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The Study of Relapse Predicting Model for First Episode Depression: Big Data Analysis Based on Clinical Features and Immunochemistry
Major depressive depression(MDD) is an severe public mental disorders. The purpose of current study is using big data analysis based on clinical features and immunochemistry to investigate and establish an relapse predict model for patients with first episode MDD.
Major depressive depression(MDD) is an severe public mental disorders. The purpose of current study is using big data analysis based on clinical features and immunochemistry to investigate and establish an relapse predict model for patients with first episode MDD. This study includes two steps. Step 1: Big data analysis based on the clinical features and immunochemical figures of 30000 patients with first episode MDD will be conducted to construct a relapse predict model. Step 2: 300 patients with first episode MDD will be recruited in this step. Physicians prefer to give corresponding treatment recommendation based on the predictive factors to verify this relapse model.
Age
18 - 65 years
Sex
ALL
Healthy Volunteers
Yes
Start Date
December 1, 2016
Primary Completion Date
December 1, 2018
Completion Date
December 1, 2019
Last Updated
October 26, 2016
300
ESTIMATED participants
Clinical features and medication
OTHER
Psycho-social
OTHER
immunology
OTHER
Laboratory abnormality
OTHER
Comorbidity
OTHER
Treatment as usual
OTHER
Lead Sponsor
Shanghai Mental Health Center
Data Source & Attribution
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