ACCESS

AI for Children's diabetiC Eye ExamS — Autonomous Artificial Intelligence Increases Screening and Follow-up for Diabetic Retinopathy in Youth

Patient / Population Intervention / Exposition Vergleich Endpunkt

In 164 youths aged 8–21 years with type 1 or type 2 diabetes at an academic paediatric diabetes centre, an autonomous AI diabetic eye examination at the point of care increased diabetic eye exam completion within 6 months compared with scripted referral to an eye care provider with education.

N
164
Design
Parallel-group RCT, single academic paediatric diabetes centre
Endpunkt
Diabetic eye exam completion rate within 6 months
Relevanz
2
ErgebnisExam completion 100% (95% CI 95.5–100%) vs 22% (95% CI 14.2–32.4%); P<0.001. Among 25/81 intervention participants with an abnormal result, 64% (16/25) completed follow-through with an eye care provider vs 22% in the control arm (P<0.001).
Wolf RM, et al. Nat Commun. 2024;15(1):421. 10.1038/s41467-023-44676-z
Diskussion & Kritik

Shows autonomous AI closing a screening gap in a racially and ethnically diverse youth population where referral alone fails — the access argument for AI rather than the accuracy one. Single centre, 164 participants, and the endpoint is exam completion rather than retinopathy detected or vision preserved; because the comparator was a referral, the trial tests point-of-care delivery as much as the AI itself.