An important obstacle in the fight against diabetic retinopathy (DR) is the use of a classification system based on old imaging techniques and insufficient data to accurately predict its evolution. New imaging techniques generate new valuable data, but we lack an adapted classification based on these data. The main objective of the Evaluation Intelligente de la Rétinopathie Diabétique, Intelligent evaluation of DR (EviRed) project is to develop and validate a system assisting the ophthalmologist in decision-making during DR follow-up by improving the prediction of its evolution.

A cohort of up to 5000 patients with diabetes will be recruited from 18 diabetology departments and 14 ophthalmology departments, in public or private hospitals in France and followed for an average of 2 years. Each year, systemic health data as well as ophthalmological data will be collected. Both eyes will be imaged by using different imaging modalities including widefield photography, optical coherence tomography (OCT) and OCT-angiography. The EviRed cohort will be divided into two groups: one group will be randomly selected in each stratum during the inclusion period to be representative of the general diabetic population. Their data will be used for validating the algorithms (validation cohort). The data for the remaining patients (training cohort) will be used to train the algorithms.

The study protocol was approved by the French South-West and Overseas Ethics Committee 4 on 28 August 2020 (CPP2020-07-060b/2020-A01725-34/20.06.16.41433). Prior to the start of the study, each patient will provide a written informed consent documenting his or her agreement to participate in the clinical trial. Results of this research will be disseminated in peer-reviewed publications and conference presentations. The database will also be available for further study or development that could benefit patients.

NCT04624737

Globally, around one-third of the population has at least one long-term health condition that could be affected by the COVID-19 pandemic. Despite the fact that studies have revealed the direct impact of COVID-19 on healthcare provision and utilisation, the impact of the pandemic on the cost of chronic disease treatment and care from a patient perspective was scanty. So, the study aimed to determine the impact of the COVID-19 pandemic on cost of chronic diseases treatment and care at public hospitals in Wallaga zones, Oromia Regional State, Ethiopia, from 1 August to 31 August 2020.

An institutional-based cross-sectional study design was used, and the sample size for the study (n=642) was determined using a single population mean formula. Data were collected using interviews and analysed using SPSS V.25. Descriptive statistics were performed, and the cost of follow-up care before and after the pandemic was compared using a related-samples Wilcoxon signed-rank test, declaring the level of significance of the median cost difference at p

A total of 642 patients were included in the study, of whom 605 (94.2%) responded to the interviews. There was a significant median cost difference (n=593, Z=5.05, p=0.001) between the cost of chronic diseases among follow-up patients during the pandemic and the costs incurred by these patients before the pandemic.

The cost of follow-up care among chronic disease patients during the COVID-19 pandemic was significantly higher compared with before the pandemic era. Therefore, healthcare providers should arrange special fee waiver mechanisms for chronic disease healthcare costs during such types of pandemics and provide the services at proximal health facilities.