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Liverpool to lead international diabetic eye disease research project

Posted February 5, 2018

Liverpool is to lead on a £1.15 million international research project to help transform early detection of diabetic eye disease in developing countries.

Researchers from the University of Liverpool, St Paul’s Eye Unit at the Royal Liverpool University Hospital and Peking University People’s Hospital in China aim to transform early detection of diabetic eye disease.

Diabetic retinopathy (DR) is one of the most common causes of visual loss in the world and can be prevented if it is detected early. High blood sugar causes the fine blood vessels in the retina to leak fluid or to close resulting in the retina becoming starved of oxygen and waterlogged.

150 million

Over 110 million people in China live with diabetes and this number is expected to increase to 150m by 2040.

A patient with DR will not be aware of the problem until vision declines, a stage when the damage is often irreversible. Prompt laser treatment, injections of drugs into the eye, or complex surgery, is required to limit the damage. At the moment people with diabetes in China and other rapidly developing countries around the world frequently present with very advance disease.

Improving early diagnosis and treatment of DR is one of the principal objectives of the Chinese Government’s 5-Year National Plan of Eye Health (2016-2020). Current methods of detecting DR rely on costly imaging equipment and many skilled personnel to take and interpret retinal images. China has very few health workers with these skills.

The University of Liverpool in partnership with St Paul’s Eye Unit and the Royal Liverpool and Broadgreen University Hospitals NHS Trust has been leading research into eye screening for the disease since 1991.

Large-scale detection

The research team have developed an innovative whole systems approach for the detection of DR in China which will be scalable and cost-effective to cope with the rapidly increasing and high numbers. They will combine machine and human intelligence with novel, low-cost, diagnostic technologies so that large scale early detection of sight-threatening disease can be performed by non-expert health care workers at the time and place of patient care.

Source: University of Liverpool

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