Bipolar DisorderNCT03949218
Bipolar Disorder and Oxidative Stress Injury Mechanism - Clinical Big Data Analysis Based on Machine Learning
An observational study of Bipolar Disorder, run by Shanghai Mental Health Center at 1 site in China.
Trial 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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Bipolar Disorder
- How many people
- 3,702 participants
- Where
- 1 siteChina
- Study dates
- 20 Nov 2018to 20 Nov 2018
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- Child, Adult, Older adult
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
Who may be able to join
- 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.
Who cannot join
- 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%)
Trial locations and contacts
1 site in 1 country.
China1 site
Shanghai Mental Health Center
Shanghai, Shanghai Municipality, 200030
About this study
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
- Medical subject headings
- Bipolar Disorder
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 |
What is being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: at August 2019
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted14 May 2019
- Study start20 Nov 2018
- Primary completion20 Nov 2018
- Study completion20 Nov 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Bipolar DisorderStudies of the same condition, open and under way.
- More trials run by Shanghai Mental Health CenterThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Other
- Time perspective
- Retrospective
- Enrolment
- 3,702 participants (actual)
Sponsor and investigators
- Lead sponsor
- Shanghai Mental Health Center
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Yiru FANG M.D., Ph.D., Shanghai Mental Health Center
- Investigators
- Yiru Fang, Principal investigator, Shanghai Mental Health Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03949218
- Sponsor's protocol ID
- CRC2018DSJ01-1
- Status last verified
- May 2019
- First submitted
- 13 May 2019
- Last updated
- 14 May 2019
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
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.
PubMed 21869688Zhang 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.
PubMed 26731438Guo 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.
PubMed 26343587Wu 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.
PubMed 40211177Zhu 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.
PubMed 35795028
Study at a glance
From the registry record, last updated by the sponsor on 14 May 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Bipolar Disorder and Oxidative Stress Injury Mechanism - Clinical Big Data Analysis Based on Machine Learning
- ClinicalTrials.gov ID
- NCT03949218
- Acronym / sponsor ID
- CRC2018DSJ01-1
- Conditions
- Bipolar Disorder
- Keywords
- bipolar disorder, machine learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 3,702 participants (actual)
- Lead sponsor
- Shanghai Mental Health CenterUniversity, hospital or other
- Study start
- 20 Nov 2018 (actual)
- Primary completion
- 20 Nov 2018 (actual)
- Study completion
- 20 Nov 2018 (actual)
- First posted
- 14 May 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Study design
- Observational model
- Other
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| 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 |
Who may qualify
- Sex
- All
- Age groups
- Child, Adult, Older adult
- 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
Key inclusion criteria (4 listed)
- 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.
Key exclusion criteria (2 listed)
- 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%)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Early prediction model of bipolar disorder with oxidative stress index as the core
Time frame: at August 2019
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.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 14 May 2019.
- Results publication: PubMed 21869688Fang 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.
- Results publication: PubMed 26731438Zhang 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.
- Results publication: PubMed 26343587Guo 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.
- Derived from this study: PubMed 40211177Wu 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.
- Derived from this study: PubMed 35795028Zhu 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Yiru Fang principal investigator
Shanghai Mental Health Center
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Bipolar Disorder, run by Shanghai Mental Health Center at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 14 May 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Early prediction model of bipolar disorder with oxidative stress index as the core (time frame: at August 2019). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03949218, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 14 May 2019.