scholarly journals Pan-organ model integration of metabolic and regulatory processes in type 1 diabetes

2019 ◽  
Author(s):  
Marouen Ben Guebila ◽  
Ines Thiele
Keyword(s):  
Type 1 Diabetes ◽  
Systemic Disease ◽  
Coarse Grained ◽  
Whole Body ◽  
Correct Prediction ◽  
Long Term Effects ◽  
Modeling Framework ◽  
Human Pathology ◽  
The Impact

SummaryType 1 diabetes mellitus (T1D) is a systemic disease triggered by a local autoimmune inflammatory reaction in insulin-producing cells that disrupts the glucose-insulin-glucagon system and induces organ-wide, long-term effects on glycolytic and nonglycolytic processes. Mathematical modeling of the whole-body regulatory bihormonal system has helped to identify intervention points to ensure better control of T1D but was limited to a coarse-grained representation of metabolism. To extend the depiction of T1D, we developed a whole-body model using a novel integrative modeling framework that links organ-specific regulation and metabolism. The developed framework allowed the correct prediction of disrupted metabolic processes in T1D, highlighted pathophysiological processes common with neurodegenerative disorders, and suggested calcium channel blockers as potential adjuvants for diabetes control. Additionally, the model predicted the occurrence of insulin-dependent rewiring of interorgan crosstalk. Moreover, a simulation of a population of virtual patients allowed an assessment of the impact of inter and intraindividual variability on insulin treatment and the implications for clinical outcomes. In particular, GLUT4 was suggested as a potential pharmacogenomic regulator of intraindividual insulin efficacy. Taken together, the organ-resolved, dynamic model may pave the way for a better understanding of human pathology and model-based design of precise allopathic strategies.

The impact of real-time continuous glucose monitoring on metabolic control in children with type 1 diabetes

2020 ◽  
Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Real Time ◽  
Metabolic Control ◽  
Continuous Glucose Monitoring ◽  
Glucose Monitoring ◽  
The Impact

Model estimates of the results of diabetes patients using modern glucometers with tri-color technology for displaying test results

2019 ◽  
pp. 81-89
Author(s):  
Larisa Dmitrievna Popovich ◽  
Svetlana Valentinovna Svetlichnaya ◽  
Aleksandr Alekseevich Moiseev
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 1 Diabetes ◽  
Economic Benefits ◽  
Test Results ◽  
Self Monitoring ◽  
Patients With Diabetes ◽  
The Impact

Diabetes – a disease in which the effect of the treatment substantially depends on the patient. Known a study showed that the use of glucometers with the technology of three-color display of test results facilitates self-monitoring of blood sugar and leads to a decrease in glycated hemoglobin (HbAlc). Purpose of the study: to modeling the impact of using of a glucometer with a color-coded display on the clinical outcomes of diabetes mellitus and calculating, the potential economic benefits of reducing the hospitalization rate of patients with diabetes. Material and methods. Based on data from two studies (O. Schnell et al. and M. Baxter et al.) simulation of the reduction in the number of complications with the use of a glucometer with a color indication. In a study by O. Schnell et al. a decrease of HbA1c by 0.69 percent is shown when using the considered type of glucometers, which was the basis of the model. Results. In the model, the use of a glucometer with a color-coded display for type 1 diabetes led to a decrease in the total number of complications by 9.2 thousand over 5 years per a cohort of 40 thousand patients with different initial levels of HbA1c. In a cohort of 40 thousand patients with type 2 diabetes, the simulated number of prevented complications was 1.7 thousand over 5 years. When extrapolating these data to all patients with diabetes included in the federal register of diabetes mellitus (FRD), the number of prevented complications was 55.4 thousand cases for type 1 diabetes and 67.1 thousand cases for type 2 diabetes. The possible economic effect from the use of the device by all patients with a diagnosis of diabetes, which are included in the FRD, estimated at 1.5 billion rubles for a cohort of patients with type 1 diabetes and 5.3 billion rubles for patients with type 2 diabetes. Conclusion. Improving the effectiveness of self-monitoring, which is the result of the use of glucometers with color indicators, can potentially significantly reduce the incidence of complications in diabetes and thereby provide significant economic benefits to society.

Care of children with type 1 diabetes mellitus in school – An interventional study

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Umamaheswari Gurunathan ◽  
Hemchand Krishna Prasad ◽  
Sherline White ◽  
Bala Prasanna ◽  
Thangavelu Sangaralingam
Keyword(s):  
Type 1 Diabetes ◽  
Education Program ◽  
School Teachers ◽  
Post Intervention ◽  
Community Based ◽  
Structured Education ◽  
Type 1 Dm ◽  
The Impact ◽  
Determining Factor

AbstractObjectivesPaucity of data from India on care of children with Type 1 diabetes in schools. Aims: To study assess the knowledge, attitude, practices and fear of Type 1 diabetes in school teachers and to assess the impact of an educational model on the fear of teachers and care of children in Type 1 DM at school hours.MethodsA community based study, involving school teachers and the intervention being educating them about diabetes conducted. Data pertaining to basic demography, attitude of teachers towards diabetic children, Hypoglycemia fear factor survey- parent version with worries domain and preparedness of school was collected. An education program was conducted on diabetes care in children. Immediately and after three months, the proforma details and HFSP-W scores reassessed.ResultsForty two teachers (mean age: 38.7±5.4; M:F ratio 2:40) participated in the study. Post intervention, a higher willingness to have the diabetic child in class (100 vs. 57.1%; p>0.05), better support in daily care (100 vs. 92%; p>0.05), participation in sports activities (100 vs. 7.1%; p<0.05) observed. HFSP-W scores were 38.8±4.5 (pre-intervention), 22.5±4.3 (immediate post intervention) and 29.5±3.2 (at 3months) (p<0.05). To study the determinants of improvement in HFSP-W a regression analysis was performed: presence of glucometer the most likely determining factor (T=1.999, p=0.05).ConclusionThere is a significant element of fear in the minds of teachers towards hypoglycemia which improves with a structured education program.

scholarly journals Impact of Carbohydrate Counting Error on Glycemic Control in Open-Loop Management of Type 1 Diabetes: Quantitative Assessment Through an in silico Trial

2021 ◽  
pp. 193229682110123
Author(s):  
Chiara Roversi ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Andrea Facchinetti ◽  
Pratik Choudhary ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
In Silico ◽  
Open Loop ◽  
Random Errors ◽  
Linear Regression Models ◽  
Reference Case ◽  
Counting Error ◽  
The Impact

Background: In the management of type 1 diabetes (T1D), systematic and random errors in carb-counting can have an adverse effect on glycemic control. In this study, we performed an in silico trial aiming at quantifying the impact of different levels of carb-counting error on glycemic control. Methods: The T1D patient decision simulator was used to simulate 7-day glycemic profiles of 100 adults using open-loop therapy. The simulation was repeated for different values of systematic and random carb-counting errors, generated with Gaussian distribution varying the error mean from -10% to +10% and standard deviation (SD) from 0% to 50%. The effect of the error was evaluated by computing the difference of time inside (∆TIR), above (∆TAR) and below (∆TBR) the target glycemic range (70-180mg/dl) compared to the reference case, that is, absence of error. Finally, 3 linear regression models were developed to mathematically describe how error mean and SD variations result in ∆TIR, ∆TAR, and ∆TBR changes. Results: Random errors globally deteriorate the glycemic control; systematic underestimations lead to, on average, up to 5.2% more TAR than the reference case, while systematic overestimation results in up to 0.8% more TBR. The different time in range metrics were linearly related with error mean and SD ( R2>0.95), with slopes of [Formula: see text], [Formula: see text] for ∆TIR, [Formula: see text], [Formula: see text] for ∆TAR, and [Formula: see text], [Formula: see text] for ∆TBR. Conclusions: The quantification of carb-counting error impact performed in this work may be useful understanding causes of glycemic variability and the impact of possible therapy adjustments or behavior changes in different glucose metrics.

scholarly journals Anxiety, depression, and glycemic control during Covid-19 pandemic in youths with type 1 diabetes

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Maria Cusinato ◽  
Mariangela Martino ◽  
Alex Sartori ◽  
Claudia Gabrielli ◽  
Laura Tassara ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Psychological Impact ◽  
Glucose Monitoring ◽  
Severe Hypoglycemia ◽  
Well Being ◽  
Glucose Variability ◽  
Threshold Score ◽  
The Impact

Abstract Objectives Our study aims to assess the impact of lockdown during the coronavirus disease 2019 pandemic on glycemic control and psychological well-being in youths with type 1 diabetes. Methods We compared glycemic metrics during lockdown with the same period of 2019. The psychological impact was evaluated with the Test of Anxiety and Depression. Results We analyzed metrics of 117 adolescents (87% on Multiple Daily Injections and 100% were flash glucose monitoring/continuous glucose monitoring users). During the lockdown, we observed an increase of the percentage of time in range (TIR) (p<0.001), with a significant reduction of time in moderate (p=0.002), and severe hypoglycemia (p=0.001), as well as the percentage of time in hyperglycemia (p<0.001). Glucose variability did not differ (p=0.863). The glucose management indicator was lower (p=0.001). 7% of youths reached the threshold-score (≥115) for anxiety and 16% for depression. A higher score was associated with lower TIR [p=0.028, p=0.012]. Conclusions Glycemic control improved during the first lockdown period with respect to the previous year. Symptoms of depression and anxiety were associated with worse glycemic control; future researches are necessary to establish if this improvement is transient and if psychological difficulties will increase during the prolonged pandemic situation.

scholarly journals Glycated haemoglobin variations in paediatric type 1 diabetes: the impact of season, gender and age

2013 ◽  
Vol 103 (4) ◽  
pp. 398-403 ◽  
Author(s):  
L Hanberger ◽  
K Åkesson ◽  
U Samuelsson
Keyword(s):  
Type 1 Diabetes ◽  
Glycated Haemoglobin ◽  
Gender And Age ◽  
The Impact
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