Real-world Outcomes of a Clinical Decision Support System for Diabetic Retinopathy in Spain

Overview

Journal BMJ Open Ophthalmol

Specialty Ophthalmology

Date 2022 Apr 13

PMID 35415265

Authors

Pedro Romero-Aroca

Raquel Verges

Najlaa Maarof

Aida Vallas-Mateu

Alex Latorre

Antonio Moreno-Ribas

Ramon Sagarra-Alamo

Josep Basora-Gallisa

Julian Cristiano

Marc Baget-Bernaldiz

Affiliations

Soon will be listed here.

Abstract

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.

Citing Articles

Applications of Clinical Decision Support Systems in Diabetes Care: Scoping Review.

Huang S, Liang Y, Li J, Li X J Med Internet Res. 2023; 25:e51024.

PMID: 38064249 PMC: 10746969. DOI: 10.2196/51024.

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