26 research outputs found

    Home use of a bihormonal bionic pancreas versus insulin pump therapy in adults with type 1 diabetes: a multicentre randomised crossover trial

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    The safety and effectiveness of a continuous, day-and-night automated glycaemic control system using insulin and glucagon has not been shown in a free-living, home-use setting. We aimed to assess whether bihormonal bionic pancreas initialised only with body mass can safely reduce mean glycaemia and hypoglycaemia in adults with type 1 diabetes who were living at home and participating in their normal daily routines without restrictions on diet or physical activity

    Consensus Recommendations for the Use of Automated Insulin Delivery (AID) Technologies in Clinical Practice

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    International audienceThe significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past six years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage

    Adjunctive Therapies to Optimize Closed-loop Glucose Control

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    Closed-loop insulin delivery systems are fast becoming the standard of care in the management of type 1 diabetes and have led to significant improvements in diabetes management. Nevertheless, there is still room for improvement for the closed-loop systems to optimize treatment and meet target glycemic control. Adjunct treatments have been introduced as an alternative method to insulin-only treatment methods to overcome diabetes treatment challenges and improve clinical and patient reported outcomes during closed-loop treatment. The adjunct treatment agents mostly consist of medications that are already approved for type 2 diabetes treatment and aim to complete the missing physiologic factors, such as the entero-endocrine system, that regulate glycemia in addition to insulin. This paper will review many of these adjunct therapies, including the basic mechanisms of action, potential benefits, side effects, and the evidence supporting their use during closed-loop treatment

    The Minimally-Invasive Oral Glucose Minimal Model: Estimation of Gastric Retention, Glucose Rate of Appearance, and Insulin Sensitivity from Type 1 Diabetes Data Collected in Real-life Conditions

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    Objective: Modeling the effect of meal composition on glucose excursion would help in designing decision support systems (DSS) for type 1 diabetes (T1D) management. In fact, macronutrients differently affect post-prandial gastric retention (GR), rate of appearance (R a), and insulin sensitivity (S I). Such variables can be estimated, in inpatient settings, from plasma glucose (G) and insulin (I) data using the Oral glucose Minimal Model (OMM) coupled with a physiological model of glucose transit through the gastrointestinal tract (reference OMM, R-OMM). Here, we present a model able to estimate those quantities in daily-life conditions, using minimally-invasive (MI) technologies, and validate it against the R-OMM. Methods: Forty-seven individuals with T1D (weight =78±13kg, age =42±10yr) underwent three 23-hour visits, during which G and I were frequently sampled while wearing continuous glucose monitoring (CGM) and insulin pump (IP). Using a Bayesian Maximum A Posteriori estimator, R-OMM was identified from plasma G and I measurements, and MI-OMM was identified from CGM and IP data. Results: The MI-OMM fitted the CGM data well and provided precise parameter estimates. GR and R a model parameters were not significantly different using the MI-OMM and R-OMM (p 0.05) and the correlation between the two S I was satisfactory ( ρ =0.77). Conclusion: The MI-OMM is usable to estimate GR, R a, and S I from data collected in real-life conditions with minimally-invasive technologies. Significance: Applying MI-OMM to datasets where meal compositions are available will allow modeling the effect of each macronutrient on GR, R a, and S I. DSS could finally exploit this information to improve diabetes management

    New therapies towards a better glycemic control in youths with type 1 diabetes

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    Type 1 diabetes (T1D) is the most frequent form of diabetes in pediatric age, affecting more than 1.5 million people younger than age 20 years worldwide. Early and intensive control of diabetes provides continued protection against both microvascular and macrovascular complications, enhances growth, and ensures normal pubertal development. In the absence of definitive reversal therapy for this disease, achieving and maintaining the recommended glycemic targets is crucial. In the last 30 years, enormous progress has been made using technology to better treat T1D. In spite of this progress, the majority of children, adolescents and young adults do not reach the recommended targets for glycemic control and assume a considerable burden each day. The development of promising new therapeutic advances, such as more physiologic insulin analogues, pioneering diabetes technology including continuous glucose monitoring and closed loop systems as well as new adjuvant drugs, anticipate a new paradigm in T1D management over the next few years. This review presents insights into current management of T1D in youths

    Glycemic outcomes of children 2-6 years of age with type 1 diabetes during the pediatric MiniMed™ 670G system trial.

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    BACKGROUND: Highly variable insulin sensitivity, susceptibility to hypoglycemia and inability to effectively communicate hypoglycemic symptoms pose significant challenges for young children with type 1 diabetes (T1D). Herein, outcomes during clinical MiniMed™ 670G system use were evaluated in children aged 2-6 years with T1D. METHODS: Participants (N = 46, aged 4.6 ± 1.4 years) at seven investigational centers used the MiniMed™ 670G system in Manual Mode during a two-week run-in period followed by Auto Mode during a three-month study phase. Safety events, mean A1C, sensor glucose (SG), and percentage of time spent in (TIR, 70-180 mg/dl), below (TBR, <70 mg/dl) and above (TAR, >180 mg/dl) range were assessed for the run-in and study phase and compared using a paired t-test or Wilcoxon signed-rank test. RESULTS: From run-in to end of study (median 87.1% time in auto mode), mean A1C and SG changed from 8.0 ± 0.9% to 7.5 ± 0.6% (p < 0.001) and from 173 ± 24 to 161 ± 16 mg/dl (p < 0.001), respectively. Overall TIR increased from 55.7 ± 13.4% to 63.8 ± 9.4% (p < 0.001), while TBR and TAR decreased from 3.3 ± 2.5% to 3.2 ± 1.6% (p = 0.996) and 41.0 ± 14.7% to 33.0 ± 9.9% (p < 0.001), respectively. Overnight TBR remained unchanged and TAR was further improved 12:00 am-6:00 am. Throughout the study phase, there were no episodes of severe hypoglycemia or diabetic ketoacidosis (DKA) and no serious adverse device-related events. CONCLUSIONS: At-home MiniMed™ 670G Auto Mode use by young children safely improved glycemic outcomes compared to two-week open-loop Manual Mode use. The improvements are similar to those observed in older children, adolescents and adults with T1D using the same system for the same duration of time
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