The Diabetic Retinopathy Screening, Prevention and Control Program
For patients and families
In plain language
An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.
- What is being studied
- This is an observational study: the protocol does not assign a study treatment.
- Who it may be relevant to
- Registry conditions: Diabetic Retinopathy. Basic parameters: from 18 years · All.
- What needs checking
- Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
- Where it takes place
- China
- Next step
- Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →
Unsure about the terms? Read our patient guide →
Overview
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.
Primary outcome measures
- Diabetic retinopathy [Time frame: through study completion, up to 20 years]
- Referable diabetic retinopathy [Time frame: through study completion, up to 20 years]
- Vision threatening diabetic retinopathy [Time frame: through study completion, up to 20 years]
- Diabetic macular edema [Time frame: through study completion, up to 20 years]
Secondary outcome measures (12)
- HbA1c (%) [Time frame: through study completion, up to 20 years]
- Smoking history [Time frame: through study completion, up to 20 years]
- Alcohol intake [Time frame: through study completion, up to 20 years]
- Salt intake [Time frame: through study completion, up to 20 years]
- Vegetable and fruits intake [Time frame: through study completion, up to 20 years]
- Physical activity [Time frame: through study completion, up to 20 years]
- Blood pressures (mmHg) [Time frame: through study completion, up to 20 years]
- Lipids (mg/dl) [Time frame: through study completion, up to 20 years]
- Cardiolvascular diseases [Time frame: through study completion, up to 20 years]
- Body mass index (BMI) [Time frame: through study completion, up to 20 years]
- Systolic blood pressure [Time frame: through study completion, up to 20 years]
- Diastolic blood pressure [Time frame: through study completion, up to 20 years]
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.
Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.
Healthy volunteers: Yes
Study design
- Observational model
- Cohort
Study locations
China · 2 centers
- Ruijin hospital, Shanghai Jiao-Tong University School of Medicine — Shanghai
- Shanghai Jiao-Tong University School of Medicine — Shanghai
Publications
- 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 PMID 33087340
Identifiers
NCT: NCT04240652 · Ruijin-20191231