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Meta-Analysis of the Sensitivity of Decision Support Systems in Diagnosing Diabetic Retinopathy

Authors :
Priscyla Waleska, Simões
Maitê Gabriel, Dos Passos
Laura Lopes, Amaral
Diego, Garcia
Ronaldo Borges, Vicente
Larissa Letieli Toniazzo, de Abreu
Jéssica Katelyn, de Siqueira Vieira
Maria Marlene, de Souza Pires
Eros, Comunello
Luciane Bisognin, Ceretta
Claudia Maria Cabral Moro, Barra
Harki, Tanaka
Deborah Ribeiro, de Carvalho
Tiago Ribeiro, de Oliveira
Patrícia Duarte Simões, Pires
Source :
Studies in health technology and informatics. 264
Publication Year :
2019

Abstract

Diabetic Retinopathy (DR) is one of the most common microvascular complications presenting by patients diagnosticated with diabetic diseases. Uncontrolled hyperglycemia may manifest as visual impairment and blindness. The early detection of DR is essential to minimize the risk and consequence of visual diminishing. The standard gold diagnoses tool relies on different imaging modalities and requires a judgment of expert photographers, which are not available in most of the primary care centers or remote location. In that scenario, an automate or semiautomated DR screening systems can contribute to improving the accuracy of the diagnostic. Thus, we performed a Systematic Review and Meta-Analysis to evaluate the Decision Support Systems (DSS) in diagnosing DR. The overall Diagnostic Odds Ratio was 73.15 (95%CI: 37.54-142.50), sensitivity was 97.70 (95%CI: 97.50-97.90) and specificity was 90.30 (95%CI: 90.00-90.60). Our results corroborate with the concept of usefulness of DSSs in early diagnosis, screening and preliminary evaluation of suspicious images of DR.

Details

ISSN :
18798365
Volume :
264
Database :
OpenAIRE
Journal :
Studies in health technology and informatics
Accession number :
edsair.pmid..........947e2610d980f37ee9f0362f00af1e56