scholarly journals The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day

2018 ◽  
Vol 12 (2) ◽  
pp. 273-281 ◽  
Author(s):  
Roberto Visentin ◽  
Enrique Campos-Náñez ◽  
Michele Schiavon ◽  
Dayu Lv ◽  
Martina Vettoretti ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
In Silico ◽  
Artificial Pancreas ◽  
Real Life ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Self Monitoring ◽  
Inhaled Insulin ◽  
Single Meal

Background: A new version of the UVA/Padova Type 1 Diabetes (T1D) Simulator is presented which provides a more realistic testing scenario. The upgrades to the previous simulator, which was accepted by the Food and Drug Administration in 2013, are described. Method: Intraday variability of insulin sensitivity (SI) has been modeled, based on clinical T1D data, accounting for both intra- and intersubject variability of daily SI. Thus, time-varying distributions of both subject’s basal insulin infusion and insulin-to-carbohydrate ratio were calculated and made available to the user. A model of “dawn” phenomenon based on clinical T1D data has been also included. Moreover, the model of subcutaneous insulin delivery has been updated with a recently developed model of commercially available fast-acting insulin analogs. Models of both intradermal and inhaled insulin pharmacokinetics have been included. Finally, new models of error affecting continuous glucose monitoring and self-monitoring of blood glucose devices have been added. Results: One hundred in silico adults, adolescent, and children have been generated according to the above modifications. The new simulator reproduces the intraday glucose variability observed in clinical data, also describing the nocturnal glucose increase, and the simulated insulin profiles reflect real life data. Conclusions: The new modifications introduced in the T1D simulator allow to extend its domain of validity from “single-meal” to “single-day” scenarios, thus enabling a more realistic framework for in silico testing of advanced diabetes technologies including glucose sensors, new insulin molecules and artificial pancreas.

scholarly journals In Silico Assessment of Literature Insulin Bolus Calculation Methods Accounting for Glucose Rate of Change

2018 ◽  
Vol 13 (1) ◽  
pp. 103-110 ◽  
Author(s):  
Giacomo Cappon ◽  
Francesca Marturano ◽  
Martina Vettoretti ◽  
Andrea Facchinetti ◽  
Giovanni Sparacino
Keyword(s):  
Blood Glucose ◽  
In Silico ◽  
Blood Glucose Concentration ◽  
Risk Index ◽  
Glucose Monitoring ◽  
Rate Of Change ◽  
Self Monitoring ◽  
Single Meal ◽  
Ideal Framework

Background: The standard formula (SF) used in bolus calculators (BCs) determines meal insulin bolus using “static” measurement of blood glucose concentration (BG) obtained by self-monitoring of blood glucose (SMBG) fingerprick device. Some methods have been proposed to improve efficacy of SF using “dynamic” information provided by continuous glucose monitoring (CGM), and, in particular, glucose rate of change (ROC). This article compares, in silico and in an ideal framework limiting the exposition to possibly confounding factors (such as CGM noise), the performance of three popular techniques devised for such a scope, that is, the methods of Buckingham et al (BU), Scheiner (SC), and Pettus and Edelman (PE). Method: Using the UVa/Padova Type 1 diabetes simulator we generated data of 100 virtual subjects in noise-free, single-meal scenarios having different preprandial BG and ROC values. Meal insulin bolus was computed using SF, BU, SC, and PE. Performance was assessed with the blood glucose risk index (BGRI) on the 9 hours after meal. Results: On average, BU, SC, and PE improve BGRI compared to SF. When BG is rapidly decreasing, PE obtains the best performance. In the other ROC scenarios, none of the considered methods prevails in all the preprandial BG conditions tested. Conclusion: Our study showed that, at least in the considered ideal framework, none of the methods to correct SF according to ROC is globally better than the others. Critical analysis of the results also suggests that further investigations are needed to develop more effective formulas to account for ROC information in BCs.

scholarly journals Artificial Pancreas Systems and Physical Activity in Patients with Type 1 Diabetes: Challenges, Adopted Approaches, and Future Perspectives

2019 ◽  
Vol 13 (6) ◽  
pp. 1077-1090 ◽  
Author(s):  
Sémah Tagougui ◽  
Nadine Taleb ◽  
Joséphine Molvau ◽  
Élisabeth Nguyen ◽  
Marie Raffray ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 1 Diabetes ◽  
Healthcare Professionals ◽  
Therapeutic Option ◽  
Artificial Pancreas ◽  
Glucose Monitoring ◽  
Glucose Variability ◽  
Delivery Methods ◽  
Current State

Physical activity is important for patients living with type 1 diabetes (T1D) but limited by the challenges associated with physical activity induced glucose variability. Optimizing glycemic control without increasing the risk of hypoglycemia is still a hurdle despite many advances in insulin formulations, delivery methods, and continuous glucose monitoring systems. In this respect, the artificial pancreas (AP) system is a promising therapeutic option for a safer practice of physical activity in the context of T1D. It is important that healthcare professionals as well as patients acquire the necessary knowledge about how the AP system works, its limits, and how glucose control is regulated during physical activity. This review aims to examine the current state of knowledge on exercise-related glucose variations especially hypoglycemic risk in T1D and to discuss their effects on the use and development of AP systems. Though effective and highly promising, these systems warrant further research for an optimized use around exercise.

Methods for Insulin Bolus Adjustment Based on the Continuous Glucose Monitoring Trend Arrows in Type 1 Diabetes: Performance and Safety Assessment in an In Silico Clinical Trial

2021 ◽  
pp. 193229682110431
Author(s):  
Giulia Noaro ◽  
Giacomo Cappon ◽  
Giovanni Sparacino ◽  
Federico Boscari ◽  
Daniela Bruttomesso ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
In Silico ◽  
Safety Assessment ◽  
Glucose Monitoring ◽  
Postprandial Glucose ◽  
Rate Of Change ◽  
The Other ◽  
Single Meal

Background: Providing real-time magnitude and direction of glucose rate-of-change (ROC) via trend arrows represents one of the major strengths of continuous glucose monitoring (CGM) sensors in managing type 1 diabetes (T1D). Several literature methods were proposed to adjust the standard formula (SF) used for insulin bolus calculation by accounting for glucose ROC, but each of them provides different suggestions, making it difficult to understand which should be applied in practice. This work aims at performing an extensive in-silico assessment of their performance and safety. Methods: The methods of Buckingham (BU), Scheiner (SC), Pettus/Edelman (PE), Klonoff/Kerr (KL), Aleppo/Laffel (AL), Ziegler (ZI), and Bruttomesso (BR) were evaluated using the UVa/Padova T1D simulator, in single-meal scenarios, where ROC and glucose at mealtime varied between [-2,+2] mg/dL/min and [80,200] mg/dL, respectively. Efficacy of postprandial glucose control was quantitatively assessed by time in, above and below range (TIR, TAR, and TBR, respectively). Results: For negative ROCs, all methods proved to increase TIR and decrease TAR and TBR vs SF, with KL, PE, and BR being the most effective. For positive ROCs, a general worsening of the performances is present, only BR improved the glycemic control when mealtime glucose was close to hypoglycemia, while SC resulted the safest in the other conditions. Conclusions: Insulin bolus adjustment methods are effective for negative ROCs, but they generally appear to overdose for positive ROCs, calling for safer strategies in such a scenario. These results can be useful in outlining guidelines to identify which adjustment to apply based on the mealtime condition.

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 Continuous glucose monitoring use and glucose variability in pre-school children with type 1 diabetes

2019 ◽  
Vol 147 ◽  
pp. 76-80 ◽  
Author(s):  
Klemen Dovc ◽  
Kevin Cargnelutti ◽  
Anze Sturm ◽  
Julij Selb ◽  
Natasa Bratina ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Continuous Glucose Monitoring ◽  
School Children ◽  
Glucose Monitoring ◽  
Glucose Variability

Diabeloop DBLG1 Closed-Loop System Enables Patients With Type 1 Diabetes to Significantly Improve Their Glycemic Control in Real-Life Situations Without Serious Adverse Events: 6-Month Follow-up

2021 ◽  
Author(s):  
Coralie Amadou ◽  
Sylvia Franc ◽  
Pierre-Yves Benhamou ◽  
Sandrine Lablanche ◽  
Erik Huneker ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Adverse Events ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Real Life ◽  
Serious Adverse Events ◽  
Life Conditions ◽  
Time In Range

<b>OBJECTIVE </b> <p>To analyze safety and efficacy of the DBLG1 hybrid closed-loop artificial pancreas system in patients with Type 1 Diabetes in real life conditions. </p> <p> </p> <p><b>METHODS</b></p> <p>Following a one-week run-in period with usual pump, 25 patients were provided with the commercial DBLG1 system. We present the results of Time-in-Range and HbA1c over a 6-month period.</p> <p><b> </b></p> <p><b>RESULTS</b></p> <p>The mean (SD;range) age of patients was 43 years (13.8; 25-72). At baseline, mean HbA1c and TIR 70-180mg/dL were respectively 7.9% (0.93; 5.6- 8.5) [63mmol/mol (10; 38-69)] and 53% (16.4;21-85). One patient stopped using the system after 2 months. At 6-month, mean HbA1c decreased to 7.1% [54mmol/mol] (p<0.001) and TIR 70-180mg/dL increased to 69.7% (p<0.0001). TIR<70mg/dL decreased from 2.4 to 1.3% (p=0.03). TIR<54mg/dL decreased from 0.32 to 0.24% (p=0.42). No serious adverse event was reported during the study. </p> <p> </p> <p><b>CONCLUSION</b></p> <p>The DBLG1 System confirms its ability to significantly improve glycemic control in real life conditions, without serious adverse events. </p>

Frequency of flash glucose monitoring readings, hemoglobin A1c and time in range: a real life study in adults with type 1 diabetes

2020 ◽  
Vol 57 (11) ◽  
pp. 1395-1397 ◽  
Author(s):  
Andrea Laurenzi ◽  
Amelia Caretto ◽  
Mariluce Barrasso ◽  
Andrea Mario Bolla ◽  
Nicoletta Dozio ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Hemoglobin A1c ◽  
Real Life ◽  
Glucose Monitoring ◽  
Flash Glucose Monitoring ◽  
Life Study ◽  
Time In Range ◽  
Real Life Study

scholarly journals Glucagon sensitivity and clearance in type 1 diabetes: insights from in vivo and in silico experiments

2015 ◽  
Vol 309 (5) ◽  
pp. E474-E486 ◽  
Author(s):  
Ling Hinshaw ◽  
Ashwini Mallad ◽  
Chiara Dalla Man ◽  
Rita Basu ◽  
Claudio Cobelli ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
In Silico ◽  
Artificial Pancreas ◽  
Glucose Production ◽  
Endogenous Glucose Production ◽  
Action Model ◽  
The Difference ◽  
Hormone Control

Glucagon use in artificial pancreas for type 1 diabetes (T1D) is being explored for prevention and rescue from hypoglycemia. However, the relationship between glucagon stimulation of endogenous glucose production (EGP) viz., hepatic glucagon sensitivity, and prevailing glucose concentrations has not been examined. To test the hypothesis that glucagon sensitivity is increased at hypoglycemia vs. euglycemia, we studied 29 subjects with T1D randomized to a hypoglycemia or euglycemia clamp. Each subject was studied at three glucagon doses at euglycemia or hypoglycemia, with EGP measured by isotope dilution technique. The peak EGP increments and the integrated EGP response increased with increasing glucagon dose during euglycemia and hypoglycemia. However, the difference in dose response based on glycemia was not significant despite higher catecholamine concentrations in the hypoglycemia group. Knowledge of glucagon's effects on EGP was used to develop an in silico glucagon action model. The model-derived output fitted the obtained data at both euglycemia and hypoglycemia for all glucagon doses tested. Glucagon clearance did not differ between glucagon doses studied in both groups. Therefore, the glucagon controller of a dual hormone control system may not need to adjust glucagon sensitivity, and hence glucagon dosing, based on glucose concentrations during euglycemia and hypoglycemia.

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