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Development and Validation of a Diabetic Retinopathy Referral Algorithm Based on Single-Field Fundus Photography.

ABSTRACT: To develop a simplified algorithm to identify and refer diabetic retinopathy (DR) from single-field retinal images specifically for sight-threatening diabetic retinopathy for appropriate care (ii) to determine the agreement and diagnostic accuracy of the algorithm as a pilot study among optometrists versus "gold standard" (retinal specialist grading).The severity of DR was scored based on colour photo using a colour coded algorithm, which included the lesions of DR and number of quadrants involved. A total of 99 participants underwent training followed by evaluation. Data of the 99 participants were analyzed. Fifty posterior pole 45 degree retinal images with all stages of DR were presented. Kappa scores (?), areas under the receiver operating characteristic curves (AUCs), sensitivity and specificity were determined, with further comparison between working optometrists and optometry students.Mean age of the participants was 22 years (range: 19-43 years), 87% being women. Participants correctly identified 91.5% images that required immediate referral (?) = 0.696), 62.5% of images as requiring review after 6 months (? = 0.462), and 51.2% of those requiring review after 1 year (? = 0.532). The sensitivity and specificity of the optometrists were 91% and 78% for immediate referral, 62% and 84% for review after 6 months, and 51% and 95% for review after 1 year, respectively. The AUC was the highest (0.855) for immediate referral, second highest (0.824) for review after 1 year, and 0.727 for review after 6 months criteria. Optometry students performed better than the working optometrists for all grades of referral.The diabetic retinopathy algorithm assessed in this work is a simple and a fairly accurate method for appropriate referral based on single-field 45 degree posterior pole retinal images.

SUBMITTER: Srinivasan S

PROVIDER: S-EPMC5035083 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Development and Validation of a Diabetic Retinopathy Referral Algorithm Based on Single-Field Fundus Photography.

Srinivasan Sangeetha S Shetty Sharan S Natarajan Viswanathan V Sharma Tarun T Raman Rajiv R

PloS one 20160923 9

<h4>Purpose</h4>To develop a simplified algorithm to identify and refer diabetic retinopathy (DR) from single-field retinal images specifically for sight-threatening diabetic retinopathy for appropriate care (ii) to determine the agreement and diagnostic accuracy of the algorithm as a pilot study among optometrists versus "gold standard" (retinal specialist grading).<h4>Methods</h4>The severity of DR was scored based on colour photo using a colour coded algorithm, which included the lesions of D ...[more]

PMID: 27661981

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Project description:IntroductionDiabetic retinopathy (DR) is one of the most prevalent microvascular complications of diabetes mellitus. Guidelines for DR screening in different countries vary greatly, including fundus photography, slit-lamp biomicroscopy, indirect ophthalmoscopy, Optical Coherence Tomography (OCT), OCT-A and Fundus Fluorescein Angiography (FFA). Two-field non-mydriatic fundus photography (NMFP) is an effective screening method due to its low cost and less time-consuming process. However, it is controversial due to the sensitivity and specificity of two-field NMFP. This review intends to evaluate the performance of the two-field NMFP in diagnosing DR and helps clinicians determine the most optimal screening method.Methods and analysisTwo reviewers will independently search on the Medline, Embase, Cochrane databases, ProQuest, Opengrey, Chinese National Knowledge Infrastructure, Wanfang Data, VIP China Science and Technology Journal Database, Chinese BioMedical Literature Database, ISRCTN, ClinicalTrials.gov and the WHO ICTRP to identify relevant studies. There is no restriction posed on the language of the study. Included studies focus on the performance of two-field NMFP in detecting DR in diabetes patients. Analysis and evaluation of the studies will be examined by two reviewers independently using the Quality Assessment for Diagnostic Accuracy Studies-2 tool and later evaluated using the Population, Intervention, Comparison, Outcome, Study design criteria. A random-effect model will calculate the diagnostic indicators, including the sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic OR, area under the curve and 95% CIs. We will also develop a summary receiver operating characteristic curve. We anticipate analysing subgroups according to the factors, which may lead to heterogeneity, including DR levels of patients, the reference standards, camera models, the interpretation criteria. The data will be analysed by STATA software. This study was registered with PROSPERO.Ethics and disseminationThis review will analyse the published data. Patients/the public were not involved in this research. The results of this study will be published in peer-reviewed journals.Prospero registration numberCRD42020203608.

Project description:PurposeTo compare the detection rate of diabetic retinopathy (DR) lesions and the agreement of DR severity grading using the ultra-widefield color fundus photography (UWF CFP) combined with high-speed ultra-widefield swept-source optical coherence tomography angiography (UWF SS-OCTA) or fluorescein angiography (FFA).MethodsThis prospective, observational study recruited diabetic patients who had already taken the FFA examination from November 2021 to June 2022. These patients had either no DR or any stage of DR. All participants were imaged with a 200° UWF CFP and UWF SS-OCTA using a 24 × 20 mm scan model. Images were independently evaluated for the presence or absence of DR lesions including microaneurysms (MAs), intraretinal hemorrhage (IRH), non-perfusion areas (NPAs), intraretinal microvascular abnormalities (IRMAs), venous beading (VB), neovascularization elsewhere (NVE), neovascularization of the optic disc (NVD), and vitreous or preretinal hemorrhage (VH/PRH). Agreement of DR severity grading based on UWF CFP plus UWF SS-OCTA and UWF CFP plus FFA was compared. All statistical analyses were performed using SPSS V.26.0.ResultsOne hundred and fifty-three eyes of 86 participants were enrolled in the study. The combination of UWF CFP with UWF SS-OCTA showed a similar detection rate compared with UWF CFP plus FFA for all the characteristic DR lesions (p>0.05), except NPAs (p = 0.039). Good agreement was shown for the identification of VB (κ = 0.635), and very good agreement for rest of the DR lesions between the two combination methods (κ-value ranged from 0.858 to 0.974). When comparing the grading of DR severity, very good agreement was achieved between UWF CFP plus UWF SS-OCTA and UWF CFP plusr FFA (κ = 0.869).ConclusionUWF CFP plus UWF SS-OCTA had a very good agreement in detecting DR lesions and determining the severity of DR compared with UWF CFP plus FFA. This modality has the potential to be used as a fast, reliable, and non-invasive method for DR screening and monitoring in the future.

Dataset Information

Development and Validation of a Diabetic Retinopathy Referral Algorithm Based on Single-Field Fundus Photography.

Publications

Development and Validation of a Diabetic Retinopathy Referral Algorithm Based on Single-Field Fundus Photography.

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