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Click to read this report on the benefits of Retinal Imaging: Digital Retinal Imaging for Vision-threatening Diseases- An Integrated Approach to Diagnostic Screening with a Non-Mydriatic Camera.
Retinopathy Screening Ratios May Improve With Telemedicine-Based Digital Retinal Imaging
Digital imaging technology used during primary care visits can significantly improve diabetic retinopathy screening rates compared with conventional methods, increase access to recommended diabetic eyecare and focus specialty care on medically indigent patients with greatest need, according to this study by Vanderbilt University.
The aim of the retrospective cohort study was to evaluate the impact of a telemedicine, digital retinal imaging strategy on diabetic retinopathy screening rates in an inner-city primary care clinic. It included all patients with diabetes aged 18 or older (495 patients) seen at Vine Hill Community Clinic between September 1, 2003, and August 31, 2004. Patients were offered an ophthalmology referral or digital screening. Those who chose referral received the next available appointment (within three months) at the Vanderbilt Eye Clinic; those who chose digital screening were screened during the visit.
Retinal screening was documented for 293 patients (59.2 percent), a significant improvement compared with the 23 percent baseline rate. Of 293 patients screened, 92 (31.4 percent) were screened in ophthalmology, and 201 (68.6 percent) were digitally screened. Among the 201 digitally screened patients, 104 (51.7 percent) screened negative and were advised to rescreen in one year, 75 (37.3 percent) screened positive and were nonurgently referred to ophthalmology and 22 (11.0 percent) screened positive for sight-threatening eye disease and were urgently referred for ophthalmological follow-up. Digital imaging technical failure rate was 0.5 percent. Referral status was associated with race/ethnicity, with whites more likely to screen negative (62.4 percent) than non-whites (47.8 percent). Sight-threatening disease among non-whites (14.7 percent) was more than double that observed for whites (5.9 percent).
SOURCE: Taylor CR, Merin LM, Salunga AM, et al. Improving diabetic retinopathy screening ratios using telemedicine-based digital retinal imaging technology: The Vine Hill Study. Diabetes Care 2007;30(3):574-8.
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Abstract
Sensitivity and specificity of digital retinal imaging for screening diabetic retinopathy
J. Lopez-Bastida, F. Cabrera-Lopez, Department of Ophthalmology, Insular-Maternoinfantil University Hospital, Las Palmas de Gran Canaria, Canary Islands Health Service, Canary Islands, Spain and P. Serrano-Aguilar, Evaluation and Planning Unit, Canary Islands Health Service and Department of Ophthalmology, Insular-Maternoinfantil University Hospital, Las Palmas de Gran Canaria, Canary Islands Health Service, Canary Islands, Spain
Correspondence to: Julio López-Bastida, C/Pérez de Rozas, 5–4° 38004–Santa Cruz de Tenerife, Canary Islands, Spain. E-mail: jlopbas@gobiernodecanarias.org
Keywords diabetic retinopathy, non-mydriatic digital camera, screening, Spain
Diabet. Med. (2007)
Abstract
Aims To assess the effectiveness of a non-mydriatic digital camera (45°−30° photographs) compared with the reference method for screening diabetic retinopathy.
Methods Type 1 and 2 diabetic patients (n = 773; 1546 eyes) underwent screening for diabetic retinopathy in a prospective observational study. Hospital-based non-mydriatic digital retinal imaging by a consultant specialist in retinal diseases was compared with slit-lamp biomicroscopy and indirect ophthalmoscopy through dilated pupils, as a gold standard, previously performed in a community health centre by another consultant specialist in retinal diseases. The main outcome measures were sensitivity and specificity of screening methods and prevalence of diabetic retinopathy.
Results The prevalence of any form of diabetic retinopathy was 42.4% (n = 328); the prevalence of sight-threatening including macular oedema and proliferative retinopathy was 9.6% (n = 74). Sensitivity of detection of any diabetic retinopathy by digital imaging was 92% (95% confidence interval 90, 94). Specificity of detection of any diabetic retinopathy was 96% (95, 98). The predictive value of the negative tests was 94% and of a positive test 95%. For sight-threatening retinopathy digital imaging had a sensitivity of 100%.
Conclusions A high sensitivity and specificity are essential for an effective screening programme. These results confirm digital retinal imaging with a non-mydriatic camera as an effective option in community-based screening programs for diabetic retinopathy.
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