ackground: The prevalence of uncorrected refractive error among school-age children is on the rise with detrimental effect on academic performance and socio-economic status of those affected. School vision screening programmes appear to be an effective way of identifying children with uncorrected refractive errors so early intervention can be made. Despite the increasing popularity of school vision screening programmes over the past few years, there is a lot of debate on its effectiveness in reducing the proportion of children with uncorrected refractive error in the long term, especially in settings where resources are limited. Some studies argue that school vision screening programmes are effective while other studies have reported otherwise. The purpose of this systematic review was to assess the effectiveness of school vision screening programmes in reducing uncorrected refractive error among children in low and middle income countries using evidence from published studies. Methods and findings: A comprehensive and systematic strategy was used to search various databases including PubMed, Cochrane Central Register of Controlled Trials (CENTRAL) which contains the Cochrane Eyes and vision Trial Register, the Cochrane Library, Medline (1980-2018), CINAHL, Academic Search Premier, Web of Science, the WHO’s Library Information System, Africa-Wide and Scopus. The search was restricted to articles published in English. Randomized control trials, cross-sectional studies, case-control studies and cohort studies were included in this review. Participants included school children with refractive error. Full-text review of search results, data extraction and risk of bias assessment was done by two independent reviewers. The certainty of the evidence was assessed using the GRADE approach and data were pooled using the random-effect model. Thirty studies met the inclusion criteria. This review found moderate certainty evidence indicating that school vision screenings may be effective in reducing uncorrected refractive error among school children by 81% (95% CI: 77%; 84%), 24% (95% CI: 13%; 35%) and 20% (95% CI: 18%; 22%) at two, six, and more than six months respectively after its introduction. Results: Results of this review also suggest that school vision screening may be effective in achieving 54% (95% CI: 25%; 100%), 57% (95% CI: 46%; 70%), 37% (95% CI: 26%; 52%), and 32% (95% CI: 14%; 72%) spectacle-wear compliance among school children at less than three months, at three months, at six months and at more than six months respectively after its introduction (low to moderate certainty evidence). This review further found moderate to high certainty evidence indicating that school vision screening, together with provision of spectacles, may be relatively cost effective, safe and has a positive impact on the academic performance of school children. Conclusion: The findings of this review show that school vision screening, together with provision of spectacles, may be a safe and cost-effective way of reducing the proportion of children with uncorrected refractive error, with long-term positive impact on academic performance of children. Most of the studies included in this review were, however, conducted in Asia. Research to investigate the effectiveness of school vision screening programmes in other parts of the world like Africa where few studies have been conducted is highly recommended

Studies on artificial intelligence (AI) in screening for diabetic retinopathy (DR) have shown promising results in addressing the mismatch between the capacity to implement DR screening and the increasing DR incidence; however, most of these studies were done retrospectively. This review sought to evaluate the diagnostic test accuracy (DTA) of AI in screening for referable diabetic retinopathy (RDR) in real-world settings. We searched CENTRAL, PubMed, CINAHL, Scopus, and Web of Science on 9 February 2023. We included prospective DTA studies assessing AI against trained human graders (HGs) in screening for RDR in patients living with diabetes. synthesis Two reviewers independently extracted data and assessed methodological quality against QUADAS-2 criteria. We used the hierarchical summary receiver operating characteristics (HSROC) model to pool estimates of sensitivity and specificity and, forest plots and SROC plots to visually examine heterogeneity in accuracy estimates. Finally, we conducted sensitivity analyses to explore the effects of studies deemed to possibly affect the quality of the studies. We included 15 studies (17 datasets: 10 patient-level analysis (N=45,785), and 7 eye-level analysis (N=15,390). Meta-analyses revealed a pooled sensitivity of 95.33%(95% CI: 90.60-100%) and specificity of 92.01%(95% CI: 87.61-96.42%) for patient-level analysis; for the eye-level analysis, pooled sensitivity was 91.24% (95% CI: 79.15-100%) and specificity, 93.90% (95% CI: 90.63-97.16%). Subgroup analyses did not provide variations in the diagnostic accuracy of country classification and DR classification criteria; however, a moderate increase was observed in diagnostic accuracy at the primary-level and, a minimal decrease in the tertiary-level healthcare settings. Sensitivity analyses did not show any variations in studies that included diabetic macular edema in the RDR definition, nor in studies with ≥3 HGs. This review provides evidence, for the first time from prospective studies, for the effectiveness of AI in screening for RDR, in real-world settings.