title: 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.
authors.affiliation: Department of Medical informatics, Nantong University, Nantong, China Nantong University Library, Nantong, China.
authors.forename: Lili
authors.initials: L
authors.lastname: Shi
authors.affiliation: Department of Medical informatics, Nantong University, Nantong, China.
authors.forename: Huiqun
authors.initials: H
authors.lastname: Wu
authors.affiliation: Department of Medical informatics, Nantong University, Nantong, China.
authors.forename: Jiancheng
authors.initials: J
authors.lastname: Dong
authors.affiliation: Department of Medical informatics, Nantong University, Nantong, China.
authors.forename: Kui
authors.initials: K
authors.lastname: Jiang
authors.affiliation: Department of Ophthalmology, Suzhou Municipal Hospital, Suzhou, China.
authors.forename: Xiting
authors.initials: X
authors.lastname: Lu
authors.affiliation: Department of Ophthalmology, Affiliated Hospital of Nantong University, Nantong, China.
authors.forename: Jian
authors.initials: J
authors.lastname: Shi
mesh_terms: D016208:Databases, Factual; D003930:Diabetic Retinopathy / Q000175:diagnosis*; D006801:Humans; D008269:Macular Edema / Q000175:diagnosis; D012372:ROC Curve; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D017216:Telemedicine / Q000379:methods* / Q000592:standards
keywords: Diagnostic tests/Investigation; Retina; Telemedicine