Boluses in Insulin Therapy

Ziegler, Ralph; Freckmann, Guido; Heinemann, Lutz

doi:10.1177/1932296816653142

Cited by 13 publications

(4 citation statements)

References 66 publications

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“…Another important part of accuracy in insulin pumps is the accurate delivery of meal and correction boluses. Boluses as small as 0.1 U are often used in infants and small children, and therefore accuracy of insulin delivery is of utmost importance . Up to now, no studies have been published regarding this question.…”

Section: Dosing Accuracymentioning

confidence: 99%

Continuous subcutaneous insulin infusion: Special needs for children

Adolfsson

Ziegler²,

Hanås

2017

Pediatr Diabetes

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Continuous subcutaneous insulin infusion (CSII) is a very common therapy for children with type 1 diabetes. Due to physiological differences they have other requirements for their insulin pump than adults. The main difference is the need for very low basal rates. Even though most available insulin pumps reach a high accuracy at usual basal rates, accuracy decreases for lower rates. In addition, the lowest delivered amount at 1 time is limiting the fine tuning of the basal rate as well as the option for temporary basal rates. Alarms in case of occlusions depend on accumulation of a certain amount of insulin in the catheter, and therefore the time until such an alarm is triggered is much longer with lower basal rates. Accordingly, the risk for hyperglycemia developing into diabetic ketoacidosis increases. The availability of bolus advisors facilitates the calculation of meal and correction boluses for children and their parents. However, there are some differences between the calculators, and the settings that the calculation is based on are very important. Better connectivity, for example with a system for continuous glucose monitoring, might help to further increase safety in the use of CSII in children. When selecting an insulin pump for a child, the features and characteristics of available pumps should be properly compared to ensure an effective and safe therapy.

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Section: Dosing Accuracymentioning

confidence: 99%

Continuous subcutaneous insulin infusion: Special needs for children

Adolfsson

Ziegler²,

Hanås

2017

Pediatr Diabetes

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“…Finally, with the aim of reducing post-prandial peaks, a super bolus strategy has been introduced. 27 With a super bolus, some of the basal insulin delivery is stopped or partially reduced and delivered instead as additional bolus insulin on top of a normal meal or correction bolus. In this case, basal insulin delivery is suspended for 60 minutes after an insulin bolus is delivered.…”

Section: Biap Controller Implementationmentioning

confidence: 99%

An In Silico Head-to-Head Comparison of the Do-It-Yourself Artificial Pancreas Loop and Bio-Inspired Artificial Pancreas Control Algorithms

Armiger

Reddy

Oliver

et al. 2021

J Diabetes Sci Technol

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Background: User-developed automated insulin delivery systems, also referred to as do-it-yourself artificial pancreas systems (DIY APS), are in use by people living with type 1 diabetes. In this work, we evaluate, in silico, the DIY APS Loop control algorithm and compare it head-to-head with the bio-inspired artificial pancreas (BiAP) controller for which clinical data are available. Methods: The Python version of the Loop control algorithm called PyLoopKit was employed for evaluation purposes. A Python-MATLAB interface was created to integrate PyLoopKit with the UVa-Padova simulator. Two configurations of BiAP (non-adaptive and adaptive) were evaluated. In addition, the Tandem Basal-IQ predictive low-glucose suspend was used as a baseline algorithm. Two scenarios with different levels of variability were used to challenge the algorithms on the adult (n = 10) and adolescent (n = 10) virtual cohorts of the simulator. Results: Both BiAP and Loop improve, or maintain, glycemic control when compared with Basal-IQ. Under the scenario with lower variability, BiAP and Loop perform relatively similarly. However, BiAP, and in particular its adaptive configuration, outperformed Loop in the scenario with higher variability by increasing the percentage time in glucose target range 70-180 mg/dL (BiAP-Adaptive vs Loop vs Basal-IQ) (adults: 89.9% ± 3.2%* vs 79.5% ± 5.3%* vs 67.9% ± 8.3%; adolescents: 74.6 ± 9.5%* vs 53.0% ± 7.7% vs 55.4% ± 12.0%, where * indicates the significance of P < .05 calculated in sequential order) while maintaining the percentage time below range (adults: 0.89% ± 0.37% vs 1.72% ± 1.26% vs 3.41 ± 1.92%; adolescents: 2.87% ± 2.77% vs 4.90% ± 1.92% vs 4.17% ± 2.74%). Conclusions: Both Loop and BiAP algorithms are safe and improve glycemic control when compared, in silico, with Basal-IQ. However, BiAP appears significantly more robust to real-world challenges by outperforming Loop and Basal-IQ in the more challenging scenario.

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“…Ces personnes croient que les outils technologiques pourraient faciliter ce calcul [39] . En effet, savoir calculer avec précision la quantité de glucides contenus dans un repas et effectuer les calculs mathématiques en prenant compte du ratio insuline : glucides et du facteur de sensibilité à l'insuline (pour corriger une hyperglycémie préprandiale) peut représenter un réel défi [40] . Aussi, des calculateurs (ou « assistants ») de bolus présents dans les pompes à insuline ont pour objectif de faciliter le calcul de la dose d'insuline prandiale à injecter.…”

Section: Technologies Et Traitement Nutritionnel Du Diabèteunclassified