conditions

Bipolar Disorder; Depressive Disorder

Keywords

biomarker; Bipolar disorder

Outcome Measures

Primary Outcomes (1)

• Development and verification of mood episode prediction algorithm

  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. Performance of the trained prediction model was evaluated by assessing the model's accuracy, sensitivity, specificity, and the area under the curve. In a machine learning evaluation process, a part of data is used for model training, and the other portion is used for model testing.

  1 year

Study Arms (1)

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

Interventions

Wearable activity tracker DEVICE

Garmin smartwatch will record features, such as activities, heart rate, sleep, through smartphone App

BP

Eligibility Criteria

• Age: 20 Years - 60 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

We will recruit 100 patients with mood disorders from the psychiatric ward and outpatient services of the Department of Psychiatry, National Taiwan University Hospital. All the participants will be followed for one year to collect the daily activity level, sleep patterns, heart rate through actigraphy, as well as location, mood report, drug compliance and face photo through smartphone app that will be developed by Co-PI Lai.

You may qualify if:

• DSM-5 Bipolar disorder or depressive disorder
• \~60 years old
• Willing to carry smartwatch and smartphone most of the time

You may not qualify if:

• Comorbid with substance use disorder
• Unable to use smartwatch and smartphone

Sponsors & Collaborators

• National Taiwan University Hospital: lead

Study Sites (1)

National Taiwan University Hospital

Taipei, Taiwan

RECRUITING

MeSH Terms

Conditions

Bipolar Disorder; Depressive Disorder

Condition Hierarchy (Ancestors)

Bipolar and Related Disorders; Mood Disorders; Mental Disorders

Central Study Contacts

Yi-Ling Chien

CONTACT

+886223123456#66013; chienyiling@gmail.com

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 13, 2023
• First Posted: April 25, 2023
• Study Start: March 2, 2020
• Primary Completion: December 31, 2024
• Study Completion: December 31, 2024
• Last Updated: May 6, 2023

Record last verified: 2023-03

Data Sharing

• IPD Sharing: Will not share

Locations

TW (1)