Introduction. Modern Diabetes mellitus is dangerous, chronic endocrine disease that originates from the disorder of metabolism, connected primarily with violation of carbohydrate exchange. Providing the necessity of independent self-control of health status of diabetes patients is the urgent problem of present time. The use of information technologies and mobile medicine facilitates enhancing the efficiency of self-control of health status by the patient. The purpose of the paper is to develop a combined information technology to enhance the efficiency of glycemic self-control in case of diabetes at different stages of treatment.

Цель работы-изучение уровня COMP в сыворотке крови больных сахарным диабетом (СД) 1 и 2 типа с артропатией и определение взаимосвязи с функциональными индексами, которые характеризуются клиническими проявлениями поражений суставов у больных сахарным диабетом.

dislike of wearing the device. Thus, sensors are good but expensive, not affordable for everybody and could be uncomfortable. Therefore, the constant search for alternative solutions remains an important challenge. The purpose of the paper is to show the possibility of using hierarchical modeling technology to develop and study glycemic profile prediction algorithm as, to some extent, alternative to continuous monitoring sensors in a context of limited irregular measurements. Results. The program-algorithmic structure for realization of the concept of hierarchical simulation is developed. The possibility of conducting research on models of varying complexity is shown. An algorithm for insulin-glucose tolerance test was synthesized. A procedure for predicting the daily glycemic profile by analytical formulas has been developed, which provides an opportunity to assess the trend of glycemic dynamics as an addition to the irregular glucose measurements with a glucometer. A simulation study, the result of which is the visualization of glycemic profile in a context of expected food intake schedule and compensating insulin doses obtained by the analytical algorithm, was conducted. Conclusions. The proposed hierarchical modeling technology, based on the use of mathematical models of varying complexity, allows to conduct a complex of simulation studies to correct glycemia in diabetes at the preclinical and pre-ambulatory stages. During the simulation of forecasting procedure, configuration discrepancies of the glycemic profile obtained from different models were detected, but they are within the margin of error and reproduce the main trend in the dynamics of glycemia during meals and insulin injections. The calculated bolus doses of insulin are almost identical to those used by insulin-dependent patients. The simplicity of calculations using analytical formulas can be a prerequisite for the implementation of the algorithm in a special-purpose portable autonomous devices or in applications for Android OS.

The aim: Of our work was to study the level of proinflammatory cytokines in patients with diabetic arthropathy and to investigate their possible effect on the development of this complication. Materials and methods: 118 patients were examined, which were divided into groups by type of diabetes, the presence and severity of diabetic arthropathy. The content of IL-1, TNF-α, IL-6 and receptors to S IL-6-R in serum was determined by immunoassay. Results: In patients with diabetic arthropathy, levels of TNF-α (with type 1 diabetes 44.5%, type 2 diabetes 42.9%) and IL-6 (with type 1 diabetes 52.1%, with diabetes 2 types by 64.4%) significantly increased. There is a direct correlation between the severity of joint damage and the level of TNF-α and IL-6. For IL -1, receptors for S IL-6-R have not been detected. Conclusions: The chances of detecting arthropathy with type 1 diabetes with increasing TNF levels increase by 1.7 times, with an increase in IL-6 by 1.5 times. For type 2 diabetes, it is 1.8 and 1.3 times, respectively. Thus, TNF-α and IL-6 may be markers of the presence and progression of arthropathy in patients with diabetes mellitus