A comprehensive analysis of diabetic patient data before and during the COVID-19 pandemic - Lessons from the MÉRY diabetes database (MDD).

Aims: Our study examined changes in average blood glucose levels (ABG), measurement frequency (MF), and data uploading (DU) before and during the COVID-19 pandemic in 882-day spans, which were divided into further 20-week intervals to highlight the pandemic's impact.

Methods: T-Tests assessed the statistical significance of blood glucose data from 26,655/20,936 patients and 19.5/16.

How to evaluate over 60 million blood glucose data - The design of the MÉRY Diabetes Database.

Aims: The aim of the article is to describe the method for creating a close to ideal diabetes database. The MÉRY Diabetes Database (MDD) consists of a large quantity of reliable, well-maintained, precise and up-to-date data suited for clinical research with the intention to improve diabetes care in terms of maintaining targeted blood glucose levels, avoiding hypoglycemic episodes and complications and improving patient compliance and quality of life.

Methods: Based on the analysis of the databases found in the literature and the experience of our research team, nine important characteristics were identified as critical to an ideal diabetes database.