Telemedicine for detecting diabetic retinopathy: a systematic review and meta-analysis

Abstract

Objective: To determine the diagnostic accuracy of telemedicine in various clinical levels of diabetic retinopathy (DR) and diabetic macular oedema (DME).

Methods: PubMed, EMBASE and Cochrane databases were searched for telemedicine and DR. The methodological quality of included studies was evaluated using the Quality Assessment for Diagnostic Accuracy Studies (QUADAS-2). Measures of sensitivity, specificity and other variables were pooled using a random effects model. Summary receiver operating characteristic curves were used to estimate overall test performance. Meta-regression and subgroup analyses were used to identify sources of heterogeneity. Publication bias was evaluated using Stata V.12.0.

Results: Twenty articles involving 1960 participants were included. Pooled sensitivity of telemedicine exceeded 80% in detecting the absence of DR, low- or high-risk proliferative diabetic retinopathy (PDR), it exceeded 70% in detecting mild or moderate non-proliferative diabetic retinopathy (NPDR), DME and clinically significant macular oedema (CSME) and was 53% (95% CI 45% to 62%) in detecting severe NPDR. Pooled specificity of telemedicine exceeded 90%, except in the detection of mild NPDR which reached 89% (95% CI 88% to 91%). Diagnostic accuracy was higher with digital images obtained through mydriasis than through non-mydriasis, and was highest when a wide angle (100-200°) was used compared with a narrower angle (45-60°, 30° or 35°) in detecting the absence of DR and the presence of mild NPDR. No potential publication bias was detected.

Conclusions: The diagnostic accuracy of telemedicine using digital imaging in DR is overall high. It can be used widely for DR screening. Telemedicine based on the digital imaging technique that combines mydriasis with a wide angle field (100-200°) is the best choice in detecting the absence of DR and the presence of mild NPDR.

Keywords: Diagnostic tests/Investigation; Retina; Telemedicine.

Figure 1

Flow chart of study selection.

Figure 2

Results of the Quality Assessment for Diagnostic Accuracy Studies (QUADAS)-2 evaluation of each study.

Figure 3

Forest plots of sensitivity and specificity in telemedicine detection of the absence of DR (A, B), mild NPDR (C, D), moderate NPDR (E, F), severe NPDR (G, H), low-risk PDR (I, J), high-risk PDR (K, L), DME (M, N) and CSME (O, P). DR, diabetic retinopathy; NPDR, non-proliferative diabetic retinopathy; PDR, proliferative diabetic retinopathy; DME, diabetic macular oedema; CSME, clinically significant macular oedema.

Figure 3

Forest plots of sensitivity and specificity in telemedicine detection of the absence of DR (A, B), mild NPDR (C, D), moderate NPDR (E, F), severe NPDR (G, H), low-risk PDR (I, J), high-risk PDR (K, L), DME (M, N) and CSME (O, P). DR, diabetic retinopathy; NPDR, non-proliferative diabetic retinopathy; PDR, proliferative diabetic retinopathy; DME, diabetic macular oedema; CSME, clinically significant macular oedema.

Figure 4

Summary receiver operating characteristic (SROC) curves of various clinical levels of DR and DME: (A) absence of DR; (B) mild NPDR; (C) moderate NPDR; (D) severe NPDR; (E) low-risk PDR; (F) high-risk PDR; (G) DME; and (H) CSME. AUC, area under the curve; DR, diabetic retinopathy; DME, diabetic macular oedema; PDR, proliferative diabetic retinopathy; NPDR, non-proliferative diabetic retinopathy; CSME, clinically significant macular oedema.