Evidence map›Paper›PMID 39514591›Full record

ArticlePLOS digital health2024

Diagnostic accuracy of a smartphone-based device (VistaView) for detection of diabetic retinopathy: A prospective study.

Rida Shahzad, Arshad Mehmood, Danish Shabbir, M A Rehman Siddiqui

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Article in PLOS digital health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Rida ShahzadShahzad Eye Hospital, Karachi, Pakistan.
Arshad MehmoodShahzad Eye Hospital, Karachi, Pakistan.
Danish ShabbirShahzad Eye Hospital, Karachi, Pakistan.
M A Rehman SiddiquiShahzad Eye Hospital, Karachi, Pakistan.ORCID https://orcid.org/0000-0001-5100-3189

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDiabetic retinopathy (DR) is a leading cause of blindness globally. The gold standard for DR screening is stereoscopic colour fundus photography with tabletop cameras. VistaView is a novel smartphone-based retinal camera which offers mydriatic retinal imaging. This study compares the diagnostic accuracy of the smartphone-based VistaView camera compared to a traditional desk mounted fundus camera (Triton Topcon). We also compare the agreement between graders for DR screening between VistaView images and Topcon images. METHODOLOGY: This prospective study took place between December 2021 and June 2022 in Pakistan. Consecutive diabetic patients were imaged following mydriasis using both VistaView and Topcon cameras at the same sitting. All images were graded independently by two graders based on the International Classification of Diabetic Retinopathy (ICDR) criteria. Individual grades were assigned for severity of DR and maculopathy in each image. Diagnostic accuracy was calculated using the Topcon camera as the gold standard. Agreement between graders for each device was calculated as intraclass correlation coefficient (ICC) (95% CI) and Cohen's weighted kappa (k). PRINCIPAL

findingsA total of 1428 images were available from 371 patients with both cameras. After excluding ungradable images, a total of 1231 images were graded. The sensitivity of VistaView for any DR was 69.9% (95% CI 62.2-76.6%) while the specificity was 92.9% (95% CI 89.9-95.1%), and PPV and NPV were 80.5% (95% CI 73-86.4%) and 88.1% (95% CI 84.5-90.9) respectively. The sensitivity of VistaView for RDR was 69.7% (95% CI 61.7-76.8%) while the specificity was 94.2% (95% CI 91.3-96.1%), and PPV and NPV were 81.5% (95% CI 73.6-87.6%) and 89.4% (95% CI 86-92%) respectively. The sensitivity for detecting maculopathy in VistaView was 71.2% (95% CI 62.8-78.4%), while the specificity was 86.4% (82.6-89.4%). The PPV and NPV of detecting maculopathy were 63% (95% CI 54.9-70.5%) and 90.1% (95% CI 86.8-92.9%) respectively. For VistaView, the ICC of DR grades was 78% (95% CI, 75-82%) between the two graders and that of maculopathy grades was 66% (95% CI, 59-71%). The Cohen's kappa for retinopathy grades of VistaView images was 0.61 (95% CI, 0.55-0.67, p<0.001), while that for maculopathy grades was 0.49 (95% CI 0.42-0.57, p<0.001). For images from the Topcon desktop camera, the ICC of DR grades was 85% (95% CI, 83-87%), while that of maculopathy grades was 79% (95% CI, 75-82%). The Cohen's kappa for retinopathy grades of Topcon images was 0.68 (95% CI, 0.63-0.74, p<0.001), while that for maculopathy grades was 0.65 (95% CI, 0.58-0.72, p<0.001).

conclusionThe VistaView offers moderate diagnostic accuracy for DR screening and may be used as a screening tool in LMIC.

Identifiers

PMID39514591
PMCPMC11548746

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