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Identification of factors to increase efficacy of telemedicine screening for diabetic retinopathy in endocrinology practices using the Intelligent Retinal Imaging System (IRIS) platform.
Diabetes Research and Clinical Practice 2018 June
AIMS: Diabetic retinopathy (DR) and diabetic macular edema (DME) can be evaluated using telemedicine systems, such as the Intelligent Retinal Imaging Systems (IRIS), in patients with Diabetes Mellitus (DM). In an endocrinology-based population utilizing IRIS we determine prevalence rates of DR and DME, and identify associated epidemiologic correlations.
METHODS: This is a multicenter, retrospective chart review using screening data from IRIS. Centers for Disease Control and Prevention (CDC) data on epidemiologic variables (by county) namely, prevalence of DM, incidence of DM, obesity, and time of physical inactivity, were compared against prevalence rates of DR found at screening.
RESULTS: A total of 10,223 eyes of 5,242 patients with DM were imaged. DR and DME were noted in 1781 (33.98%) and 226 imaging studies (4.31%) respectively. The coefficient of determination was greatest for incidence of DM (R2 = 0.92), followed by DM prevalence (R2 = 0.79), obesity, (R2 = 0.67), and physical inactivity (R2 = 0.34). The presence of DR during screening varied significantly by county (p < 0.001).
CONCLUSIONS: Screening in counties with a higher incidence of DM led to a higher prevalence of identified DR at time of screening. The current work suggests that telemedicine screening in areas known to have a higher incidence of DM may be worthwhile.
METHODS: This is a multicenter, retrospective chart review using screening data from IRIS. Centers for Disease Control and Prevention (CDC) data on epidemiologic variables (by county) namely, prevalence of DM, incidence of DM, obesity, and time of physical inactivity, were compared against prevalence rates of DR found at screening.
RESULTS: A total of 10,223 eyes of 5,242 patients with DM were imaged. DR and DME were noted in 1781 (33.98%) and 226 imaging studies (4.31%) respectively. The coefficient of determination was greatest for incidence of DM (R2 = 0.92), followed by DM prevalence (R2 = 0.79), obesity, (R2 = 0.67), and physical inactivity (R2 = 0.34). The presence of DR during screening varied significantly by county (p < 0.001).
CONCLUSIONS: Screening in counties with a higher incidence of DM led to a higher prevalence of identified DR at time of screening. The current work suggests that telemedicine screening in areas known to have a higher incidence of DM may be worthwhile.
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