scholarly journals Hybrid Closed-Loop Insulin Delivery Systems for People With Type 1 Diabetes

2021 ◽  
Vol 1 (6) ◽  
Author(s):  
Health Technology Assessment Team
Keyword(s):  
Type 1 Diabetes ◽  
Closed Loop ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Insulin Delivery ◽  
Monitoring Methods ◽  
Expert Review ◽  
Expert Review Panel ◽  
Time In Range

The CADTH Health Technology Expert Review Panel (HTERP) suggests that hybrid closed-loop insulin delivery (HCL) systems hold promise for the care of people with type 1 diabetes. HTERP considers that, at present, there are insufficient long-term data on clinically relevant and patient-important outcomes to recommend how extensive the role of HCL systems should be in care. HTERP recommends the collection of robust and comparative data for consideration of future reassessments that compare HCL systems to existing insulin delivery and glucose monitoring methods in terms of glycated hemoglobin (hemoglobin A1C); time-in-range; time above and below range; glycemic variability; quality of life; patient, parent or caregiver, and health care provider satisfaction; diabetes-related complications; discontinuation rates; and health system impact. Robust data are collected in well-designed comparative studies that are, among other considerations, of sufficient duration to ensure a clinically meaningful outcome assessment.

Open-source automated insulin delivery systems for the management of type 1 diabetes during pregnancy

2021 ◽  
Vol 14 (9) ◽  
pp. e243522
Author(s):  
Khulood Bukhari ◽  
Rana Malek
Keyword(s):  
Type 1 Diabetes ◽  
Open Source ◽  
Closed Loop ◽  
Glycated Hemoglobin ◽  
Insulin Delivery ◽  
Third Trimester ◽  
Time In Range ◽  
Insulin Delivery System ◽  
Iphone Application

A 40-year-old woman used an open-source automated insulin delivery system to manage her type 1 diabetes (T1D) prior to conception. The code for building the iPhone application called ‘Loop’ that carried the software for the hybrid closed-loop controller was available online. Her glycated hemoglobin before conception was 6.4%. Between 6 and 12 weeks gestation, she spent 66% time-in-range (TIR), 28% time-above-range (TAR) and 6% time-below-range (TBR). Between 18 and 24 weeks gestation, she spent 68% TIR, 27% TAR and 5% TBR. During her third trimester, she spent 72% TIR, 21% TAR and 7% TBR. She delivered a healthy infant with no neonatal complications. Clinicians should be aware of this technology as it gains traction in the T1D community and seeks Food and Drug Administration approval.

scholarly journals The road from intermittently scanned glucose monitoring to hybrid closed-loop systems: Part A. Keys to success: subject profiles, choice of systems, education

2019 ◽  
Vol 10 ◽  
pp. 204201881986539 ◽  
Author(s):  
Francesca De Ridder ◽  
Marieke den Brinker ◽  
Christophe De Block
Keyword(s):  
Type 1 Diabetes ◽  
Closed Loop ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Open Loop ◽  
Loop Control ◽  
The Road ◽  
Low Glucose ◽  
Functional Features

Managing type 1 diabetes (T1DM) is challenging and requires intensive glucose monitoring and titration of insulin in order to reduce the risk of complications. The use of continuous glucose monitoring (CGM) systems, either flash or intermittently scanned glucose monitoring (isCGM) or real-time (RT) CGM, has positively affected the management of type 1 diabetes with the potential to lower HbA1c, enhance time spent in range, reduce frequency and time spent in hypoglycemia and hyperglycemia, lower glycemic variability, and improve quality of life. In recent years, both CGM and pump technology have advanced, with improved functional features and integration, including low glucose suspend (LGS), predictive low glucose suspend (PLGS), and hybrid closed-loop (HCL) systems. In this review, we highlight the benefits and limitations of use of isCGM/RT-CGM for open-loop control and recent progress in closed-loop control systems. We also discuss different subject profiles for the different systems, and focus on educational aspects that are key to successful use of the systems.

scholarly journals Lower Daily Carbohydrate Intake is associated with Improved Glycemic Control in Adults with Type 1 Diabetes using a Hybrid Closed-Loop System

2020 ◽  
Author(s):  
Vera Lehmann ◽  
Thomas Zueger ◽  
Anna Zeder ◽  
Sam Scott ◽  
Lia Bally ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Closed Loop ◽  
Glucose Monitoring ◽  
Closed Loop System ◽  
Female Age ◽  
Time In Range ◽  
Design And Methods

<i>Objective</i> <p>To assess the association between daily carbohydrate (CHO) intake and glycemic control in adult hybrid closed-loop (HCL) users with type 1 diabetes mellitus (T1D).</p> <p><i>Research Design and Methods</i></p> <p>Mean individual daily CHO intake (MIDC) and deviation from MIDC (rMIDC; ≤80% low; 81-120% medium, >120% high CHO consumption) were compared with parameters of glycemic control assessed by continuous glucose monitoring (CGM). </p> <p><i>Results</i></p> <p>Records from 36 patients (26 male, 10 female; age 36.9±13.5y; HbA<sub>1c</sub> 7.1±0.9% [54±10mmol/mol]) provided 810 days of data (22.5±6.7 days per patient). Time in range (70-180mg/dL) for low, medium, and high CHO consumption was 77.4±15.4%, 75.2±16.7% and 70.4±17.8%, respectively (<i>p</i><0.001). Time above range (>180mg/dL) was 20.1±14.7%, 22.0±16.9% and 27.2±18.4%, respectively (<i>p</i><0.001). There was no between-group difference for time in hypoglycemia (<70mg/dL; <i>p</i>=0.50).</p> <p><i>Conclusions</i></p> Daily CHO intake was inversely associated with glycemic control in adults with T1D using a HCL system. Lower CHO intake may be a strategy to optimize glucose control in HCL users.

scholarly journals Achieving the HbA1c Target Requires Longer Time in Range in Pregnant Women with Type 1 Diabetes

2021 ◽  
Author(s):  
Ping Ling ◽  
Daizhi Yang ◽  
Nan Gu ◽  
Xinhua Xiao ◽  
Jing Lu ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Pregnant Women ◽  
Glucose Monitoring ◽  
Glycemic Variability ◽  
Pregnancy And Postpartum ◽  
Best Fitting ◽  
Time In Range ◽  
Hba1c Target ◽  
Mean Glucose

Abstract Aims Continuous glucose monitoring (CGM) overcomes the limitations of glycated hemoglobin (HbA1c). This study was to investigate the relationship between CGM metrics and laboratory HbA1c in pregnant women with type 1 diabetes. Methods An observational study enrolled pregnant women with type 1 diabetes who wore CGM devices during pregnancy and postpartum from 11 hospitals in China from January 2015 to June 2019. CGM data were collected to calculate time-in-range (TIR), time above range (TAR), time below range (TBR), and glycemic variability parameters. Relationships between the CGM metrics and HbA1c were explored. Linear and curvilinear regressions were conducted to investigate the best-fitting model to clarify the influence of HbA1c on the TIR-HbA1c relationship during pregnancy. Results A total of 272 CGM data and corresponding HbA1c from 98 pregnant women with type 1 diabetes and their clinical characteristics were analyzed in this study. Mean HbA1c and TIR were 6.49±1.29% and 76.16±17.97% during pregnancy, respectively. HbA1c was moderately correlated with TIR 3.5-7.8(R= -0.429, P=0.001), mean glucose (R= 0.405, P=0.001) and TAR 7.8 (R=0.435, P=0.001), but was weakly correlated with TBR 3.5 (R=0.034, P=0.001) during pregnancy. On average, a 1% (11 mmol/mol) decrease in HbA1c corresponded to an 8.5% increase in TIR 3.5-7.8. During pregnancy, HbA1c of 6.0%, 6.5% and 7.0% were equivalent to a TIR 3.5-7.8 of 78%, 74%, and 69%, respectively. Conclusions We found that there was a moderate correlation between HbA1c and TIR 3.5-7.8 during pregnancy. To achieve the HbA1c target &lt;6.0%, pregnant women with type 1 diabetes should strive for TIR 3.5-7.8 &gt;78% (18h 43min) during pregnancy.

scholarly journals Lower Daily Carbohydrate Intake is associated with Improved Glycemic Control in Adults with Type 1 Diabetes using a Hybrid Closed-Loop System

2020 ◽  
Author(s):  
Vera Lehmann ◽  
Thomas Zueger ◽  
Anna Zeder ◽  
Sam Scott ◽  
Lia Bally ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Closed Loop ◽  
Glucose Monitoring ◽  
Closed Loop System ◽  
Female Age ◽  
Time In Range ◽  
Design And Methods

<i>Objective</i> <p>To assess the association between daily carbohydrate (CHO) intake and glycemic control in adult hybrid closed-loop (HCL) users with type 1 diabetes mellitus (T1D).</p> <p><i>Research Design and Methods</i></p> <p>Mean individual daily CHO intake (MIDC) and deviation from MIDC (rMIDC; ≤80% low; 81-120% medium, >120% high CHO consumption) were compared with parameters of glycemic control assessed by continuous glucose monitoring (CGM). </p> <p><i>Results</i></p> <p>Records from 36 patients (26 male, 10 female; age 36.9±13.5y; HbA<sub>1c</sub> 7.1±0.9% [54±10mmol/mol]) provided 810 days of data (22.5±6.7 days per patient). Time in range (70-180mg/dL) for low, medium, and high CHO consumption was 77.4±15.4%, 75.2±16.7% and 70.4±17.8%, respectively (<i>p</i><0.001). Time above range (>180mg/dL) was 20.1±14.7%, 22.0±16.9% and 27.2±18.4%, respectively (<i>p</i><0.001). There was no between-group difference for time in hypoglycemia (<70mg/dL; <i>p</i>=0.50).</p> <p><i>Conclusions</i></p> Daily CHO intake was inversely associated with glycemic control in adults with T1D using a HCL system. Lower CHO intake may be a strategy to optimize glucose control in HCL users.

scholarly journals Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Susan Kohl Malone ◽  
Amy J. Peleckis ◽  
Laura Grunin ◽  
Gary Yu ◽  
Sooyong Jang ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Glycemic Control ◽  
Closed Loop ◽  
Sleep Onset ◽  
Glucose Monitoring ◽  
Insulin Delivery ◽  
Effect Sizes ◽  
Onset Latency ◽  
Hypoglycemia Unawareness

Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age = 58   y ) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t -tests and Cohen’s d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia ( d = 0.47 ‐ 0.79 ), reduced basal insulin requirements ( d = 0.48 ), and a smaller glucose coefficient of variation ( d = 0.47 ) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score ( d = 0.60 ), lability index ( d = 0.50 ), HYPO score ( d = 1.06 )). Shorter sleep onset latency ( d = 1.53 ; p < 0.01 ), shorter sleep duration ( d = 0.79 ), fewer total activity counts ( d = 1.32 ), shorter average awakening length ( d = 0.46 ), and delays in sleep onset ( d = 1.06 ) and sleep midpoint ( d = 0.72 ) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914).

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