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| Name | Class |
|---|---|
| Shanghai Zhongshan Hospital | OTHER |
| Shanghai 10th People's Hospital | OTHER |
| RenJi Hospital | OTHER |
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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.
Together with three tertiary hospitals in Shanghai, Shanghai Tenth People's Hospital, Renji Hospital affiliated to Shanghai Jiaotong University School of Medicine, and Zhongshan Hospital affiliated to Fudan University, Shanghai Mental Health Center will take a lead to establish a big database focused on depressive disorders. Expert consensus will be used to determine the standard for the dataset. Real-world data will be include. To establish a depressive disorders-specific database with multiple functions, such as data insight, data retrieval, cohort project establishment, follow-up, and statistical analysis.
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| Measure | Description | Time Frame |
|---|---|---|
| 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 |
| Measure | Description | Time Frame |
|---|---|---|
| Recruitment of 300 patients who was diagnosed as depressive disorders. | In order to: collect demographic and sociological information., clinical data, social function, cognitive function, and blood index test. Collection of Audio-Visual, as well as brain imaging or electrophysiology if patients agreed to participate in these tests. | Baseline, and 1,2,3,4,5 years follow-up point |
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| Name | Affiliation | Role |
|---|---|---|
| Yiru Fang, M.D., Ph.D. | Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Shanghai Mental Health Center | Shanghai | Shanghai Municipality | 200030 | China |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 19524780 | Background | Phillips MR, Zhang J, Shi Q, Song Z, Ding Z, Pang S, Li X, Zhang Y, Wang Z. Prevalence, treatment, and associated disability of mental disorders in four provinces in China during 2001-05: an epidemiological survey. Lancet. 2009 Jun 13;373(9680):2041-53. doi: 10.1016/S0140-6736(09)60660-7. | |
| 15939839 | Background |
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| ID | Term |
|---|---|
| D003866 | Depressive Disorder |
| D003863 | Depression |
| ID | Term |
|---|---|
| D019964 | Mood Disorders |
| D001523 | Mental Disorders |
| D001526 | Behavioral Symptoms |
| D001519 | Behavior |
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| 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. |
| 24056922 | 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. |
| 18667101 | 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. |
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| 27178786 | 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. |
| 27338147 | 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. |