Automated Diagnostic Test for Diabetic Retinopathy in Brazilian Mass Screening

Completed

• Conditions: Diabetic Retinopathy

• Registration Number: NCT02927561
• Lead Sponsor: Retina Clinic, Sao Paulo, Brazil

Brief Summary

In Brazil 10% of the adult population has diabetes. Of these, 39.0% are undiagnosed, at risk for developing complications such as diabetic retinopathy (DR). Due to the increasing prevalence of diabetes and high percentage of patients with uncontrolled disease, cost-effective tools are needed with focused attention on diabetes prevention and management in the current health system. The automatic retinopathy detection can enlarge the screening, reducing the workload and costs compared to manual image graders.

Detailed Description

In the South and Central America Region, an estimated 9.4% of the adult population (20-79 years) has diabetes in 2015, and Brazil is the first country in number of people with diabetes. Of these, 39.0% are undiagnosed, at risk for developing complications such as diabetic retinopathy (DR)(1).

The rising number of people with diabetes in the world has become a real challenge for the public health system to provide care for patients with DR and for people with diabetes at risk for this complication(2). A large proportion of patients with diabetes was inadequately controlled in Brazil, which may contribute to increased rates of diabetic complications (3).

The detection of any degree of DR may result in improved medical monitoring and optimization of risk factors, delaying the progression of the disease(4). In Brazil, the great demand in the public service causes delay in early diagnosis, worsening health status of patients with diabetic retinopathy and increasing the cost of their treatment.

Due to the increasing prevalence of diabetes and high percentage of patients with uncontrolled disease, cost-effective tools are needed with focused attention on diabetes prevention and management in the current health system.

Several studies have shown that systematic screening for DR is an effective way of prevention (5). Furthermore, the automatic retinopathy detection can enlarge the screening, reducing the workload and costs compared to manual image graders(6). There are no reports on automated DR detection in Brazilian population, especially in screening campaigns with large-scale diagnosis.

Study Timeline

• Study Start: 2015-06
• Primary Completion: 2016-06
• Study Completion: 2016-09
• Study First Submitted: 2016-09-30
• Status Verified: 2016-10
• Study First Submitted QC: 2016-10-05
• Last Update Submitted: 2016-10-05
• Study First Posted: 2016-10-07
• Last Update Posted: 2016-10-07

Recruitment & Eligibility

• Status: COMPLETED
• Sex: All
• Target Recruitment: 220

Inclusion Criteria

• Adults ≥ 18 years with type 1 or 2 diabetes mellitus

Exclusion Criteria

• Previous cataract, trabeculectomy or vitrectomy
• Aphakia
• External ocular infections
• Glaucoma (IOP of > 21 mmHg or regular use of more than 2 IOP lowering drugs)
• Pregnancy or breastfeeding.

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Primary Outcome Measures

Name	Time	Method
To compare the sensitivity and specificity of automated grading system versus human grading in detecting diabetic retinopathy	6 months	The aim of this study is to determine the sensitivity and specificity of automated grading system in detecting diabetic retinopathy compared with human grading on the population of annual massive screening campaign for diabetes conducted in the Northeast of Brazil.

Trial Locations

Locations (1)

Retina Clinic; 🇧🇷 São Paulo, Brazil