Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices (IDx-DR)

AI Generated Summary*

A prospective pivotal trial evaluated an autonomous artificial intelligence system for detecting more than mild diabetic retinopathy (mtmDR) in adults with diabetes and no prior retinopathy diagnosis. Across 10 US primary care sites, 900 people enrolled and 819 were analyzable, with mtmDR prevalence of 23.8% in a sample partly enriched for higher glycemic risk. Clinic staff trained for four hours captured the algorithm's images, while certified photographers obtained reference stereoscopic widefield photographs and macular OCT scans graded by a reading center. Sensitivity reached 87.2% (95% CI 81.8 to 91.2) and enrichment-adjusted specificity 90.7% (88.3 to 92.7), clearing goals of 85% and 82.5%; imageability was 96.1%. All proliferative cases were flagged, and findings contributed in part to FDA authorization.

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