Screening for diabetic retinopathy at a health centre in South Africa: A cross-sectional study.

Abstract

Background: In South Africa, screening for diabetic retinopathy (DR) is non-existent at the primary healthcare (PHC) level because of the absence of a screening programme. This leads to preventable vision loss.

Aim: To describe the clinical characteristics and outcomes of eye screenings and subsequent referrals.

Setting: Laudium Community Health Centre (CHC), a PHC facility in Tshwane.

Methods: We conducted a cross-sectional study from February 2022 to August 2022. Individuals with diabetes were screened for eye complications using visual acuity testing, intraocular pressure measurement, and fundoscopy with a non-mydriatic digital fundus camera. Fundus images were analysed by an optometrist and an artificial intelligence (AI) programme. Demographic and clinical data were collected.

Results: A total of 120 participants were included, with the majority (60.7%) from Laudium CHC. Most participants (64.2%) were on oral agents, and 66.7% were women. The mean haemoglobin A1c (HbA1c) was 8.3%, with a median diabetes duration of 8 years. Artificial intelligence detected more glaucoma cases (17.5% vs 9.2%) and DR (23.3% vs 15.8%) compared to the optometrist. In contrast, the optometrist identified more cases of macula pathology (29.2% vs 19.2%). Participants (n = 79) were referred to an ophthalmologist for diagnosis confirmation and management.

Conclusion: The study revealed that while DR was not highly prevalent among PHC patients with diabetes, there was a significant referral rate for other ocular complications. Artificial intelligence can enhance early detection and improve efficiency.

Contribution: The findings underscore the need to integrate diabetes eye screening programmes into PHC services for people living with diabetes.