Ignite Creation Date:
2025-12-24 @ 11:24 PM
Ignite Modification Date:
2025-12-31 @ 7:55 AM
Study NCT ID:
NCT05828056
Status:
UNKNOWN
Last Update Posted:
2023-05-06
First Post:
2023-04-13
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D001714', 'term': 'Bipolar Disorder'}, {'id': 'D003866', 'term': 'Depressive Disorder'}], 'ancestors': [{'id': 'D000068105', 'term': 'Bipolar and Related Disorders'}, {'id': 'D019964', 'term': 'Mood Disorders'}, {'id': 'D001523', 'term': 'Mental Disorders'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_ONLY'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2020-03-02', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2023-03', 'completionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2023-05-04', 'studyFirstSubmitDate': '2023-04-13', 'studyFirstSubmitQcDate': '2023-04-13', 'lastUpdatePostDateStruct': {'date': '2023-05-06', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2023-04-25', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2024-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Development and verification of mood episode prediction algorithm', 'timeFrame': '1 year', 'description': "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."}]}, 'oversightModule': {'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['biomarker', 'Bipolar disorder'], 'conditions': ['Bipolar Disorder', 'Depressive Disorder']}, 'descriptionModule': {'briefSummary': '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.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT'], 'maximumAge': '60 Years', 'minimumAge': '20 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': '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.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* DSM-5 Bipolar disorder or depressive disorder\n* 20\\~60 years old\n* Willing to carry smartwatch and smartphone most of the time\n\nExclusion Criteria:\n\n* Comorbid with substance use disorder\n* Unable to use smartwatch and smartphone'}, 'identificationModule': {'nctId': 'NCT05828056', 'briefTitle': 'Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder', 'organization': {'class': 'OTHER', 'fullName': 'National Taiwan University Hospital'}, 'officialTitle': 'Prediction on the Recurrence of Manic and Depressive Episodes in Bipolar Disorder', 'orgStudyIdInfo': {'id': '202002006RINA'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'BP', 'description': '100 patients with mood disorders from the psychiatric ward and outpatient services of the Department of Psychiatry, National Taiwan University Hospital', 'interventionNames': ['Device: Wearable activity tracker']}], 'interventions': [{'name': 'Wearable activity tracker', 'type': 'DEVICE', 'description': 'Garmin smartwatch will record features, such as activities, heart rate, sleep, through smartphone App', 'armGroupLabels': ['BP']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Taipei', 'status': 'RECRUITING', 'country': 'Taiwan', 'contacts': [{'name': 'Yi-Ling Chien, MD, PhD', 'role': 'CONTACT', 'email': 'chienyiling@gmail.com', 'phone': '+886223123456#66013'}], 'facility': 'National Taiwan University Hospital', 'geoPoint': {'lat': 25.05306, 'lon': 121.52639}}], 'centralContacts': [{'name': 'Yi-Ling Chien', 'role': 'CONTACT', 'email': 'chienyiling@gmail.com', 'phone': '+886223123456#66013'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO', 'description': 'All the data in this study will be appropriately maintained with protection of privacy and confidentiality. Any personal identifiable data will be replaced by research ID number.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'National Taiwan University Hospital', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}