DIABSAT Telemedicine Itinerant Screening of Chronic Complications of Diabetes Using a Satellite

The Role of Telemedicine, In-Home Testing and Artificial Intelligence to Alleviate an Increasingly Burdened Healthcare System: Diabetic Retinopathy

In the presence of the ever-increasing incidence of diabetes mellitus (DM), the prevalence of diabetic eye disease (DED) is also growing. Despite many improvements in diabetic care, DM remains a leading cause of visual impairment in working-age patients. So far, prevention has been the best way to protect vision. The sooner we diagnose DED, the more effective the treatment is. Thus, diabetic retinopathy (DR) screening, especially with imaging techniques, is a method of choice for vision protection. To alleviate the burden of diabetic patients who need ophthalmic care, telemedicine and in-home testing are used, supported by artificial intelligence (AI) algorithms. This is why we decided to evaluate current image teleophthalmology methods used for DR screening. We searched the PubMed platform for papers published over the last 5 years (2015–2020) using the following key words: telemedicine in diabetic retinopathy screening, diabetic retinopathy screening, automated diabetic retinopathy screening, artificial intelligence in diabetic retinopathy screening, smartphone diabetic retinopathy testing. We have included 118 original articles meeting the above criteria, discussing imaging diabetic retinopathy screening methods. We have found that fundus cameras, stable or mobile, are most commonly used for retinal photography, with portable fundus cameras also relatively common. Other possibilities involve the use of ultra-wide-field (UWF) imaging and even optical coherence tomography (OCT) devices for DR screening. Also, the role of smartphones is increasingly recognized in the field. Retinal fundus images are assessed by humans instantly or remotely, while AI algorithms seem to be useful tools facilitating retinal image assessment. The common use of smartphones and availability of relatively cheap, easy-to-use adapters for retinal photographs augmented by AI algorithms make it possible for eye fundus photographs to be taken by non-specialists and in non-medical setting. This opens the way for in-home testing conducted on a much larger scale in the future. In conclusion, based on current DR screening techniques, we can suggest that the future practice of eye care specialists will be widely supported by AI algorithms, and this way will be more effective.

Diabetes in French Guiana, adapting national standards of therapeutic education and care to the amazonian challenge

French Guiana is a territory located more than 7000 km from France. It is also the largest French territory, with almost 84000 km² and 90% of it is covered by forest. Some municipalities are isolated due to the scarcity of transportation and the poor road infrastructure. The population is extremely diverse ethnically and culturally, and includes more than thirty ethnic groups. Immigration is high because it is one of the richest countries in the area bordering northern Brazil, Suriname, Guyana, and as a result of socio-economic crises in some other countries such as Haiti, and it has permeable natural borders. Diabetes and obesity, are emerging issues, with double the prevalence of Mainland France, whereas infectious diseases, such as HIV, take second place. Therapeutic and educational management are challenging because they require the adaptation of tools and treatments to the mul-ticulturalism and precariousness often encountered in these populations. The French and European recommendations are unsuited to the needs of the territory and must take into account the epidemiological, sociological and cultural parameters of these populations in order to provide appropriate and graded management of diabetes in the French Amazon.