In-silico Assessment of Preventive Hypotreatment Efficacy and Development of a Continuous Glucose Monitoring Based Algorithm to Prevent/Mitigate Hypoglycemia in Type 1 Diabetes

Author(s):  
Nunzio Camerlingo ◽  
Martina Vettoretti ◽  
Simone Del Favero ◽  
Giacomo Cappon ◽  
Giovanni Sparacino ◽  
...  
2021 ◽  
pp. 193229682110431
Author(s):  
Giulia Noaro ◽  
Giacomo Cappon ◽  
Giovanni Sparacino ◽  
Federico Boscari ◽  
Daniela Bruttomesso ◽  
...  

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.


Author(s):  
Peris Begoña Pla ◽  
Leví Ana M Ramos ◽  
Vargas Marcos Lahera ◽  
Casieri Raffaele Carraro ◽  
Moreno Nerea Aguirre ◽  
...  

Author(s):  
Ruxandra Calapod Ioana ◽  
Irina Bojoga ◽  
Duta Simona Gabriela ◽  
Ana-Maria Stancu ◽  
Amalia Arhire ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 1179-P ◽  
Author(s):  
THOMAS DANNE ◽  
BERTRAND CARIOU ◽  
JOHN B. BUSE ◽  
SATISH K. GARG ◽  
JULIO ROSENSTOCK ◽  
...  

Diabetes ◽  
2018 ◽  
Vol 67 (Supplement 1) ◽  
pp. 932-P
Author(s):  
LUDI FAN ◽  
COLLEEN GAREY ◽  
JINGWEN LIU ◽  
BETH MITCHELL ◽  
JEOFFREY BISPHAM ◽  
...  

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 955-P
Author(s):  
JESSIE J. WONG ◽  
SUSAN MICHELLE CLAY ◽  
GREGORY P. FORLENZA ◽  
SARAH HANES ◽  
R. PAUL WADWA ◽  
...  

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