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Posters

Evaluation of an automated image analysis software for the detection of diabetic retinopathy to reduce the ophthalmologist workload

Poster Details

First Author: C.Hernaez-Ortega SPAIN

Co Author(s):    A. Navea   E. Soto-Pedre   J. Morales   S. Millan   P. Perez   C. Desco   0   0 0   0 0   0 0   0 0

Abstract Details



Purpose:

To assess the safety of an automated ‘‘disease/no disease’’ grading system for diabetic retinopathy within a systematic screening program.

Setting:

Cross-sectional observational epidemiologic study.Fundación Oftalmológica del Mediterráneo (FOM), Valencia, Spain.European Innovative Biomedicine Institute (EIBI), Cantabria, Spain.

Methods:

A single central field digital image per eye was obtained from consecutive patients attending a regional primary care based diabetic retinopathy screening program in Valencia (Spain). Photographers were trained nurse assistants. The sensitivity and specificity of the automated system (iGrading- Medalytix Ltd, Manchester UK - operating as more than one microaneurysm detection for disease presence) grader were determined against a manual grading as gold standard.

Results:

5517 patients were screened at twenty-seven Health Centers of four Health Departments. The median age was 69 years (IQR 16 years) and 56% were male. The software classified 44.5% of the patients as having no retinopathy. Detection of retinopathy was achieved with 94.5% sensitivity (95% CI 92.6- 96.5) and 69.1% specificity (95% CI 67.6- 70.6).

Conclusions:

Automated grading of diabetic retinopathy based on a single field plus one microaneurysm detection for disease presence approach seems to be adequate not only in terms of workload reduction but also in terms of safety.

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