People receiving AI-supported screening for diabetic retinopathy, a leading cause of blindness globally, were almost twice as likely to attend specialist follow-up appointments as those receiving standard screening, according to new research from the London School of Hygiene & Tropical Medicine (LSHTM).

In a trial of 2,378 people attending a diabetic eye screening program across 24 hospitals in Tanzania, half of the participants received AI-supported screening, while the other half followed the standard screening pathway.

Of those who received AI-supported screening and had a level of diabetic retinopathy requiring referral, 35.9% attended a specialist clinic within eight weeks, compared with 18.2% of those who received standard screening. Those who attended specialist care after AI screening did so sooner, an average of 10.9 days after screening compared with 36.9 days for those receiving standard screening.

The findings, published in The Lancet Global Health, suggest integrating AI into screening programs could give health care workers more time to provide face-to-face support to patients, particularly in low-resource settings, for conditions where early intervention and treatment are crucial.

The difference may be partially explained by how patients received their results. In the AI-supported pathway, patients were provided with an immediate result, allowing for face-to-face counseling from health care workers. In the standard pathway, retinal images were assessed by a health care worker at a nearby hospital, and results and counseling were given weeks later over the phone.

Dr. Charles Cleland, an ophthalmologist and clinical research fellow at the International Center for Eye Health (ICEH) at LSHTM, said, “Using AI in a diabetic eye screening program in Tanzania enabled patients to receive their result along with face-to-face counseling at the point of screening, giving people the opportunity to ask questions, understand treatment options and feel supported in their care.

“In places where health care workers are already stretched, these results suggest AI could improve access to specialist care and help prevent irreversible sight loss from diabetic retinopathy.”

Diabetic retinopathy is a common complication of diabetes and a leading cause of blindness worldwide. It develops when high blood sugar levels damage the small blood vessels in the retina, the light-sensitive tissue in the back of the eye. In the early stages, the condition may not cause noticeable symptoms, meaning it can progress quickly before patients seek treatment.

The number of people affected by diabetic retinopathy is expected to increase, with an estimated 44–82 million people projected to be at risk of sight loss from the condition by 2045.

Screening can detect early changes in the retina before significant vision loss occurs, allowing for timely treatment that can prevent much of the sight loss caused by diabetic retinopathy. However, access to screening and specialist eye care remains limited in many parts of Africa, meaning people may not receive the follow-up care needed to protect their sight.

These findings suggest integrating AI into screening programs could help address some of these barriers by providing immediate results and creating more opportunities for patients to discuss their condition and treatment options.

The Tanzanian Ministry of Health, a collaborator on the study, has committed to integrating AI diagnostics into diabetic eye screening programs in multiple regions of the country. However, the authors say improved screening needs to be accompanied by better access to specialist clinics and treatments to prevent vision loss from diabetes.

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