Automated Diagnostic Test for Diabetic Retinopathy in Brazilian Mass Screening

Diabetic Retinopathy Clinical Trial

Official title:

Automated Diagnostic Test for Diabetic Retinopathy in Brazilian Mass Screening

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT02927561
• Other study ID #: Retina C
• Status: Completed
• Phase: N/A
• First received: September 30, 2016
• Last updated: October 5, 2016
• Start date: June 2015
• Est. completion date: September 2016

Study information

• Verified date: October 2016
• Source: Retina Clinic, Sao Paulo, Brazil
• Contact: n/a
• Is FDA regulated: No
• Health authority: Brazil: Ethics Committee
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 220
• Est. completion date: September 2016
• Est. primary completion date: June 2016
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years and older

Eligibility

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

Time Perspective: Retrospective

Related Conditions & MeSH terms

• Diabetic Retinopathy
• Retinal Diseases

Intervention

Other:
• Diabetic Retinopathy screening
Diabetic Retinopathy screening

Locations

Country	Name	City	State
Brazil	Retina Clinic	São Paulo

Sponsors (1)

Lead Sponsor	Collaborator
Retina Clinic, Sao Paulo, Brazil

Country where clinical trial is conducted

Brazil, 

References & Publications (8)

Bhaskaranand M, Ramachandra C, Bhat S, Cuadros J, Nittala MG, Sadda S, Solanki K. Automated Diabetic Retinopathy Screening and Monitoring Using Retinal Fundus Image Analysis. J Diabetes Sci Technol. 2016 Feb 16;10(2):254-61. doi: 10.1177/1932296816628546. — View Citation

Fleming AD, Philip S, Goatman KA, Olson JA, Sharp PF. Automated assessment of diabetic retinal image quality based on clarity and field definition. Invest Ophthalmol Vis Sci. 2006 Mar;47(3):1120-5. — View Citation

Grading diabetic retinopathy from stereoscopic color fundus photographs--an extension of the modified Airlie House classification. ETDRS report number 10. Early Treatment Diabetic Retinopathy Study Research Group. Ophthalmology. 1991 May;98(5 Suppl):786-8 — View Citation

Malerbi FK, Morales PH, Farah ME, Drummond KR, Mattos TC, Pinheiro AA, Mallmann F, Perez RV, Leal FS, Gomes MB, Dib SA; Brazilian Type 1 Diabetes Study Group. Comparison between binocular indirect ophthalmoscopy and digital retinography for diabetic retin — View Citation

Mendes AB, Fittipaldi JA, Neves RC, Chacra AR, Moreira ED Jr. Prevalence and correlates of inadequate glycaemic control: results from a nationwide survey in 6,671 adults with diabetes in Brazil. Acta Diabetol. 2010 Jun;47(2):137-45. doi: 10.1007/s00592-00 — View Citation

Ribeiro L, Oliveira CM, Neves C, Ramos JD, Ferreira H, Cunha-Vaz J. Screening for Diabetic Retinopathy in the Central Region of Portugal. Added Value of Automated 'Disease/No Disease' Grading. Ophthalmologica. 2014 Nov 26. [Epub ahead of print] — View Citation

Scotland GS, McNamee P, Philip S, Fleming AD, Goatman KA, Prescott GJ, Fonseca S, Sharp PF, Olson JA. Cost-effectiveness of implementing automated grading within the national screening programme for diabetic retinopathy in Scotland. Br J Ophthalmol. 2007 — View Citation

Soto-Pedre E, Navea A, Millan S, Hernaez-Ortega MC, Morales J, Desco MC, Pérez P. Evaluation of automated image analysis software for the detection of diabetic retinopathy to reduce the ophthalmologists' workload. Acta Ophthalmol. 2015 Feb;93(1):e52-6. do — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To compare the sensitivity and specificity of automated grading system versus human grading in detecting diabetic retinopathy	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.	6 months	No