Bipolar Disorder and Oxidative Stress Injury Mechanism - Clinical Big Data Analysis Based on Machine Learning

NCT03949218 | Completed

• 1 other identifier: CRC2018DSJ01-1
• Study Type: observational
• Target: 3,702
• Locations: 1 country
• Sites: 1

Brief Summary

This study is a single-center, retrospective, cross-sectional study. We plan to work with our network information center to analysis the related indicators of oxidative stress injury in patients with bipolar disorder based on oxidative stress data. During the study, machine learning was used as a data analysis method to screen out the biomarker risk factors with sensitivity and specificity for early recognition of bipolar disorder from major depression disorder with oxidative stress injury as the core. And then build up effective clinical predictive models for early identification of bipolar disorder, which can predict the early quantitative probabilistic of the onset of bipolar disorder.

Conditions

Bipolar Disorder

Keywords

bipolar disorder; machine learning

Outcome Measures

Primary Outcomes (1)

• Early prediction model of bipolar disorder with oxidative stress index as the core

  Based on the oxidative stress data, the study will analysis related indicators of oxidative stress injury in patients with bipolar disorder. Then use the method of machine learning to build up the early prediction model of bipolar disorder.

  at August 2019

Study Arms (2)

bipolar disorder(BD)

hospitalized patients BD patients in SMHC from 2009 to 2018; meet ICD-10 diagnosis of F31 bipolar disorder criteria and its subtype (mental examination was conducted by three levels of doctors including at least one attending physician and one chief physician in psychiatric); available relevant HIS system biochemical data; hospitalized patients need to the first admission; age and gender is not limited

major depressive disorder（MDD）

hospitalized patients MDD patients in SMHC from 2009 to 2018; meet ICD-10 diagnosis of F32 depressive disorder criteria and its subtype (mental examination was conducted by three levels of doctors including at least one attending physician and one chief physician in psychiatric); available relevant HIS system biochemical data; hospitalized patients need to the first admission; age and gender is not limited

Eligibility Criteria

• Sex: all
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Subjects are hospitalized patients in SMHC from 2009 to 2018; meet ICD-10 diagnosis of F31 bipolar disorder, F32 depressive disorder criteria and its subtype (mental examination was conducted by three levels of doctors including at least one attending physician and one chief physician in psychiatric); available relevant HIS system biochemical data; hospitalized patients need to the first admission; age and gender is not limited

You may qualify if:

• age is not limited
• gender is not limited
• meets the diagnostic criteria for bipolar disorder of ICD-10 F31,F32 and its sub-categories
• has relevant HIS system data that can be utilized.

You may not qualify if:

• patients who did not meet the appeal diagnosis after three-level rounds of ward
• patients who met the above three diagnoses but had severe data loss (missing value ≥ estimated data value of 30%)

Sponsors & Collaborators

• Shanghai Mental Health Center: lead

Study Sites (1)

Shanghai Mental Health Center

Shanghai, Shanghai Municipality, 200030, China

Location

Related Publications (5)

• Fang Y, Yuan C, Xu Y, Chen J, Wu Z, Cao L, Yi Z, Hong W, Wang Y, Jiang K, Cui X, Calabrese JR, Gao K; OPERATION Study Team. A pilot study of the efficacy and safety of paroxetine augmented with risperidone, valproate, buspirone, trazodone, or thyroid hormone in adult Chinese patients with treatment-resistant major depression. J Clin Psychopharmacol. 2011 Oct;31(5):638-42. doi: 10.1097/JCP.0b013e31822bb1d9.

  PMID: 21869688 RESULT

• Zhang C, Lu W, Wang Z, Ni J, Zhang J, Tang W, Fang Y. A comprehensive analysis of NDST3 for schizophrenia and bipolar disorder in Han Chinese. Transl Psychiatry. 2016 Jan 5;6(1):e701. doi: 10.1038/tp.2015.199.

  PMID: 26731438 RESULT

• Guo X, Li Z, Zhang C, Yi Z, Li H, Cao L, Yuan C, Hong W, Wu Z, Peng D, Chen J, Xia W, Zhao G, Wang F, Yu S, Cui D, Xu Y, Golam CM, Smith AK, Wang T, Fang Y. Down-regulation of PRKCB1 expression in Han Chinese patients with subsyndromal symptomatic depression. J Psychiatr Res. 2015 Oct;69:1-6. doi: 10.1016/j.jpsychires.2015.07.011. Epub 2015 Jul 17.

  PMID: 26343587 RESULT

• Wu X, Wang S, Niu Z, Zhu Y, Sun P, Sun W, Chen J, Fang Y. Bipolar disorder at mixed states and major depressive disorder with mixed features differ in peripheral biochemical parameters. BMC Psychiatry. 2025 Apr 10;25(1):362. doi: 10.1186/s12888-025-06800-9.

  PMID: 40211177 DERIVED

• Zhu Y, Ji H, Niu Z, Liu H, Wu X, Yang L, Wang Z, Chen J, Fang Y. Biochemical and Endocrine Parameters for the Discrimination and Calibration of Bipolar Disorder or Major Depressive Disorder. Front Psychiatry. 2022 Jun 20;13:875141. doi: 10.3389/fpsyt.2022.875141. eCollection 2022.

  PMID: 35795028 DERIVED

MeSH Terms

Conditions

Bipolar Disorder

Condition Hierarchy (Ancestors)

Bipolar and Related Disorders; Mood Disorders; Mental Disorders

Study Officials

• Yiru Fang

  Shanghai Mental Health Center

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: director of clinical research center & division of mood disorders

Study Record Dates

• First Submitted: May 13, 2019
• First Posted: May 14, 2019
• Study Start: November 20, 2018
• Primary Completion: November 20, 2018
• Study Completion: November 20, 2018
• Last Updated: May 14, 2019

Record last verified: 2019-05

Locations

CN (1)