The Diabetic Retinopathy Screening, Prevention and Control Program

NCT ID: NCT04240652

Last Updated: 2020-02-05

Basic Information

• Recruitment Status: RECRUITING
• Total Enrollment: 500000 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2018-06-05
• Study Completion Date: 2040-06-05

Brief Summary

The greatest harm of diabetes is various acute and chronic complications, especially diabetic retinopathy(DR), leading to extremely high rates of disability and blindness. Early screening, early diagnosis, and early treatment are the keys to maintaining vision in patients with DR. However, compared with the high prevalence of diabetes in China, the DR screening ability is relatively inadequate. To change this situation, deep learning(DL), a form of artificial intelligence (AI), might be a potential effective method to solve this dilemma.

Detailed Description

The greatest harm of diabetes is various acute and chronic complications, especially DR, leading to extremely high rates of disability and blindness. However, if the fundus examination is carried out regularly in the early stages of onset, the risk of blindness can be significantly reduced. Therefore, early screening, early diagnosis, and early treatment are the keys to maintaining vision in patients with DR. However, compared with the high prevalence of diabetes in China, the DR screening ability is relatively inadequate.

The Diabetic Retinopathy Screening and Prevention Program is a branch project of MMC. Its purpose is to carry out an efficient workflow for early detecting, timely managing of DR, and to establish a referral system for implementing treatment and the long-term follow-up of DR by means of DL. First, In order to improve its sensitivity and specificity, more participants are involved in other medical institutes besides MMCs, then we can effectively explore the prevalance of DR in China and helps to early screening, prevention, treatment and referal process of DR. Secend, we collect participants' serum, plasma,DNA, several medical stastistics and life styles to explore genetics, new biomarkers, risk factors of DR.

Objective:

1. To validate the methodology and feasibility of DR screening using a DL based automated DR grading system in clinical practice.

2. To explore the prevalence of DR and subgroup identification, and fundus images analysis, etc.

3. To explore the genetics, new biomarkers, risk factors of DR.

4. To explore the methods of early screening, prevention, treatment and referal process of DR.

Conditions

Diabetic Retinopathy

Study Design

• Observational Model Type: COHORT
• Study Time Perspective: PROSPECTIVE

Study Groups

Subjects with fundus photography

Subjects diagnosed with diabetes or not who have fundus images from MMCs and other medical institutes.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Meet the diagnostic criteria for type 2 diabetes according to the World Health Organization (WHO) in 1999; Type 1 diabetes, single gene mutation diabetes, secondary diabetes caused by pancreatic damage, Cushing's syndrome, thyroid dysfunction, or acromegaly;
• Subjects from other medical institutes are diabetes, non-diabetic patients and healthy participants who are invited to participate in the study.

Exclusion Criteria

• Those who have a history of drug abuse;
• Sexually transmitted diseases such as AIDS and syphilis, and infectious diseases such as viral hepatitis and tuberculosis which are at active phase;
• Any condition that the investigator think that the subject is not suitable for participating in the study.

For detailed In-/Ex-clusion criteria please see the study protocol.

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

Shanghai Jiao Tong University School of Medicine

OTHER

Sponsor Role: lead

Responsible Party

Guang Ning

Professor

Responsibility Role: PRINCIPAL_INVESTIGATOR

Principal Investigators

Guang Ning, MD,PHD

Role: PRINCIPAL_INVESTIGATOR

Shanghai Jiao Tong University School of Medicine Shanghai, Shanghai, China

Locations

Ruijin hospital, Shanghai Jiao-Tong University School of Medicine

Shanghai, Shanghai Municipality, China

Site Status: RECRUITING

Shanghai Jiao-Tong University School of Medicine

Shanghai, , China

Site Status: RECRUITING

Countries

China

Central Contacts

Guang Ning, MD,PHD

Role: CONTACT

guangning@medmail.com.cn

8621-64370045 ext. 665344

Facility Contacts

Guang Ning, Professor

Role: primary

feifei1116@hotmail.com

8621-64370045 ext. 671817

Guang Ning, MD,PHD

Role: primary

guangning@medmail.com.cn

008621 64370045 ext. 671817

References

Zhang Y, Shi J, Peng Y, Zhao Z, Zheng Q, Wang Z, Liu K, Jiao S, Qiu K, Zhou Z, Yan L, Zhao D, Jiang H, Dai Y, Su B, Gu P, Su H, Wan Q, Peng Y, Liu J, Hu L, Ke T, Chen L, Xu F, Dong Q, Terzopoulos D, Ning G, Xu X, Ding X, Wang W. Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study. BMJ Open Diabetes Res Care. 2020 Oct;8(1):e001596. doi: 10.1136/bmjdrc-2020-001596.

Reference Type: DERIVED

PMID: 33087340 (View on PubMed)

Other Identifiers

Ruijin-20191231

Identifier Type: -

Identifier Source: org_study_id