scholarly journals Customizing the Types of Technologies Used by Patients With Type 1 Diabetes Mellitus for Diabetes Treatment: Case Series on Patient Experience (Preprint)

2018 ◽  
Author(s):  
Anna Holubová ◽  
Martina Vlasáková ◽  
Jan Mužík ◽  
Jan Brož
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Diabetes Management ◽  
Case Series ◽  
Diabetes Control ◽  
Self Management ◽  
Telemedicine System ◽  
Specific Patient

BACKGROUND Despite the fact there are many wearable and mobile medical devices that enable patients to better self-manage their diabetes, not many patients are aware of all the options they have. In addition, there are those who are not fully satisfied with the devices they use, and those who often do not use them effectively. OBJECTIVE The study aimed to propose possible changes to the combination of devices used by 6 specific patients for diabetes self-management. We assessed the suitability of selected technical devices for diabetes control. METHODS Data of 6 patients (3 men and 3 women) with type 1 diabetes mellitus, who had been using the Diani telemedicine system for at least 3 months, were analyzed. The suitability of selected technical devices for diabetes control was ascertained using the data obtained via the Diani telemedicine system, as well as the patients’ subjective feelings and statements, their everyday life habits, and self-management of diabetes. Informed consent was signed and obtained from each of the patients included. RESULTS Each of the presented case studies describes how a given patient handled the system and its specific components based on his or her lifestyle, level of education, habits related to diabetes management, personality type, and other factors. At the conclusion of each case study, the best composition of devices for patients with similar personal descriptions was suggested. CONCLUSIONS We believe this study can provide relevant guidance on how to help particular patients choose the technology that is best suited for their needs, based on the specific patient information we are able to obtain from them. Furthermore, clinicians or educators should be aware of available technologies a given patient can choose from. In addition, there is a substantial need for proper patient education in order for them to effectively use devices for diabetes self-management.

scholarly journals The Effect of HbA1c Variability as a Risk Measure for Microangiopathy in Type 1 Diabetes Mellitus

Diagnostics ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1151
Author(s):  
Pedro Romero-Aroca ◽  
Raul Navarro-Gil ◽  
Albert Feliu ◽  
Aida Valls ◽  
Antonio Moreno ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Diabetic Retinopathy ◽  
Type 1 Diabetes Mellitus ◽  
Risk Measure ◽  
Case Series ◽  
Multivariate Statistical ◽  
Case Series Study ◽  
Prospective Case Series

Background: To measure the relationship between variability in HbA1c and microalbuminuria (MA) and diabetic retinopathy (DR) in the long term. Methods: A prospective case-series study, was conducted on 366 Type 1 Diabetes Mellitus patients with normoalbuminuria and without diabetic retinopathy at inclusion. The cohort was followed for a period of 12 years. The Cox survival analysis was used for the multivariate statistical study. The effect of variability in microangiopathy (retinopathy and nephropathy) was evaluated by calculating the standard deviation of HbA1c (SD-HbA1c), the coefficient of variation of HbA1c (CV-HbA1c), average real variability (ARV-HbA1c) and variability irrespective of the mean (VIM-HbA1c) adjusted for the other known variables. Results: A total of 106 patients developed diabetic retinopathy (29%) and 73 microalbuminuria (19.9%). Overt diabetic nephropathy, by our definition, affected only five patients (1.36%). Statistical results show that the current age, mean HbA1c, SD-HbA1c and ARV-HbA1c are significant in the development of diabetic retinopathy. Microalbuminuria was significant for current age, mean HbA1c, CV-HbA1c and ARV-HbA1c. Conclusions: By measuring the variability in HbA1c, we can use SD-HbA1c and ARV-HbA1c as possible targets for judging which patients are at risk of developing DR and MA, and CV-HbA1c as the target for severe DR.

Agent-based modeling for the self-management of chronic diseases: An exploratory study

SIMULATION ◽  
2017 ◽  
Vol 93 (9) ◽  
pp. 781-793 ◽  
Author(s):  
Sara Montagna ◽  
Andrea Omicini
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Type 1 Diabetes Mellitus ◽  
Chronic Diseases ◽  
Agent Based Modeling ◽  
Self Management ◽  
Agent Based ◽  
Management Interventions ◽  
The Impact

The impact of mobile technologies on healthcare is particularly evident in the case of self-management of chronic diseases, where they can decrease spending and improve life quality of patients. We propose the adoption of agent-based modeling and simulation techniques as built-in tools to dynamically monitor the state of patient health and provide recommendations for self-management. To demonstrate the feasibility of our proposal we focus on Type 1 diabetes mellitus as our case study, and provide simulation results where the dynamic evolution of signal parameters is shown in the case of healthy and Type 1 diabetes mellitus patients, focussing in particular on the beneficial effects that self-management interventions have on plasma glucose values.

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