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Type 1 diabetes requires the patient to be very involved in the treatment process, especially in terms of proper self-control. The new method of non-invasive glycemic control by scanning is an attractive alternative for patients requiring multiple measurements due to the high dynamics of glycemic changes. The aim of the study was to evaluate the usefulness of Flash FreeStyle Libre in glycemic control in children during summer camp on the basis of the participants' completed questionnaire and on the basis of the assessment o the suitability of the system performed by medical staff based on a comparative analysis: glycemia by sensor and glucometer. Material and Methods. A study using the new Flash FreeStyle Libre glycemic control system was conducted at a seaside summer camp for children with diabetes at the seaside. The study included 75 children (32 boys and 43 girls), in mean 13.4 (SD 4.6) years old, with an average duration of diabetes of 6.5 (SD 4.5) years and mean HbA 1 c of 7.81% (SD 2.05). All camp participants were provided with Libre sensors, however, routine glucose control measurements with therapeutic decisions was made using traditional glucose meters. On the last day of the camp, after the removal of the sensors, a satisfaction survey was conducted to assess with a new self-monitoring method and a comparative analysis of the glucose results from the sensor with the personal glucose meters -MARD, MAD, and clinical errors on the Clarke Error Grid were calculated. Results. In the Libre user's survey, wearing comfort and ease of installation were described as very good / good by 86% and 94% of the respondends, respectively. Ease of reading blood glucose by scan was positively evaluated by 92% of the respondents, 95% of the subjects did not report any side effects. The sensor remained intact for 14 days in 46 children (62%), which value was the basis for the statistical calculations. Comparative analysis of glucose results obtained from Libre measurements performed with glucose meters (3143 measurements) showed a relatively good MARD index -18.22% on average, with a large individual variation (6.36-29.51%). Clarke Error Grid showed that 75.2% (2309) of the results were in Zone A (Acceptable Errors) and 95.81% (3012) in Zone A and B (Non-Negative Errors). Conclusion. Libre user's satisfaction survey revealed that most of the respondents rated the cooperation with Flash FreeStyle Libre positively. The relatively good results of Libre in comparison with glucose meters have confirmed the usefulness of this method of monitoring glucose in summer camps for children with diabetes.

Historically, game theory has been mainly used to define and analyze conflicts. 11,15,[34][35][36][37][38][39][40] We propose the rough set and Boolean reasoning methods to specify conflicts, and transform the conflict analysis problem and the conflict-resolving problem into the Boolean-reasoning problem.5,43 Our model is an extension of that proposed by Pawlak. [27][28][29] We discuss some basic conflict problems expressible in this new model, as well as algorithms for solving them.

BackgroundIn spite of numerous research efforts on supporting the therapy of diabetes mellitus, the subject still involves challenges and creates active interest among researchers. In this paper, a decision support tool is presented for setting insulin therapy in new-onset type 1 diabetes.MethodsThe concept of differential sequential patterns (DSPs) is introduced with the aim of representing deviations in the patient’s blood glucose level (BGL) and the amount of insulin injections administered. The decision support tool is created using data mining algorithms for discovering sequential patterns.ResultsBy using the DSPs, it is possible to support the physician’s decisionmaking concerning changing the treatment (i.e., whether to increase or decrease the insulin dosage). The other contributions of the paper are an algorithm for generating DSPs and a new method for evaluating nocturnal glycaemia. The proposed qualitative evaluation of nocturnal glycaemia improves the generalization capabilities of the DSPs.ConclusionsThe usefulness of the proposed approach was evident in the results of experiments in which juvenile diabetic patients actual data were used. It was confirmed that the proposed DSPs can be used to guide the therapy of numerous juvenile patients with type 1 diabetes.

The disease of diabetes mellitus has spread in recent years across the world, and has thus become an even more important medical problem. Despite numerous solutions already proposed, the problem of management of glucose concentration in the blood of a diabetic patient still remains as a challenge and raises interest among researchers. The data-driven models of glucose-insulin interaction are one of the recent directions of research. In particular, a data-driven model can be constructed using the idea of sequential patterns as the knowledge representation method. In this paper a new hierarchical, template-based approach for mining sequential patterns is proposed. The paper proposes also to use functional abstractions for the representation and mining of clinical data. Due to the experts knowledge involved in the construction of functional abstractions and sequential templates, the discovered underlying template-based patters can be easily interpreted by physicians and are able to provide recommendations of medical therapy. The proposed methodology was validated by experiments using real clinical data of juvenile diabetes.