Diurnal variation of carbohydrate insulin ratio in adult type 1 diabetic patients treated with continuous subcutaneous insulin infusion

Nakamura, Tomoaki; Hirota, Yushi; Hashimoto, Naoko; Matsuda, Tomokazu; Takabe, Michinori; Sakaguchi, Kazuhiko; Ogawa, Wataru; Seino, Susumu

doi:10.1111/jdi.12132

Cited by 17 publications

(12 citation statements)

References 19 publications

(32 reference statements)

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“…In this study, the total basal dose was approximately 35% (35.9% and 34.6% for IGlar and IDeg, respectively) of the total daily dose at the end of each treatment period. This percentage was lower than that previously reported for white individuals with type 1 diabetes, but was similar to those reported for Japanese patients with type 1 diabetes [ 18 , 19 ].…”

Section: Discussionsupporting

confidence: 83%

Effects of insulin degludec and insulin glargine on day-to-day fasting plasma glucose variability in individuals with type 1 diabetes: a multicentre, randomised, crossover study

Nakamura

Sakaguchi

et al. 2015

Diabetologia

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Aims/hypothesisWe compared the effects of insulin degludec (IDeg; Des(B30)LysB29(γ-Glu Nε-hexadecandioyl) human insulin) and insulin glargine (IGlar; A21Gly,B31Arg,B32Arg human insulin) on the day-to-day variability of fasting plasma glucose (FPG) levels in individuals with type 1 diabetes treated with basal-bolus insulin injections.MethodsThe effects of basal-bolus insulin therapy for 4 weeks with either IDeg or IGlar as the basal insulin in adult C-peptide-negative outpatients with type 1 diabetes were investigated in an open-label, multicentre, randomised, crossover trial. Randomisation was conducted using a centralised allocation process. The primary endpoints were the SD and CV of FPG during the final week of each treatment period. Secondary endpoints included serum glycoalbumin level, daily dose of insulin, intraday glycaemic variability and frequency of severe hypoglycaemia.ResultsThirty-six randomised participants (17 in the IDeg/IGlar and 19 in the IGlar/IDeg groups) were recruited, and data for 32 participants who completed the trial were analysed. The mean (7.74 ± 1.76 vs 8.56 ± 2.06 mmol/l; p = 0.04) and SD (2.60 ± 0.97 vs 3.19 ± 1.36 mmol/l; p = 0.03) of FPG were lower during IDeg treatment than during IGlar treatment, whereas the CV did not differ between the two treatments. The dose of IDeg was smaller than that of IGlar (11.0 ± 5.2 vs 11.8 ± 5.6 U/day; p < 0.01), but other secondary endpoints did not differ between the treatments.Conclusions/interpretationIDeg yielded a lower FPG level and smaller day-to-day variability of FPG at a lower daily dose compared with IGlar in participants with type 1 diabetes. IDeg serves as a good option for basal insulin in the treatment of type 1 diabetes.Trial registration: University Hospital Medical Information Network 000009965.Funding: This research recieved no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

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Section: Discussionsupporting

confidence: 83%

Effects of insulin degludec and insulin glargine on day-to-day fasting plasma glucose variability in individuals with type 1 diabetes: a multicentre, randomised, crossover study

Nakamura

Sakaguchi

et al. 2015

Diabetologia

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“…• CF might vary with the time of the day [14], physical activity [15], stress or illness. • CIR varies according to meal composition [16].…”

Section: Difficulty Of Computing the Bolus Of Insulinmentioning

confidence: 99%

Hypoglycaemia‐free artificial pancreas project

Magdelaine

Rivadeneira

Chaillous

et al. 2020

IET Systems Biology

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Driving blood glycaemia from hyperglycaemia to euglycaemia as fast as possible while avoiding hypoglycaemia is a major problem for decades for type-1 diabetes and is solved in this study. A control algorithm is designed that guaranties hypoglycaemia avoidance for the first time both from the theory of positive systems point of view and from the most pragmatic clinical practice. The solution consists of a state feedback control law that computes the required hyperglycaemia correction bolus in real-time to safely steer glycaemia to the target. A rigorous proof is given that shows that the control-law respects the positivity of the control and of the glucose concentration error: as a result, no hypoglycaemic episode occurs. The so-called hypo-free strategy control is tested with all the UVA/Padova T1DM simulator patients (i.e. ten adults, ten adolescents, and ten children) during a fasting-night scenario and in a hybrid closed-loop scenario including three meals. The theoretical results are assessed by the simulations on a large cohort of virtual patients and encourage clinical trials.

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“…The circadian nature of the problem is often accounted for by using different values of ICR for breakfast, lunch and dinner when calculating the bolus insulin needs (see e.g. [7]). In the last couple of years, effort has been made in the research community to take advantage of the clear 24-hour patterns in diabetes management for iteratively learning an adequate control strategy for maintaining the BG level within an acceptable range.…”

Section: Introductionmentioning

confidence: 99%

Identification of diurnal patterns in insulin action from measured CGM data for patients with T1DM

Reiterer

Kirchsteiger

Freckmann

et al. 2015

2015 European Control Conference (ECC)

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We propose a method to identify diurnal changes in insulin action in patients suffering from type 1 diabetes mellitus (T1DM) based on data recorded by continuous glucose monitoring systems (CGMS). In order to do so the data is fitted using a continuous time transfer function including time dependent terms. The identified values for the insulin needs per gram of carbohydrate were compared with the patientspecific carbohydrate-to-insulin-ratios used for the calculation of the bolus insulin needs. A good agreement between the identified parameters and values determined by diabetologists were found. Furthermore, the diurnal variations in insulin action (as inferred from the changes in the patient-specific carbohydrate-to-insulin-ratios) could be reproduced. The identified models, including the diurnal changes in insulin action and the information on the intra-patient variability, have the potential to be used in future studies for managing the blood glucose level of patients, e.g. in a smart bolus calculator.

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Diurnal variation of carbohydrate insulin ratio in adult type 1 diabetic patients treated with continuous subcutaneous insulin infusion

Cited by 17 publications

References 19 publications

Effects of insulin degludec and insulin glargine on day-to-day fasting plasma glucose variability in individuals with type 1 diabetes: a multicentre, randomised, crossover study

Effects of insulin degludec and insulin glargine on day-to-day fasting plasma glucose variability in individuals with type 1 diabetes: a multicentre, randomised, crossover study

Hypoglycaemia‐free artificial pancreas project

Identification of diurnal patterns in insulin action from measured CGM data for patients with T1DM

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