Identification of Predictive Biomarkers of Mood Relapses in Patients With Bipolar Disorder (Predibip)
Primary Purpose
Bipolar Disorder
Status
Unknown status
Phase
Not Applicable
Locations
Study Type
Interventional
Intervention
clinical assessment (mood relapses identification)
Sponsored by
About this trial
This is an interventional prevention trial for Bipolar Disorder
Eligibility Criteria
Inclusion Criteria:
- Voluntary subjects responding to the diagnosis of bipolar I or II disorder according to the criteria of the DSM-5
- Agreement to benefit from connected objects required for study and able to understand their use
- Age between 18 and75 years old
- Affiliated to the Social Security system (beneficiary or entitled)
- No opposition signed
Exclusion Criteria:
- Subject included in clinical and/or therapeutic experimentation with exclusion period
- Primary psychiatric pathology other than bipolar type I or II disorder
- Patient hospitalized without consent
- Subject deprived of liberty by judicial or administrative decision
- Pregnant, parturient, breastfeeding woman
- Known allergy to one of the materials of the bracelets
Sites / Locations
Arms of the Study
Arm 1
Arm Type
Experimental
Arm Label
Bipolar Patients with connected devices
Arm Description
Patients with bipolar disorder provided with connected devices (wristwatch and wristband)
Outcomes
Primary Outcome Measures
Prediction of mood relapses
number of relapses predicted by machine learning algorithms versus number of relapses highlighted by clinical assessment
Secondary Outcome Measures
Correlation between values of Heart rate variability and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Heart rate variability (HRV) (ms)
Correlation between values of skin surface temperature and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Physical parameters measured: Skin surface temperature in °C
Correlation between values of actimetry and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Physical parameters measured: Actimetry using accelerometer (movement per minute)
Correlation between ElectroDermal activity and the occurrence of a thymic relapse (number of relapses during the follow-up period).
ElectroDermal activity (siemens)
Correlation between sleep periods and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Sleep periods
Correlation between social measures and the occurrence of a thymic relapse (number of relapses during the follow-up period).
The internet connection times (minute), including social networks, the number and duration (minute) of telephone calls and the number and length (number of characters) of text messages will be automatically recorded daily in order to provide parameters that help quantify the patient's social activity.
Correlation between values of clinical characteristics (age of onset) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Age of onset (in years)
Correlation between values of clinical characteristics about thyme episode and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Predominant polarity (hypo/manic or depressive or without), polarity of last episode (hypo/manic or depressive), number of previous thymic episodes, duration of remission (in month).
Correlation between values of clinical characteristics (suicide attempts) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Number of suicide attempts.
Correlation between values of clinical characteristics (hospitalizations) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Number of hospitalizations.
Correlation between values of clinical characteristics (comorbid disorders) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
History and presence of comorbid disorders.
Correlation between values of clinical characteristics (medication) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Medication load (in Chlorpromazine equivalent for antipsychotic medication, Chen&Davis).
Full Information
NCT ID
NCT04703972
First Posted
December 2, 2020
Last Updated
January 13, 2021
Sponsor
University Hospital, Grenoble
Collaborators
Commissariat A L'energie Atomique
1. Study Identification
Unique Protocol Identification Number
NCT04703972
Brief Title
Identification of Predictive Biomarkers of Mood Relapses in Patients With Bipolar Disorder
Acronym
Predibip
Official Title
Identification of Predictive Biomarkers of Mood Relapses in Patients With Bipolar Disorder
Study Type
Interventional
2. Study Status
Record Verification Date
May 2020
Overall Recruitment Status
Unknown status
Study Start Date
January 13, 2021 (Anticipated)
Primary Completion Date
January 31, 2022 (Anticipated)
Study Completion Date
June 30, 2022 (Anticipated)
3. Sponsor/Collaborators
Responsible Party, by Official Title
Sponsor
Name of the Sponsor
University Hospital, Grenoble
Collaborators
Commissariat A L'energie Atomique
4. Oversight
Studies a U.S. FDA-regulated Drug Product
No
Studies a U.S. FDA-regulated Device Product
No
Data Monitoring Committee
No
5. Study Description
Brief Summary
Relapses in bipolar disorders are associated with a significant proportional functional impact, as well as worsening of the course of bipolar disorder, with impairment of the quality of functional remission, as well as the development of addictive, anxiety and suicidal comorbidities.The functional deficit and the instability of the mood disorder increase with thymic relapses. Currently, these relapses (transition from the state of remission, to a depressive or hyperthymic state) are difficult to predict and to treat because of the absence of correlation between the degree of severity of the stressful event (intensity associated stress) and the occurrence of relapse, taking into account the mediation of this relationship by the stress compensation / adaptation capacities, which are very individual.
This project proposes to develop tools based on artificial intelligence technologies to monitor the level of stress and adaptation to life events as well as identifying relapse predictive factors of a patient by using portable and connected devices recording different physiological signals in order to alert him/her when there is a risk of relapse, thus anticipating therapeutic strategies.
6. Conditions and Keywords
Primary Disease or Condition Being Studied in the Trial, or the Focus of the Study
Bipolar Disorder
7. Study Design
Primary Purpose
Prevention
Study Phase
Not Applicable
Interventional Study Model
Single Group Assignment
Masking
None (Open Label)
Allocation
N/A
Enrollment
10 (Anticipated)
8. Arms, Groups, and Interventions
Arm Title
Bipolar Patients with connected devices
Arm Type
Experimental
Arm Description
Patients with bipolar disorder provided with connected devices (wristwatch and wristband)
Intervention Type
Behavioral
Intervention Name(s)
clinical assessment (mood relapses identification)
Other Intervention Name(s)
physiological data monitoring
Intervention Description
clinical assessment via psychometric scales physiological data acquired automatically via the connected device (wristwatch, wristband)
Primary Outcome Measure Information:
Title
Prediction of mood relapses
Description
number of relapses predicted by machine learning algorithms versus number of relapses highlighted by clinical assessment
Time Frame
at Month 6 of the follow-up
Secondary Outcome Measure Information:
Title
Correlation between values of Heart rate variability and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Heart rate variability (HRV) (ms)
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of skin surface temperature and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Physical parameters measured: Skin surface temperature in °C
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of actimetry and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Physical parameters measured: Actimetry using accelerometer (movement per minute)
Time Frame
at Month 6 of the follow-up
Title
Correlation between ElectroDermal activity and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
ElectroDermal activity (siemens)
Time Frame
at Month 6 of the follow-up
Title
Correlation between sleep periods and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Sleep periods
Time Frame
at Month 6 of the follow-up
Title
Correlation between social measures and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
The internet connection times (minute), including social networks, the number and duration (minute) of telephone calls and the number and length (number of characters) of text messages will be automatically recorded daily in order to provide parameters that help quantify the patient's social activity.
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics (age of onset) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Age of onset (in years)
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics about thyme episode and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Predominant polarity (hypo/manic or depressive or without), polarity of last episode (hypo/manic or depressive), number of previous thymic episodes, duration of remission (in month).
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics (suicide attempts) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Number of suicide attempts.
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics (hospitalizations) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Number of hospitalizations.
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics (comorbid disorders) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
History and presence of comorbid disorders.
Time Frame
at Month 6 of the follow-up
Title
Correlation between values of clinical characteristics (medication) and the occurrence of a thymic relapse (number of relapses during the follow-up period).
Description
Medication load (in Chlorpromazine equivalent for antipsychotic medication, Chen&Davis).
Time Frame
at Month 6 of the follow-up
10. Eligibility
Sex
All
Minimum Age & Unit of Time
18 Years
Maximum Age & Unit of Time
75 Years
Accepts Healthy Volunteers
Accepts Healthy Volunteers
Eligibility Criteria
Inclusion Criteria:
Voluntary subjects responding to the diagnosis of bipolar I or II disorder according to the criteria of the DSM-5
Agreement to benefit from connected objects required for study and able to understand their use
Age between 18 and75 years old
Affiliated to the Social Security system (beneficiary or entitled)
No opposition signed
Exclusion Criteria:
Subject included in clinical and/or therapeutic experimentation with exclusion period
Primary psychiatric pathology other than bipolar type I or II disorder
Patient hospitalized without consent
Subject deprived of liberty by judicial or administrative decision
Pregnant, parturient, breastfeeding woman
Known allergy to one of the materials of the bracelets
Central Contact Person:
First Name & Middle Initial & Last Name or Official Title & Degree
Mircea POLOSAN, MD-PhD
Phone
04 76 76 54 11
Email
MPolosan@chu-grenoble.fr
First Name & Middle Initial & Last Name or Official Title & Degree
Arnaud Pouchon, MD
Phone
04 76 76 54 11
Email
APouchon@chu-grenoble.fr
12. IPD Sharing Statement
Plan to Share IPD
Undecided
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Identification of Predictive Biomarkers of Mood Relapses in Patients With Bipolar Disorder
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