Vércukor-önellenőrzési adatok intelligens értelmezése

Abstract

Self monitoring of blood glucose is the cornerstone of diabetes management. However, the data obtained by self monitoring of blood glucose have rarely been used with the highest advantage. Few physicians routinely download data from memory-equipped glucose meters and analyse these data systematically at the time of patient visits. There is a need for improved methods for the display and analysis of blood glucose data along with a modular approach for identification of clinical problems. The authors present a systematic methodology for the analysis and interpretation of self monitoring blood glucose data in order to assist the management of patients with diabetes. This approach utilizes the followings 1) overall quality of glycemic control; 2) severity and timing of hypoglycemia and hyperglycemia; 3) variability of blood glucose readings; 4) various temporal patterns extracted from recorded data and 5) adequacy of self monitoring blood glucose data. Based on reliable measures of the quality of glycaemic control and glucose variability, a prioritized problem list is derived along with the probable causes of the detected problems. Finally, problems and their interpretation are used to guide clinicians to choose therepeutic actions and/or recommend behaviour change in order to solve the problems that have been identified. Orv. Hetil., 2015, 156(29), 1165–1173.