By Gift Briton

Kenya has received a donation of research equipment used to predict the risk of hypertension, diabetes and eye conditions through retinal scanning.

The Ministry of Health received the equipment on behalf of the Kenyan government from AstraZeneca during a ceremony in Nairobi.

Hypertension (blood pressure) and diabetes are among the Non-Communicable Diseases(NCDs) accounting for the death of one in every four people in Kenya annually, according to World Health Organization (WHO).

The equipment is also expected to strengthen local research capacity for NCDs and improve the screening capacity for these diseases in the country by identifying the risk or presence of complications arising particularly from hypertension and diabetes through a single retinal scan instead of separate tests.

“We are glad to support this donation because it will potentially contribute to the future of non-invasive screening for NCDs by empowering the recipient research institutions here in Kenya. This project demonstrates the importance of innovative public-private partnerships (PPPs) by contributing to the Ministry of Health’s mission and National NCD Strategic Plan, ensuring that Kenyans receive the highest attainable standard of NCD care in a sustainable, affordable and accessible manner,” Ashling Mulvaney, Vice President Global Sustainability and Access to Healthcare, AstraZeneca said during the ceremony.

 Ashling Mulvaney, Vice President, Global Sustainability and Access to Healthcare at AstraZeneca

Normally, hypertension is screened by a blood pressure measuring device attached to a cuff wrapped on upper left arm. On the other hand, diabetes is screened by taking blood sample, a process which is invasive, more costly and requires more turnaround time for results. However, through this equipment, screening of high blood pressure and diabetes will be done by screening of an individual’s retina for both diseases simultaneously.

The image will then be processed through an online database stored in a cloud and compared to millions of other retinal scans by Machine Learning and Artificial Intelligence (AI) in order to predict whether the individual has any of the conditions.

Moreover, the process is fast, non-invasive and potentially cost-effective especially for large scale population screenings in the long run.

Speaking on behalf of Cabinet Minister for Health, Dr. Rashid Aman Chief Administrative Secretary, Health said, “Successful health care delivery requires effective medical devices as tools for prevention, diagnosis, treatment, and rehabilitation. As expected, the use and evaluation of this digital Non Mydriatic camera (it does not require that the patient’s pupil be dilated before use) to predict medical changes associated with enhanced disease, and especially seen in diabetic and hypertensive patients, will expand innovation in early detection of systemic complications manifesting as eye disease thus effectively controlling an important health problem.”

Dr. Rashid Aman Chief Administrative Secretary, Health

A single retinal scan will be able to identify the risk or presence of complications thus strengthen the local research capacity and improve the screening for NCDs in the country. Other than hypertension and diabetes, the digital Non Mydriatic camera will also be able to predict risks like eye conditions.

According to Prof. Sylvester Kimaiyo, Executive Director for Academic Model Providing Access to Healthcare(AMPATH), the machine will predict whether an individual has diabetes complications or not by looking at the blood vessels of the eye and its background.

Normally, eyes damaged by diabetes will either have thick blood vessels, broken blood vessels or have exudates (droppings on the eye that can make someone blind). Therefore, experts will use this knowledge to predict whether or not an individual is having eye complications and is likely to become blind, he said.

The equipment will be distributed across Kenya Medical Research Institute (KEMRI), Kenyatta National Hospital(KNH), the University of Nairobi (UON) and Aga Khan University Hospital (AKUHN).