Establish a Specific Cohort Database for Depressive Disorders

NCT05095662 | Active Not Recruiting DMC

• 1 other identifier: SHDC2020CR6023
• Study Type: observational
• Target: 80,000
• Locations: 1 country
• Sites: 1

Brief Summary

Depression is characterized by high prevalence, high recurrence rate, high disability rate, high suicide rate, and heavy disease burden. However, the diagnosis, treatment, and prognosis of depression are difficult to meet the clinical needs at present. This study plans to integrate a large sample of hospital clinical data, laboratory examination data, brain imaging, and electrophysiological data, as well as audio-visual data, to establish a database for depressive disorder, and long-term follow-up to form a specific disease cohort. This study will provide a scientific basis for exploring biomarkers related to objective diagnosis and treatment of depression.

Conditions

Depressive Disorder

Keywords

depression; cohort study; database

Outcome Measures

Primary Outcomes (1)

• Construct the structured data set for depression by integrating a large sample of outpatient and inpatient clinical data, blood tests, psychological tests, and brain imaging data.

  Have 80000 patients been included.

  3 years

Secondary Outcomes (1)

• Recruitment of 300 patients who was diagnosed as depressive disorders.

  Baseline, and 1,2,3,4,5 years follow-up point

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

1. Depressive disorder cohort study: Outpatient or inpatient patients in Shanghai Mental Health Center, Shanghai Zhongshan Hospital, Renji Hospital and Shanghai Tenth People's Hospital were included in this cohort study if the patients agreed to participate in this study and the patients with depressive disorder met the inclusion and exclusion criteria. 2. Construction of standard database for depression: All inpatients and outpatients of Shanghai Mental Health Center will be included in the special database if they meet the diagnostic criteria for depression（ICD-10）.

You may qualify if:

• Age 18-75
• Meeting ICD-10 depressive episode criteria (F32, F33, F34, F38, F39)
• Cultural, social and educational background sufficient to understand informed consent and research content
• Agree to participate in this study

You may not qualify if:

• Exclude other mental disorders such as bipolar disorder and schizophrenia (but not comorbidities)
• Patients with a history of brain injury or cerebrovascular accident, myocardial infarction, severe liver cirrhosis, acute and chronic renal failure, severe diabetes, aplastic anemia, moderate and severe malnutrition and other serious physical diseases of the nervous, heart, liver, kidney, endocrine and blood systems

Sponsors & Collaborators

• Shanghai Mental Health Center: lead
• Shanghai Zhongshan Hospital: collaborator
• Shanghai 10th People's Hospital: collaborator
• RenJi Hospital: collaborator

Study Sites (1)

Shanghai Mental Health Center

Shanghai, Shanghai Municipality, 200030, China

Location

Related Publications (7)

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  PMID: 19524780 BACKGROUND

• Kessler RC, Chiu WT, Demler O, Merikangas KR, Walters EE. Prevalence, severity, and comorbidity of 12-month DSM-IV disorders in the National Comorbidity Survey Replication. Arch Gen Psychiatry. 2005 Jun;62(6):617-27. doi: 10.1001/archpsyc.62.6.617.

  PMID: 15939839 BACKGROUND

• Gunaratne P, Lloyd AR, Vollmer-Conna U. Mood disturbance after infection. Aust N Z J Psychiatry. 2013 Dec;47(12):1152-64. doi: 10.1177/0004867413503718. Epub 2013 Sep 20.

  PMID: 24056922 BACKGROUND

• Reppermund S, Ising M, Lucae S, Zihl J. Cognitive impairment in unipolar depression is persistent and non-specific: further evidence for the final common pathway disorder hypothesis. Psychol Med. 2009 Apr;39(4):603-14. doi: 10.1017/S003329170800411X. Epub 2008 Jul 30.

  PMID: 18667101 BACKGROUND

• Anoushiravani AA, Patton J, Sayeed Z, El-Othmani MM, Saleh KJ. Big Data, Big Research: Implementing Population Health-Based Research Models and Integrating Care to Reduce Cost and Improve Outcomes. Orthop Clin North Am. 2016 Oct;47(4):717-24. doi: 10.1016/j.ocl.2016.05.008. Epub 2016 Aug 8.

  PMID: 27637658 BACKGROUND

• Murphy DR, Meyer AN, Bhise V, Russo E, Sittig DF, Wei L, Wu L, Singh H. Computerized Triggers of Big Data to Detect Delays in Follow-up of Chest Imaging Results. Chest. 2016 Sep;150(3):613-20. doi: 10.1016/j.chest.2016.05.001. Epub 2016 May 10.

  PMID: 27178786 BACKGROUND

• Auffray C, Balling R, Barroso I, Bencze L, Benson M, Bergeron J, Bernal-Delgado E, Blomberg N, Bock C, Conesa A, Del Signore S, Delogne C, Devilee P, Di Meglio A, Eijkemans M, Flicek P, Graf N, Grimm V, Guchelaar HJ, Guo YK, Gut IG, Hanbury A, Hanif S, Hilgers RD, Honrado A, Hose DR, Houwing-Duistermaat J, Hubbard T, Janacek SH, Karanikas H, Kievits T, Kohler M, Kremer A, Lanfear J, Lengauer T, Maes E, Meert T, Muller W, Nickel D, Oledzki P, Pedersen B, Petkovic M, Pliakos K, Rattray M, I Mas JR, Schneider R, Sengstag T, Serra-Picamal X, Spek W, Vaas LA, van Batenburg O, Vandelaer M, Varnai P, Villoslada P, Vizcaino JA, Wubbe JP, Zanetti G. Making sense of big data in health research: Towards an EU action plan. Genome Med. 2016 Jun 23;8(1):71. doi: 10.1186/s13073-016-0323-y.

  PMID: 27338147 BACKGROUND

MeSH Terms

Conditions

Depressive Disorder; Depression

Condition Hierarchy (Ancestors)

Mood Disorders; Mental Disorders; Behavioral Symptoms; Behavior

Study Officials

• Yiru Fang, M.D., Ph.D.

  Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Target Duration: 1 Year
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: October 14, 2021
• First Posted: October 27, 2021
• Study Start: June 1, 2021
• Primary Completion (Estimated): December 31, 2026
• Study Completion (Estimated): December 31, 2026
• Last Updated: October 27, 2021

Record last verified: 2021-04

Data Sharing

• IPD Sharing: Will not share

Locations

CN (1)