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Colmegna P, McFadden R, Fabris C, Lobo B, Nass R, Oliveri MC, Brown SA, Kovatchev B. Adaptive Biobehavioral Control: A Pilot Analysis of Human-Machine Coadaptation in Type 1 Diabetes. Diabetes Technol Ther 2024; 26:644-651. [PMID: 38662425 DOI: 10.1089/dia.2023.0399] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/26/2024]
Abstract
Background: While it is well recognized that an automated insulin delivery (AID) algorithm should adapt to changes in physiology, it is less understood that the individual would also have to adapt to the AID system. The adaptive biobehavioral control (ABC) method presented here attempts to compensate for this deficiency by including AID into an information cloud-based ecosystem. Methods: The Web Information Tool (WIT) implements the ABC concept via the following: (1) a Physiological Adaptation Module (PAM) that tracks metabolic changes and adapts AID parameters accordingly and (2) a Behavioral Adaptation Module (BAM) that provides information feedback. The safety of WIT (primary outcome) was assessed in an 8-week randomized, two-arm parallel pilot study. All participants used the Control-IQ® AID system enhanced with PAM, but only those in the Experimental group had access to BAM. Secondary glycemic outcomes were computed using the 2-week baseline period and the last 2 weeks of treatment. Results: Thirty participants with type 1 diabetes (T1D) completed all study procedures (17 female/13 male; age: 40 ± 14 years; HbA1c: 6.6% ± 0.5%). No severe hypoglycemia, DKA, or other serious adverse events were reported. Comparing the Experimental and Control groups, no significant difference was observed in time in range (70-180 mg/dL): 74.6% vs 73.8%, adjusted mean difference: 2.65%, 95% CI (-1.12%,6.41%), P = 0.161. Time in 70-140 mg/dL was significantly higher in the Experimental group: 50.7% vs 49.2%, 5.71% (0.44%,10.97%), P = 0.035, without increased time below range: 0.54% (-0.09%,1.17%), P = 0.089. Conclusion: The results demonstrate that it is safe to integrate an AID system into the WIT ecosystem. Validation in a full-scale study is ongoing.
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Affiliation(s)
- Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- Dexcom Inc, San Diego, California, USA
| | - Ryan McFadden
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- Dexcom Inc, San Diego, California, USA
| | - Chiara Fabris
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Benjamin Lobo
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- School of Data Science, University of Virginia, Charlottesville, Virginia, USA
| | - Ralf Nass
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Mary C Oliveri
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Sue A Brown
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
- Division of Endocrinology and Metabolism, Department of Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Boris Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
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Yang Q, Zeng B, Hao J, Yang Q, Sun F. Real-world glycaemic outcomes of automated insulin delivery in type 1 diabetes: A meta-analysis. Diabetes Obes Metab 2024; 26:3753-3763. [PMID: 38888056 DOI: 10.1111/dom.15718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2024] [Revised: 05/24/2024] [Accepted: 05/30/2024] [Indexed: 06/20/2024]
Abstract
AIM To evaluate the real-world effectiveness of automated insulin delivery (AID) systems in patients with type 1 diabetes (T1D). MATERIALS AND METHODS PubMed, Embase, the Cochrane Library, and ClinicalTrials.gov were searched for studies published up until 2 March 2024. We included pragmatic randomized controlled trials (RCTs), cohort studies, and before-after studies that compared AID systems with conventional insulin therapy in real-world settings and reported continuous glucose monitoring outcomes. Percent time in range (TIR; 3.9-10 mmol/L), time below range (TBR; <3.9 mmol/L), time above range (TAR; >10 mmol/L), and glycated haemoglobin (HbA1c) level were extracted. Data were summarized as mean differences (MDs) with 95% confidence interval. RESULTS A total of 23 before-after studies (101 704 participants) were included in the meta-analysis. AID systems were associated with an increased percentage of TIR (11.61%, 10.47 to 12.76; p < 0.001). The favourable effect of AID systems was consistently observed when used continuously for 6 (11.76%) or 12 months (11.33%), and in both children (12.16%) and adults (11.04%). AID systems also showed favourable effects on TBR (-0.53%, -0.63 to -0.42), TAR (-9.65%, -10.63 to -8.67) and HbA1c level (-0.42%, -0.47 to -0.37) when compared with previous treatments. CONCLUSIONS Similar improvements in glycaemic parameters were observed in real-world settings in RCTs using AID systems in T1D. AID systems benefit both children and adults by increasing TIR for both short- and long-term interventions.
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Affiliation(s)
- Qin Yang
- Department of Cardiology, Chu Hsien-I Memorial Hospital & Tianjin Institute of Endocrinology, Tianjin Medical University, Tianjin, China
| | - Baoqi Zeng
- Medical Research Center, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
- Department of Emergency, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China
| | - Jiayi Hao
- Medical Research Center, Peking University Binhai Hospital (Tianjin Fifth Central Hospital), Tianjin, China
| | - Qingqing Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
| | - Feng Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
- Xinjiang Medical University, Xinjiang, China
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Fabris C, Kovatchev B. Real-Life Use of Automated Insulin Delivery in Individuals With Type 2 Diabetes. J Diabetes Sci Technol 2024:19322968241274786. [PMID: 39180292 DOI: 10.1177/19322968241274786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/26/2024]
Abstract
BACKGROUND The objective of this work is to document performance of automated insulin delivery (AID) during real-life use in type 2 diabetes (T2D). METHODS A retrospective analysis was performed of continuous glucose monitoring and insulin delivery data from 796 individuals with T2D, who transitioned from 1-month predictive low-glucose suspend (PLGS) use to 3-month AID use, in real-life settings. Primary outcome was change of time in range (TIR = 70-180 mg/dL) from PLGS to AID. Secondary outcomes included time above/below range (TAR/TBR) and total daily insulin (TDI). RESULTS Compared with PLGS, AID increased TIR on average from 63.2% to 72.6%, decreased TAR from 36.2% to 26.8%, and increased TDI from 70.2 to 76.3 U (all P < .001), without significant change to TBR. Glycemic improvements were more pronounced in those with worse glycemic control during PLGS use (P < .001). CONCLUSIONS Real-life use of AID led to a rapid and sustained improvement of glycemic control in individuals with T2D.
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Affiliation(s)
- Chiara Fabris
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Boris Kovatchev
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
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4
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Forlenza GP, DeSalvo DJ, Aleppo G, Wilmot EG, Berget C, Huyett LM, Hadjiyianni I, Méndez JJ, Conroy LR, Ly TT, Sherr JL. Real-World Evidence of Omnipod ® 5 Automated Insulin Delivery System Use in 69,902 People with Type 1 Diabetes. Diabetes Technol Ther 2024; 26:514-525. [PMID: 38375861 DOI: 10.1089/dia.2023.0578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Background: The Omnipod® 5 Automated Insulin Delivery System was associated with favorable glycemic outcomes for people with type 1 diabetes (T1D) in two pivotal clinical trials. Real-world evidence is needed to explore effectiveness in nonstudy conditions. Methods: A retrospective analysis of the United States Omnipod 5 System users (aged ≥2 years) with T1D and sufficient data (≥90 days of data; ≥75% of days with ≥220 continuous glucose monitor readings/day) available in Insulet Corporation's device and person-reported datasets as of July 2023 was performed. Target glucose setting usage (i.e., 110-150 mg/dL in 10 mg/dL increments) was summarized and glycemic outcomes were examined. Subgroup analyses of those using the lowest average glucose target (110 mg/dL) and stratification by baseline characteristics (e.g., age, prior therapy, health insurance coverage) were conducted. Results: In total, 69,902 users were included. Multiple and higher glucose targets were more commonly used in younger age groups. Median percentage of time in range (TIR; 70-180 mg/dL) was 68.8%, 61.3%, and 53.6% for users with average glucose targets of 110, 120, and 130-150 mg/dL, respectively, with minimal time <70 mg/dL (all median <1.13%). Among those with an average glucose target of 110 mg/dL (n = 37,640), median TIR was 65.0% in children and adolescents (2-17 years) and 69.9% in adults (≥18 years). Subgroup analyses of users transitioning from Omnipod DASH or multiple daily injections and of Medicaid/Medicare users demonstrated favorable glycemic outcomes among these groups. Conclusion: These glycemic outcomes from a large and diverse sample of nearly 70,000 children and adults demonstrate effective use of the Omnipod 5 System under real-world conditions.
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Affiliation(s)
- Gregory P Forlenza
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Daniel J DeSalvo
- Department of Pediatrics, Baylor College of Medicine, Houston, Texas, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism, and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Emma G Wilmot
- Translational Medical Sciences, University of Nottingham, School of Medicine, Royal Derby Hospital, Derby, United Kingdom
| | - Cari Berget
- Department of Pediatrics, Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | | | | | | | | | - Trang T Ly
- Insulet Corporation, Acton, Massachusetts, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
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5
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Schoelwer MJ, DeBoer MD, Breton MD. Use of diabetes technology in children. Diabetologia 2024:10.1007/s00125-024-06218-0. [PMID: 38995398 DOI: 10.1007/s00125-024-06218-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Accepted: 05/23/2024] [Indexed: 07/13/2024]
Abstract
Children with type 1 diabetes and their caregivers face numerous challenges navigating the unpredictability of this complex disease. Although the burden of managing diabetes remains significant, new technology has eased some of the load and allowed children with type 1 diabetes to achieve tighter glycaemic management without fear of excess hypoglycaemia. Continuous glucose monitor use alone improves outcomes and is considered standard of care for paediatric type 1 diabetes management. Similarly, automated insulin delivery (AID) systems have proven to be safe and effective for children as young as 2 years of age. AID use improves not only blood glucose levels but also quality of life for children with type 1 diabetes and their caregivers and should be strongly considered for all youth with type 1 diabetes if available and affordable. Here, we review key data on the use of diabetes technology in the paediatric population and discuss management issues unique to children and adolescents.
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Affiliation(s)
| | - Mark D DeBoer
- Department of Pediatrics, University of Virginia, Charlottesville, VA, USA
| | - Marc D Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA.
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6
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Laugesen C, Ritschel T, Ranjan AG, Hsu L, Jørgensen JB, Svensson J, Ekhlaspour L, Buckingham B, Nørgaard K. Impact of Missed and Late Meal Boluses on Glycemic Outcomes in Automated Insulin Delivery-Treated Children and Adolescents with Type 1 Diabetes: A Two-Center, Population-Based Cohort Study. Diabetes Technol Ther 2024. [PMID: 38805311 DOI: 10.1089/dia.2024.0022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/30/2024]
Abstract
Objective: To evaluate the impact of missed or late meal boluses (MLBs) on glycemic outcomes in children and adolescents with type 1 diabetes using automated insulin delivery (AID) systems. Research Design and Methods: AID-treated (Tandem Control-IQ or Medtronic MiniMed 780G) children and adolescents (aged 6-21 years) from Stanford Medical Center and Steno Diabetes Center Copenhagen with ≥10 days of data were included in this two-center, binational, population-based, retrospective, 1-month cohort study. The primary outcome was the association between the number of algorithm-detected MLBs and time in target glucose range (TIR; 70-180 mg/dL). Results: The study included 189 children and adolescents (48% females with a mean ± standard deviation age of 13 ± 4 years). Overall, the mean number of MLBs per day in the cohort was 2.2 ± 0.9. For each additional MLB per day, TIR decreased by 9.7% points (95% confidence interval [CI] 11.3; 8.1), and compared with the quartile with fewest MLBs (Q1), the quartile with most (Q4) had 22.9% less TIR (95% CI: 27.2; 18.6). The age-, sex-, and treatment modality-adjusted probability of achieving a TIR of >70% in Q4 was 1.4% compared with 74.8% in Q1 (P < 0.001). Conclusions: MLBs significantly impacted glycemic outcomes in AID-treated children and adolescents. The results emphasize the importance of maintaining a focus on bolus behavior to achieve a higher TIR and support the need for further research in technological or behavioral support tools to handle MLBs.
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Affiliation(s)
- Christian Laugesen
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Tobias Ritschel
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Ajenthen G Ranjan
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Liana Hsu
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - John Bagterp Jørgensen
- Department of Applied Mathematics and Computer Science, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Jannet Svensson
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Gentofte, Denmark
| | - Laya Ekhlaspour
- Division of Endocrinology, Department of Pediatrics, University of San Francisco, San Francisco, California, USA
| | - Bruce Buckingham
- Division of Endocrinology and Diabetes, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Kirsten Nørgaard
- Clinical Research, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Gentofte, Denmark
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Kovatchev B, Castillo A, Pryor E, Kollar LL, Barnett CL, DeBoer MD, Brown SA. Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm. Diabetes Technol Ther 2024; 26:375-382. [PMID: 38277161 PMCID: PMC11305265 DOI: 10.1089/dia.2023.0469] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Abstract
Background: Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. Methods: The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. Results: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. Conclusion: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.
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Affiliation(s)
- Boris Kovatchev
- Address correspondence to: Boris Kovatchev, PhD, Center for Diabetes Technology, University of Virginia School of Medicine, 560 Ray C Hunt Drive, Charlottesville, VA 22903, USA
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8
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van den Heuvel T, Castaneda J, Thijs I, Arrieta A, Lintereur L, Shin J, Cohen O. MiniMed 780G System Outperforms Other Automated Insulin Systems Due to Algorithm Design, Not Bias: Response to Inaccurate Allegations. Diabetes Technol Ther 2024. [PMID: 38563714 DOI: 10.1089/dia.2024.0121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- Tim van den Heuvel
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Javier Castaneda
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Isabeau Thijs
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Arcelia Arrieta
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Lou Lintereur
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - John Shin
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
| | - Ohad Cohen
- Diabetes Operating Unit, Medtronic International Trading Sàrl, Tolochenaz, Switzerland
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Singh R, Imberg H, Ahmadi SS, Hallström S, Jendle J, Tengmark BO, Folino A, Marie E, Lind M. Effects, Safety, and Treatment Experience of Advanced Hybrid Closed-Loop Systems in Clinical Practice Among Adults Living With Type 1 Diabetes. J Diabetes Sci Technol 2024:19322968241242386. [PMID: 38629871 DOI: 10.1177/19322968241242386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/28/2024]
Abstract
BACKGROUND There are few studies providing a more comprehensive picture of advanced hybrid closed-loop (AHCL) systems in clinical practice. The aim was to evaluate the effects of the AHCL systems, Tandem® t: slim X2™ with Control IQ™, and MiniMed™ 780G, on glucose control, safety, treatment satisfaction, and practical barriers for individuals with type 1 diabetes. METHOD One hundred forty-two randomly selected adults with type 1 diabetes at six diabetes outpatient clinics in Sweden at any time treated with either the Tandem Control IQ (TCIQ) or the MiniMed 780G system were included. Glycated hemoglobin A1c (HbA1c) and glucose metrics were evaluated. Treatment satisfaction and practical barriers were examined via questionnaires. RESULTS Mean age was 42 years, median follow-up was 1.7 years, 58 (40.8%) were females, 65% used the TCIQ system. Glycated hemoglobin A1c was reduced by 0.6% (6.8 mmol/mol; 95% confidence interval [CI] = 0.5-0.8% [5.3-8.2 mmol/mol]; P < .001), from 7.3% to 6.7% (57-50 mmol/mol). Time in range (TIR) increased with 14.5% from 57.0% to 71.5% (95% CI = 12.2%-16.9%; P < .001). Time below range (TBR) (<70 mg/dL, <3.9 mmol/L) decreased from 3.8% to 1.6% (P < .001). The standard deviation of glucose values was reduced from 61 to 51 mg/dL (3.4-2.9 mmol/L, P < .001) and the coefficient of variation from 35% to 33% (P < .001). Treatment satisfaction increased, score 14.8 on the Diabetes Treatment Satisfaction Questionnaire (DTSQ) (change version ranging from -18 to 18, P < .001). Four severe hypoglycemia events were detected and no cases of ketoacidosis. Skin problems were experienced by 32.4% of the study population. CONCLUSIONS Advanced hybrid closed-loop systems improve glucose control with a reasonable safety profile and high treatment satisfaction. Skin problems are common adverse events.
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Affiliation(s)
- Ramanjit Singh
- Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Imberg
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Mathematical Sciences, Chalmers University of Technology and University of Gothenburg, Gothenburg, Sweden
- Statistiska Konsultgruppen, Gothenburg, Sweden
| | - Shilan Seyed Ahmadi
- Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Sara Hallström
- Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Johan Jendle
- Faculty of Medicine and Health, School of Medical Science, Örebro University, Örebro, Sweden
| | | | - Anna Folino
- Department of Medicine and Emergency, Sahlgrenska University Hospital/Mölndal Hospital, Gothenburg, Sweden
| | - Ekström Marie
- Department of Medicine, NU Hospital Group, Uddevalla, Sweden
| | - Marcus Lind
- Department of Medicine, Sahlgrenska University Hospital, Gothenburg, Sweden
- Department of Molecular and Clinical Medicine, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Medicine, NU Hospital Group, Uddevalla, Sweden
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10
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Considine EG, Sherr JL. Real-World Evidence of Automated Insulin Delivery System Use. Diabetes Technol Ther 2024; 26:53-65. [PMID: 38377315 PMCID: PMC10890954 DOI: 10.1089/dia.2023.0442] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
Objective: Pivotal trials of automated insulin delivery (AID) closed-loop systems have demonstrated a consistent picture of glycemic benefit, supporting approval of multiple systems by the Food and Drug Administration or Conformité Européenne mark receipt. To assess how pivotal trial findings translate to commercial AID use, a systematic review of retrospective real-world studies was conducted. Methods: PubMed and EMBASE were searched for articles published after 2018 with more than five nonpregnant individuals with type 1 diabetes (T1D). Data were screened/extracted in duplicate for sample size, AID system, glycemic outcomes, and time in automation. Results: Of 80 studies identified, 20 met inclusion criteria representing 171,209 individuals. Time in target range 70-180 mg/dL (3.9-10.0 mmol/L) was the primary outcome in 65% of studies, with the majority of reports (71%) demonstrating a >10% change with AID use. Change in hemoglobin A1c (HbA1c) was reported in nine studies (range 0.1%-0.9%), whereas four reported changes in glucose management indicator (GMI) with a 0.1%-0.4% reduction noted. A decrease in HbA1c or GMI of >0.2% was achieved in two-thirds of the studies describing change in HbA1c and 80% of articles where GMI was described. Time below range <70 mg/dL (<3.9 mmol/L) was reported in 16 studies, with all but 1 study showing stable or reduced levels. Most systems had >90% time in automation. Conclusion: With larger and more diverse populations, and follow-up periods of longer duration (∼9 months vs. 3-6 months for pivotal trials), real-world retrospective analyses confirm pivotal trial findings. Given the glycemic benefits demonstrated, AID is rapidly becoming the standard of care for all people living with T1D. Individuals should be informed of these systems and differences between them, have access to and coverage for these technologies, and receive support as they integrate this mode of insulin delivery into their lives.
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Affiliation(s)
| | - Jennifer L. Sherr
- Department of Pediatrics, Yale School of Medicine, New Haven, Connecticut, USA
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11
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Nimri R, Phillip M, Clements MA, Kovatchev B. Closed-Loop Control, Artificial Intelligence-Based Decision-Support Systems, and Data Science. Diabetes Technol Ther 2024; 26:S68-S89. [PMID: 38441444 DOI: 10.1089/dia.2024.2505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/07/2024]
Affiliation(s)
- Revital Nimri
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Moshe Phillip
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Mark A Clements
- Division of Pediatric Endocrinology, Children's Mercy Hospitals and Clinics, Kansas City, MO, USA
| | - Boris Kovatchev
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA, USA
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12
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Buckingham BA, Bergenstal RM. Decreasing the Burden of Carbohydrate Counting and Meal Announcement with Automated Insulin Delivery, Meal Recognition, and Autocorrection Doses: A Case Study. Diabetes Technol Ther 2024; 26:97-101. [PMID: 38377320 DOI: 10.1089/dia.2023.0505] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2024]
Abstract
The use of automated insulin delivery (AID) has led to a decrease in the burden of diabetes, allowing for better sleep, decreased anxiety about hypoglycemia, and automatic corrections doses, and meal recognition algorithms have provided "forgiveness" for imprecise carbohydrate (CHO) entries and missed or late meal boluses. We provide a case report and review of the current literature assessing the effect of AID on the burden of meal bolus. The case also demonstrates how sensor and pump data provide insight into insulin bolus behavior, and access to integrated cloud-based data has allowed for virtual patient visits. Glucose sensor metrics provides time in range and time below range, and the sensor-derived glucose management indicator provides an assessment of the long-term risk of complications when a laboratory glycated hemoglobin is not available.
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Affiliation(s)
- Bruce A Buckingham
- Division of Pediatric Endocrinology, Stanford University School of Medicine, Palo Alto, California, USA
| | - Richard M Bergenstal
- International Diabetes Center, HealthPartners Institute, Bloomington, Minnesota, USA
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13
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Messer LH, D’Souza E, Merchant G, Mueller L, Farnan J, Habif S, Pinsker JE. Smartphone Bolus Feature Increases Number of Insulin Boluses in People With Low Bolus Frequency. J Diabetes Sci Technol 2024; 18:10-13. [PMID: 37605474 PMCID: PMC10899852 DOI: 10.1177/19322968231191796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/23/2023]
Abstract
BACKGROUND The t:connect mobile app from Tandem Diabetes Care recently added a feature to allow t:slim X2 insulin pump users to initiate an insulin bolus from their personal smartphone. User experience and user interface considerations prioritized safety and ease of use, and we examined whether the smartphone bolus feature changed bolus behavior in individuals who bolused less than three times/day. METHODS We performed a retrospective analysis of t:slim X2 insulin pump users in the United States who had remotely updated their insulin pump software to be compatible with the smartphone bolus version of the app and who gave less than three boluses per day prior to the smartphone bolus update. RESULTS Of the 4470 early adopters who met these criteria, the median number of boluses was 2.2 per day (prior to smartphone bolus update) versus 2.7 per day (after smartphone bolus update), equating to approximately half a bolus more delivered per day (P < .001). Overall, a median of one bolus per day was administered by smartphone app as opposed to being initiated from the screen on the insulin pump. CONCLUSION This analysis found a significant increase in bolusing behavior among early adopters of the smartphone bolus feature of the t:connect mobile app.
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Wu Z, Talbo M, Lebbar M, Messier V, Courchesne A, Brazeau AS, Rabasa-Lhoret R. Characteristics associated with having a hemoglobin A1c ≤ 7 % (≤53 mmol/mol) among adults with type 1 diabetes using an automated insulin delivery system. Diabetes Res Clin Pract 2023; 206:111006. [PMID: 37952601 DOI: 10.1016/j.diabres.2023.111006] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 06/16/2023] [Accepted: 11/09/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND We aim to investigate which characteristics are associated with having an HbA1c ≤ 7 % (≤53 mmol/mol) among adult automated insulin delivery (AID) users living with type 1 diabetes (T1D). METHODS Cross-sectional study using data from the T1D BETTER registry. INCLUSION CRITERIA aged ≥ 18 years old, using a commercial AID system, and with a reported HbA1c range value. Participants were divided into two groups (HbA1c ≤ 7 % group, N = 57; and HbA1c > 7 % group, N = 74). RESULTS A total of 131 participants were included: 61.8 % females, median age (Q1-Q3) was 43.0 (30.0, 55.0) years, and median duration of T1D was 24.0 (16.0, 36.0) years. Logistic regression analysis suggested that participants with a bachelor's degree or above were more likely (OR 3.04, 95 %CI 1.22, 7.58; P = 0.017) and with a longer duration of pump use were less likely (OR 0.90, 95 %CI 0.84, 0.98; P = 0.009) to report an HbA1c ≤ 7 % when using an AID, after adjusting for age, sex, body mass index, and annual household income. CONCLUSIONS Our study indicates that among AID users, in order to maximize benefits, additional support is needed for those who do not have a bachelor's degree and/or who have been using an insulin pump for a long time.
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Affiliation(s)
- Zekai Wu
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Quebec, H3A 0G4, Canada; Montreal Clinical Research Institute, 110 Pine Ave W, Montréal, Québec, H2W 1R7, Canada.
| | - Meryem Talbo
- School of Human Nutrition, McGill University, 21111 Lakeshore Dr, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada
| | - Maha Lebbar
- Montreal Clinical Research Institute, 110 Pine Ave W, Montréal, Québec, H2W 1R7, Canada; Department of Nutrition, Faculty of Medicine, Universite de Montréal, 2900 Edouard Montpetit Blvd, Montreal, Quebec H3T 1J4, Canada
| | - Virginie Messier
- Montreal Clinical Research Institute, 110 Pine Ave W, Montréal, Québec, H2W 1R7, Canada
| | - Alec Courchesne
- Montreal Clinical Research Institute, 110 Pine Ave W, Montréal, Québec, H2W 1R7, Canada
| | - Anne-Sophie Brazeau
- School of Human Nutrition, McGill University, 21111 Lakeshore Dr, Sainte-Anne-de-Bellevue, Quebec, H9X 3V9, Canada; Montreal Diabetes Research Center, 900 Saint-Denis, Montreal, Quebec, H2X 0A9, Canada
| | - Remi Rabasa-Lhoret
- Department of Medicine, Division of Experimental Medicine, McGill University, Montreal, Quebec, H3A 0G4, Canada; Montreal Clinical Research Institute, 110 Pine Ave W, Montréal, Québec, H2W 1R7, Canada; Department of Nutrition, Faculty of Medicine, Universite de Montréal, 2900 Edouard Montpetit Blvd, Montreal, Quebec H3T 1J4, Canada; Montreal Diabetes Research Center, 900 Saint-Denis, Montreal, Quebec, H2X 0A9, Canada; Division of Endocrinology and Metabolism, Centre hospitalier de l'Université de montréal, 1051 Rue Sanguinet, Montréal, Quebec, H2X 3E4, Canada
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15
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Renard E, Joubert M, Villard O, Dreves B, Reznik Y, Farret A, Place J, Breton MD, Kovatchev BP. Safety and Efficacy of Sustained Automated Insulin Delivery Compared With Sensor and Pump Therapy in Adults With Type 1 Diabetes at High Risk for Hypoglycemia: A Randomized Controlled Trial. Diabetes Care 2023; 46:2180-2187. [PMID: 37729080 DOI: 10.2337/dc23-0685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2023] [Accepted: 09/06/2023] [Indexed: 09/22/2023]
Abstract
OBJECTIVE Assess the safety and efficacy of automated insulin delivery (AID) in adults with type 1 diabetes (T1D) at high risk for hypoglycemia. RESEARCH DESIGN AND METHODS Participants were 72 adults with T1D who used an insulin pump with Clarke Hypoglycemia Perception Awareness scale score >3 and/or had severe hypoglycemia during the previous 6 months confirmed by time below range (TBR; defined as sensor glucose [SG] reading <70 mg/dL) of at least 5% during 2 weeks of blinded continuous glucose monitoring (CGM). Parallel-arm, randomized trial (2:1) of AID (Tandem t:slim ×2 with Control-IQ technology) versus CGM and pump therapy for 12 weeks. The primary outcome was TBR change from baseline. Secondary outcomes included time in target range (TIR; 70-180 mg/dL), time above range (TAR), mean SG reading, and time with glucose level <54 mg/dL. An optional 12-week extension with AID was offered to all participants. RESULTS Compared with the sensor and pump (S&P), AID resulted in significant reduction of TBR by -3.7% (95% CI -4.8, -2.6), P < 0.001; an 8.6% increase in TIR (95% CI 5.2, 12.1), P < 0.001; and a -5.3% decrease in TAR (95% CI -87.7, -1.8), P = 0.004. Mean SG reading remained similar in the AID and S&P groups. During the 12-week extension, the effects of AID were sustained in the AID group and reproduced in the S&P group. Two severe hypoglycemic episodes occurred using AID. CONCLUSIONS In adults with T1D at high risk for hypoglycemia, AID reduced the risk for hypoglycemia more than twofold, as quantified by TBR, while improving TIR and reducing hyperglycemia. Hence, AID is strongly recommended for this specific population.
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Affiliation(s)
- Eric Renard
- Department of Endocrinology and Diabetology, Montpellier University Hospital, Montpellier, France
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, France
| | - Michael Joubert
- Diabetes Care Unit, Caen University Hospital, Caen, France
- University of Caen Normandy, University of Caen, Caen, France
| | - Orianne Villard
- Department of Endocrinology and Diabetology, Montpellier University Hospital, Montpellier, France
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, France
| | - Bleuenn Dreves
- Diabetes Care Unit, Caen University Hospital, Caen, France
- University of Caen Normandy, University of Caen, Caen, France
| | - Yves Reznik
- Diabetes Care Unit, Caen University Hospital, Caen, France
- University of Caen Normandy, University of Caen, Caen, France
| | - Anne Farret
- Department of Endocrinology and Diabetology, Montpellier University Hospital, Montpellier, France
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, France
| | - Jerome Place
- Department of Physiology, Institute of Functional Genomics, CNRS, INSERM, University of Montpellier, France
| | - Marc D Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
| | - Boris P Kovatchev
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA
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16
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Cobelli C, Kovatchev B. Developing the UVA/Padova Type 1 Diabetes Simulator: Modeling, Validation, Refinements, and Utility. J Diabetes Sci Technol 2023; 17:1493-1505. [PMID: 37743740 PMCID: PMC10658679 DOI: 10.1177/19322968231195081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Arguably, diabetes mellitus is one of the best quantified human conditions. In the past 50 years, the metabolic monitoring technologies progressed from occasional assessment of average glycemia via HbA1c, through episodic blood glucose readings, to continuous glucose monitoring (CGM) producing data points every few minutes. The high-temporal resolution of CGM data enabled increasingly intensive treatments, from decision support assisting insulin injection or oral medication, to automated closed-loop control, known as the "artificial pancreas." Throughout this progress, mathematical models and computer simulation of the human metabolic system became indispensable for the technological progress of diabetes treatment, enabling every step, from assessment of insulin sensitivity via the now classic Minimal Model of Glucose Kinetics, to in silico trials replacing animal experiments, to automated insulin delivery algorithms. In this review, we follow these developments, beginning with the Minimal Model, which evolved through the years to become large and comprehensive and trigger a paradigm change in the design of diabetes optimization strategies: in 2007, we introduced a sophisticated model of glucose-insulin dynamics and a computer simulator equipped with a "population" of N = 300 in silico "subjects" with type 1 diabetes. In January 2008, in an unprecedented decision, the Food and Drug Administration (FDA) accepted this simulator as a substitute to animal trials for the pre-clinical testing of insulin treatment strategies. This opened the field for rapid and cost-effective development and pre-clinical testing of new treatment approaches, which continues today. Meanwhile, animal experiments for the purpose of designing new insulin treatment algorithms have been abandoned.
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Affiliation(s)
| | - Boris Kovatchev
- Center for Diabetes Technology,
University of Virginia, Charlottesville, VA, USA
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17
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Kovatchev BP, Lobo B. Clinically-Similar Clusters of Daily CGM Profiles: Tracking the Progression of Glycemic Control Over Time. Diabetes Technol Ther 2023. [PMID: 37130300 DOI: 10.1089/dia.2023.0117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
BACKGROUND The adoption of CGM results in vast amounts of data, but their interpretation is still more art than exact science. The International Consensus on Time in Range (TIR) proposed the widely accepted TIR system of metrics, which we now take forward by introducing a finite and fixed set of clinically-similar clusters (CSCs), such that the TIR metrics of the daily CGM profiles within a cluster are homogeneous. METHODS CSC definition and validation used 204,710 daily CGM profiles in health, type 1 and type 2 diabetes (T1D, T2D), on different treatments. The CSCs were defined using 23,916 daily CGM profiles (Training set), and the final fixed set of CSCs was obtained using another 37,758 profiles (Validation set). The Testing set (143,036 profiles) was used to establish the robustness and generalizability of the CSCs. RESULTS The final set of CSCs contains 32 clusters. Any daily CGM profile was classifiable to a single CSC which approximated common glycemic metrics of the daily CGM profile, as evidenced by regression analyses with 0 intercept (R-squares≥0.83, e.g., correlation≥0.91), for all TIR and several other metrics. The CSCs distinguished CGM profiles in health, T2D, and T1D on different treatments, and allowed tracking of the daily changes in a person's glycemic control over time. CONCLUSION Daily CGM profiles can be classified into one of 32 prefixed CSCs, which enables a host of applications, e.g. tabulated data interpretation and algorithmic approaches to treatment, database indexing, pattern recognition, and tracking disease progression.
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Affiliation(s)
- Boris P Kovatchev
- University of Virginia, 2358, Center for Diabetes Technology, Charlottesville, Virginia, United States;
| | - Benjamin Lobo
- University of Virginia, 2358, School of Data Science, Charlottesville, Virginia, United States;
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18
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Beck RW, Kanapka LG, Breton MD, Brown SA, Wadwa RP, Buckingham BA, Kollman C, Kovatchev B. A Meta-Analysis of Randomized Trial Outcomes for the t:slim X2 Insulin Pump with Control-IQ Technology in Youth and Adults from Age 2 to 72. Diabetes Technol Ther 2023; 25:329-342. [PMID: 37067353 PMCID: PMC10171957 DOI: 10.1089/dia.2022.0558] [Citation(s) in RCA: 27] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Objective: To evaluate the effect of hybrid-closed loop Control-IQ technology (Control-IQ) in randomized controlled trials (RCTs) in subgroups based on baseline characteristics such as race/ethnicity, socioeconomic status (SES), prestudy insulin delivery modality (pump or multiple daily injections), and baseline glycemic control. Methods: Data were pooled and analyzed from 3 RCTs comparing Control-IQ to a Control group using continuous glucose monitoring in 369 participants with type 1 diabetes (T1D) from age 2 to 72 years old. Results: Time in range 70-180 mg/dL (TIR) in the Control-IQ group (n = 256) increased from 57% ± 17% at baseline to 70% ± 11% during follow-up, and in the Control group (n = 113) was 56% ± 15% and 57% ± 14%, respectively (adjusted treatment group difference = 11.5%, 95% confidence interval +9.7% to +13.2%, P < 0.001), an increase of 2.8 h/day on average. Significant reductions in mean glucose, hyperglycemia metrics, hypoglycemic metrics, and HbA1c were also observed. A statistically similar beneficial treatment effect on time in range 70-180 mg/dL was observed across the full age range irrespective of race-ethnicity, household income, prestudy continuous glucose monitor use, or prestudy insulin delivery method. Participants with the highest baseline HbA1c levels showed the greatest improvements in TIR and HbA1c. Conclusion: This pooled analysis of Control-IQ RCTs demonstrates the beneficial effect of Control-IQ in T1D across a broad spectrum of participant characteristics, including racial-ethnic minority, lower SES, lack of prestudy insulin pump experience, and high HbA1c levels. The greatest benefit was observed in participants with the worst baseline glycemic control in whom the auto-bolus feature of the Control-IQ algorithm appears to have substantial impact. Since no subgroups were identified that did not benefit from Control-IQ, hybrid-closed loop technology should be strongly considered for all youth and adults with T1D. Clinical Trials Registry: clinicaltrials.gov; NCT03563313, NCT03844789, and NCT04796779.
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Affiliation(s)
- Roy W. Beck
- JAEB Center for Health Research, Tampa, Florida, USA
| | | | - Marc D. Breton
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
| | - Sue A. Brown
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
| | - R. Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Bruce A. Buckingham
- Division of Pediatric Endocrinology and Diabetes, Department of Pediatrics, Stanford University School of Medicine, Stanford, California, USA
| | - Craig Kollman
- JAEB Center for Health Research, Tampa, Florida, USA
| | - Boris Kovatchev
- University of Virginia Center for Diabetes Technology, Charlottesville, Virginia, USA
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19
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Diaz C. JL, Colmegna P, Breton MD. Maximizing Glycemic Benefits of Using Faster Insulin Formulations in Type 1 Diabetes: In Silico Analysis Under Open- and Closed-Loop Conditions. Diabetes Technol Ther 2023; 25:219-230. [PMID: 36595379 PMCID: PMC10066764 DOI: 10.1089/dia.2022.0468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background: Ultrarapid-acting insulin analogs that could improve or even prevent postprandial hyperglycemia are now available for both research and clinical care. However, clear glycemic benefits remain elusive, especially when combined with automated insulin delivery (AID) systems. In this work, we study two insulin formulations in silico and highlight adjustments of both open-loop and closed-loop insulin delivery therapies as a critical step to achieve clinically meaningful improvements. Methods: Subcutaneous insulin transport models for two faster analogs, Fiasp (Novo Nordisk, Bagsværd, Denmark) and AT247 (Arecor, Saffron Walden, United Kingdom), were identified using data collected from prior clamp experiments, and integrated into the UVA/Padova type 1 diabetes simulator (adult cohort, N = 100). Pump therapy parameters and the aggressiveness of our full closed-loop algorithm were adapted to the new insulin pharmacokinetic and pharmacodynamic profiles through a sequence of in silico studies. Finally, we assessed these analogs' glycemic impact with and without modified therapy parameters in simulated conditions designed to match clinical trial data. Results: Simply switching to faster insulin analogs shows limited improvements in glycemic outcomes. However, when insulin acceleration is accompanied by therapy adaptation, clinical significance is found comparing time-in-range (70-180 mg/dL) with Aspart versus AT247 in open-loop (+5.1%); and Aspart versus Fiasp (+5.4%) or AT247 (+10.6%) in full closed-loop with no clinically significant differences in the exposure to hypoglycemia. Conclusion: In silico results suggest that properly adjusting intensive insulin therapy profiles, or AID tuning, to faster insulin analogs is necessary to obtain clinically significant improvements in glucose control.
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Affiliation(s)
- Jenny L. Diaz C.
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
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20
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Nimri R, Phillip M, Kovatchev B. Closed-Loop and Artificial Intelligence-Based Decision Support Systems. Diabetes Technol Ther 2023; 25:S70-S89. [PMID: 36802182 DOI: 10.1089/dia.2023.2505] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Affiliation(s)
- Revital Nimri
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Moshe Phillip
- Diabetes Technology Center, Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, Schneider Children's Medical Center of Israel, Petah Tikva, Israel
- Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Boris Kovatchev
- University of Virginia Center for Diabetes Technology, University of Virginia School of Medicine, Charlottesville, VA, USA
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