Transforming Diabetic Vision Health: Innovative AI Enhances Youth Screening Efficiency

by | Jan 12, 2024

A major breakthrough in screening and follow-up for diabetic retinopathy in young people has been achieved at the Johns Hopkins Pediatric Diabetes Center in Baltimore, Maryland. Researchers conducted the ACCESS trial, which used an autonomous AI system called IDx-DR to diagnose diabetic eye disease (DED) without the need for pharmacologic dilation. This new approach has the potential to revolutionize the management of diabetic retinopathy in young people, making screening services more accessible and empowering them to prioritize their eye health.

The trial, which followed the requirements for randomized control trials, enrolled participants between Nov 2021 and Jun 2022, with follow-up completed by Dec 2022. The study included young people aged 8 to 21 years with type 1 or type 2 diabetes who needed DED screening.

To ensure fairness between the control and intervention groups, randomization was used. The intervention group used the autonomous AI system, which provided an independent medical diagnosis and guided operators in taking high-quality images for diagnosis. The AI system reported one of three outcomes: “DED present, refer to a specialist,” “DED not present, test again in 12 months,” or “insufficient image quality.”

One advantage of the AI system was its ability to diagnose without the need for pharmacologic dilation, making the screening process more accessible and appealing to young people. Traditional dilation procedures can be uncomfortable and inconvenient, often discouraging people from getting necessary eye exams. By removing this barrier, the AI technology in the ACCESS trial aimed to increase screening completion rates and improve the management of diabetic eye disease.

Participants in the intervention group received personalized educational interventions for follow-up eye care based on the AI diagnosis. This approach aimed to empower participants and increase screening rates, ensuring that young people understood the importance of regular eye exams and were ready to seek appropriate follow-up care.

While the AI system was not officially approved for use in individuals under 22 years old, all images were reviewed by a board-certified retina specialist to ensure safety and accuracy. This additional oversight enhanced the reliability of the AI system’s diagnoses.

Data for the trial were collected from electronic health records, including demographic information, diabetes-related details, and medical history. Self-reported parental education status and household income provided insights into potential socioeconomic factors influencing screening rates.

The primary outcome of the study was the proportion of participants who completed a documented diabetic eye exam in each group. The secondary outcome focused on the proportion of participants who completed follow-through at the eye care provider. These measures allowed researchers to evaluate the effectiveness of the AI system and the educational intervention in improving screening rates and subsequent eye care.

The sample size calculation ensured that the study had enough statistical power to draw meaningful conclusions from the data. By enrolling 164 participants, the trial had an 80% power to detect a 20% difference in screening completion rates.

By using AI technology, the ACCESS trial aimed to revolutionize diabetic eye care for young people. The autonomous AI system provided timely and accurate diagnoses, reducing the burden on healthcare professionals and improving access to screening services. Moreover, the educational intervention offered personalized guidance, empowering participants to prioritize their eye health and seek appropriate follow-up care.

The groundbreaking results of the ACCESS trial demonstrate the potential of AI technology to revolutionize diabetic eye care and inspire future research in this rapidly evolving field. As AI continues to advance, its integration into healthcare practices holds immense promise for enhancing diagnostic accuracy, improving patient outcomes, and reducing healthcare disparities.

This innovative approach has the potential to transform the management of diabetic retinopathy in young people. By increasing awareness, streamlining the screening process, and providing targeted interventions, the ACCESS trial has paved the way for improved eye care outcomes and better overall diabetes management in young people.

With further research and advancements, AI-powered interventions may become standard practice in diabetic eye care, ensuring that young people receive the necessary screenings and treatments to protect their vision and overall health. The ACCESS trial conducted at the Johns Hopkins Pediatric Diabetes Center has demonstrated the effectiveness of an autonomous AI system in increasing screening and follow-up rates for diabetic retinopathy in young people. The results of this trial will undoubtedly inspire future research in this rapidly evolving field, bringing us closer to a future where AI technology revolutionizes diabetic eye care for everyone.