Diabete MellitusNCT03899623
Multi-modal Imaging and Artificial Intelligence Diagnostic System for Multi-level Clinical Application
An observational study of Diabete Mellitus and Diabetic Retinopathy, run by Zhongshan Ophthalmic Center, Sun Yat-sen University at 1 site in China.
Trial summary
This study is to build an multi-modal artificial intelligence ophthalmological imaging diagnostic system covering multi-level medical institutions. We are going to evaluate this system in an evidence-based medicine view, taking diabetic retinopathy as an example. Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- Diabete Mellitus, Diabetic Retinopathy
- How many people
- 3,000 participants
- Where
- 1 siteChina
- Study dates
- 23 Apr 2018to 31 Dec 2019
- 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
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Stratified sampling
Who may be able to join
- Group A(normal individuals): Meet all the items 1 ~ 5 below
- No familial or hereditary retinopathy;
- No history of ocular trauma and / or history of ocular disease (except for mild to moderate refractive errors and / or age-related cataracts);
- No drug use history that may cause side effects of retina (such as chloroquine, hydroxychloroquine, chlorpromazine, rifampin, etc.); 4 binocular diopter ≤ ± 6.00D; No systemic diseases that may affect the retina.
- Group B(diabetes patients without ocular complications): meet any of 1 to 3, and both 4 to 5 items
- Diagnosed with type 1 diabetes for more than 5 years;
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- Diagnosed with type 2 diabetes patients;
- Diagnosis of gestational diabetes patients;
- Without systemic disease that may affect the retina except for diabetes;
- Meet the standards of 1 to 4 items.
- Group C(patients with diabetic ocular complications): meet with any of 1 to 3, and all 4 to 6 items
- Diagnosed with type 1 diabetes for more than 5 years;
- Diagnosed with type 2 diabetes patients;
- Diagnosis of gestational diabetes patients;
- Meet the guidelines for diagnosis and treatment of diabetic retinopathy in any stage of diabetic retinopathy and / or diabetic macular edema.
- Without systemic disease that may affect the retina except for diabetes;
- A group to meet the criteria for 1 to 4 items.
Who cannot join
- Refractive pathway is turbid, so that fundus image can not be clearly photographed;
- With other fundus diseases and / or other diseases that seriously affect the visual function;
- Any eye infection, such as conjunctivitis, keratitis, scleritis, endophthalmitis, acute and chronic dacryocystitis, or eye injury;
- Serious systemic diseases such as diabetes, hypertension, heart failur,renal failure;
- Can not cooperate with the examiner due to mental or other reasons.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Zhongshan Opthalmic Center
Guangzhou, Guangdong, 510000
Yuan Jin, Professor, 8602087333391, yuanjincornea@126.com
About this study
This study is to build an multi-modal artificial intelligence ophthalmological imaging diagnostic system covering multi-level medical institutions. We are going to evaluate this system in an evidence-based medicine view, taking diabetic retinopathy as an example. And clinical diagnostic criteria will be made based on this multi-modal artificial intelligence imaging diagnostic system. The study is designed as a cross-sectional study involving 1,000 normal individuals, 1,000 diabetes patients without ocular complications, and 1,000 with diabetic ocular complications. Statistical analysis of the diagnostic sensitivity and specificity of the artificial intelligence system will be made, and ROC curve wil be draw.
- Conditions
- Diabete Mellitus, Diabetic Retinopathy
- Keywords
- Diabete Mellitus, Diabetic Retinopathy, Artificial Intelligence
- Medical subject headings
- Diabetes Mellitus, Diabetic Retinopathy
What is being measured
The primary outcome is the main question the study is designed to answer.
The diagnostic sensitivity, specificity and ROC curve of the artificial intelligence（AI） system compared with reference standard (ophthalmologist).
Sensitivity: the percentage of diabetic retinopathy（DR） patients who are correctly identified as having the condition by AI. Sensitivity=True positive/(True positive+False negative). Specificity: the percentage of healthy people who are correctly identified as not having the condition by AI. Specificity=True negative /(True negative +False positive). The ROC curve was plotted with true positive rate (sensitivity) as the ordinate and false positive rate (1-specificity) as the abscissa.
Measured: It will take 15~20min for each subject to take the exams.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted2 Apr 2019
- Study start23 Apr 2018
- Primary completion31 Dec 2019 (estimated)
- Study completion31 Dec 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Diabete MellitusStudies of the same condition, open and under way.
- More trials run by Zhongshan Ophthalmic Center, Sun Yat-sen UniversityThe 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
- Cohort
- Time perspective
- Cross-sectional
- Enrolment
- 3,000 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Jin Yuan, Zhongshan Ophthalmic Center, Sun Yat-sen University
- Investigators
- Yuan Jin, Professor, Principal investigator, Zhongshan Opthalmic Center
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03899623
- Sponsor's protocol ID
- 2017KYPJ104
- Status last verified
- Mar 2019
- First submitted
- 29 Mar 2019
- Last updated
- 2 Apr 2019
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 2 Apr 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Multi-modal Imaging and Artificial Intelligence Diagnostic System for Multi-level Clinical Application
- ClinicalTrials.gov ID
- NCT03899623
- Acronym / sponsor ID
- 2017KYPJ104
- Conditions
- Diabete Mellitus, Diabetic Retinopathy
- Keywords
- Diabete Mellitus, Diabetic Retinopathy, Artificial Intelligence
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 3,000 participants (estimated)
- Lead sponsor
- Zhongshan Ophthalmic Center, Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 23 Apr 2018 (actual)
- Primary completion
- 31 Dec 2019 (estimated)
- Study completion
- 31 Dec 2019 (estimated)
- First posted
- 2 Apr 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 to build an multi-modal artificial intelligence ophthalmological imaging diagnostic system covering multi-level medical institutions. We are going to evaluate this system in an evidence-based medicine view, taking diabetic retinopathy as an example. And clinical diagnostic criteria will be made based on this multi-modal artificial intelligence imaging diagnostic system. The study is designed as a cross-sectional study involving 1,000 normal individuals, 1,000 diabetes patients without ocular complications, and 1,000 with diabetic ocular complications. Statistical analysis of the diagnostic sensitivity and specificity of the artificial intelligence system will be made, and ROC curve wil be draw.
Study design
- Observational model
- Cohort
- Time perspective
- Cross-sectional
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Stratified sampling
Key inclusion criteria (17 listed)
- Group A(normal individuals): Meet all the items 1 ~ 5 below
- No familial or hereditary retinopathy;
- No history of ocular trauma and / or history of ocular disease (except for mild to moderate refractive errors and / or age-related cataracts);
- No drug use history that may cause side effects of retina (such as chloroquine, hydroxychloroquine, chlorpromazine, rifampin, etc.); 4 binocular diopter ≤ ± 6.00D; No systemic diseases that may affect the retina.
- Group B(diabetes patients without ocular complications): meet any of 1 to 3, and both 4 to 5 items
Key exclusion criteria (5 listed)
- Refractive pathway is turbid, so that fundus image can not be clearly photographed;
- With other fundus diseases and / or other diseases that seriously affect the visual function;
- Any eye infection, such as conjunctivitis, keratitis, scleritis, endophthalmitis, acute and chronic dacryocystitis, or eye injury;
- Serious systemic diseases such as diabetes, hypertension, heart failur,renal failure;
- Can not cooperate with the examiner due to mental or other reasons.
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
The diagnostic sensitivity, specificity and ROC curve of the artificial intelligence（AI） system compared with reference standard (ophthalmologist).
Time frame: It will take 15~20min for each subject to take the exams.
Sensitivity: the percentage of diabetic retinopathy（DR） patients who are correctly identified as having the condition by AI. Sensitivity=True positive/(True positive+False negative). Specificity: the percentage of healthy people who are correctly identified as not having the condition by AI. Specificity=True negative /(True negative +False positive). The ROC curve was plotted with true positive rate (sensitivity) as the ordinate and false positive rate (1-specificity) as the abscissa.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 2 Apr 2019.
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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.
Yuan Jin, Professor principal investigator
Zhongshan Opthalmic 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 Diabete Mellitus and Diabetic Retinopathy, run by Zhongshan Ophthalmic Center, Sun Yat-sen University 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 17 inclusion and 5 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: status not confirmed, as of the sponsor's last update on 2 Apr 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?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
Contact Yuan Jin, Professor (8602087333391, yuanjincornea@126.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
The diagnostic sensitivity, specificity and ROC curve of the artificial intelligence（AI） system compared with reference standard (ophthalmologist). (time frame: It will take 15~20min for each subject to take the exams.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 2 Apr 2019.