PT  - JOURNAL ARTICLE
AU  - Pedro Romero-Aroca
AU  - Raquel Verges
AU  - Najlaa Maarof
AU  - Aida Vallas-Mateu
AU  - Alex Latorre
AU  - Antonio Moreno-Ribas
AU  - Ramon Sagarra-Alamo
AU  - Josep Basora-Gallisa
AU  - Julian Cristiano
AU  - Marc Baget-Bernaldiz
TI  - Real-world outcomes of a clinical decision support system for diabetic retinopathy in Spain
AID  - 10.1136/bmjophth-2022-000974
DP  - 2022 Mar 01
TA  - BMJ Open Ophthalmology
PG  - e000974
VI  - 7
IP  - 1
4099  - http://bmjophth.bmj.com/content/7/1/e000974.short
4100  - http://bmjophth.bmj.com/content/7/1/e000974.full
SO  - BMJ Open Ophth2022 Mar 01; 7
AB  - Objective The aim of present study was to evaluate our clinical decision support system (CDSS) for predicting risk of diabetic retinopathy (DR). We selected randomly a real population of patients with type 2 diabetes (T2DM) who were attending our screening programme.Methods and analysis The sample size was 602 patients with T2DM randomly selected from those who attended the DR screening programme. The algorithm developed uses nine risk factors: current age, sex, body mass index (BMI), duration and treatment of diabetes mellitus (DM), arterial hypertension, Glicated hemoglobine (HbA1c), urine–albumin ratio and glomerular filtration.Results The mean current age of 67.03±10.91, and 272 were male (53.2%), and DM duration was 10.12±6.4 years, 222 had DR (35.8%). The CDSS was employed for 1 year. The prediction algorithm that the CDSS uses included nine risk factors: current age, sex, BMI, DM duration and treatment, arterial hypertension, HbA1c, urine–albumin ratio and glomerular filtration. The area under the curve (AUC) for predicting the presence of any DR achieved a value of 0.9884, the sensitivity of 98.21%, specificity of 99.21%, positive predictive value of 98.65%, negative predictive value of 98.95%, α error of 0.0079 and β error of 0.0179.Conclusion Our CDSS for predicting DR was successful when applied to a real population.Data are available upon reasonable request.