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Rizzi A, Tartaglione L, Lucaccini Paoli L, Leo ML, Popolla V, Viti L, Barberio A, Di Leo M, Pontecorvi A, Pitocco D. Evaluation of time in tight range and the glycaemia risk index in adults with type 1 diabetes using an advanced hybrid closed loop system: A 1-year real-world assessment. Diabetes Obes Metab 2024; 26:4078-4086. [PMID: 39010292 DOI: 10.1111/dom.15766] [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] [Received: 03/25/2024] [Revised: 06/13/2024] [Accepted: 06/22/2024] [Indexed: 07/17/2024]
Abstract
AIM To assess the long-term glycaemic outcomes, with additional metrics, in adults with type 1 diabetes (T1D) using the Tandem t:slim X2 with Control-IQ technology advanced hybrid closed-loop (AHCL) system. METHODS This was a single-centre, retrospective study involving 56 T1D patients who transitioned to the Tandem t:slim X2 with Control-IQ system. The primary and secondary endpoints consisted of variations in time in tight range (TiTR; 70-140 mg/dL) and the glycaemia risk index (GRI), respectively. Additional standardized continuous glucose monitoring (CGM) metrics, mean sensor glucose, coefficient of variation, the glucose management indicator (GMI), HbA1c and insulin daily dose, were also evaluated. Variables were measured at baseline and at 15 days, 3 months, 6 months and 1 year after Tandem t:slim X2 Control-IQ initiation. Glucose outcomes are expressed as mean (standard deviation). RESULTS Use of Tandem t:slim X2 with Control-IQ over 1 year was associated with an increase in mean TiTR, from 38.11% (17.05%) to 43.10% (13.20%) (P = .059), and with a decline in the GRI, from 41.03 (25.48) to 28.55 (16.27) (P = .008). CGM metrics, including time in range and time above range, showed consistent improvements. Mean sensor glucose, the GMI and HbA1c decreased significantly over time. After an initial increase, insulin daily dose remained stable throughout the 12 months. CONCLUSIONS The results highlight the sustained effectiveness of Tandem t:slim X2 with Control-IQ in improving glycaemic outcomes over 1 year and support the use of this technology for the management of T1D.
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Affiliation(s)
- Alessandro Rizzi
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Linda Tartaglione
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Lorenzo Lucaccini Paoli
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Maria Laura Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Valentina Popolla
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Luca Viti
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Annarita Barberio
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Mauro Di Leo
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Alfredo Pontecorvi
- Department of Endocrinology, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
| | - Dario Pitocco
- Diabetes Care Unit, Fondazione Policlinico Agostino Gemelli, Universita' Cattolica del Sacro Cuore, Rome, Italy
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Lee J, Yoon KH. Islet transplantation in Korea. J Diabetes Investig 2024. [PMID: 39105663 DOI: 10.1111/jdi.14264] [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: 02/26/2024] [Revised: 06/22/2024] [Accepted: 06/27/2024] [Indexed: 08/07/2024] Open
Abstract
Type 1 diabetes mellitus is characterized by absolute insulin deficiency, which requires life-long insulin replacement. Exogenous multiple-daily insulin injections are most commonly prescribed for patients with type 1 diabetes mellitus. However, exogenous insulin supply often fails to cope with real-time changing life-log variables, such as activity, diet and stress, which results in recurrent hypo- and hyperglycemia in patients with type 1 diabetes mellitus. Islet transplantation is an ideal method to treat patients with type 1 diabetes mellitus, as it can restore the endogenous capacity of glucose-stimulated insulin secretion. However, due to donor scarcity and technical barriers, only a limited number of islet transplantations have been carried out in Asia, including South Korea. Since 2013, our center has carried out two allogenic islet transplantations, with one case leading to near total insulin independence after one-to-one islet transplantation. Although the other patient failed to restore endogenous insulin production, there was a remarkable improvement in hypoglycemia. We speculate that islet transplantation remains an important and ideal treatment option for patients with type 1 diabetes mellitus who suffer from recurrent severe hypoglycemia.
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Affiliation(s)
- Joonyub Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Seoul St Mary's Hospital, The Catholic University of Korea, Seoul, Korea
| | - Kun-Ho Yoon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, College of Medicine, Seoul St Mary's Hospital, The Catholic University of Korea, Seoul, Korea
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Kalita D, Sharma H, Mirza KB. Continuous Glucose, Insulin and Lifestyle Data Augmentation in Artificial Pancreas Using Adaptive Generative and Discriminative Models. IEEE J Biomed Health Inform 2024; 28:4963-4974. [PMID: 38709612 DOI: 10.1109/jbhi.2024.3396880] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Artificial pancreas requires data from multiple sources for accurate insulin dose estimation. These include data from continuous glucose sensors, past insulin dosage information, meal quantity and time and physical activity data. The effectiveness of closed-loop diabetes management systems might be hampered by the absence of these data caused by device error or lack of compliance by patients. In this study, we demonstrate the effect of output sequence length-driven generative and discriminative model selection in high quality data generation and augmentation. This novel generative adversarial network (GAN) based architecture automatically selects the generator and discriminator architecture based on the desired output sequence length. The proposed model is able to generate glucose, physical activity, meal information data for individual patients. The discriminative scores for Ohio T1DM (2018) dataset were 0.17 ±0.03 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, Heart Rate, Steps) and for Ohio T1D (2020) dataset was 0.16 ±0.02 (Inputs: CGM, CHO, Insulin) and 0.15 ±0.02 (Inputs: CGM, CHO, Insulin, acceleration). A mixture of generated and real data was used to test predictive scores for glucose forecasting models. The best RMSE and MARD achieved for OhioT1DM patients were 17.19 ±3.22 and 7.14 ±1.76 for PH=30 min with CGM, CHO, Insulin, heartrate and steps as inputs. Similarly, the RMSE and MARD for real+synthetic data were 15.63 ±2.57 and 5.86 ±1.69 respectively. Compared to existing generative models, we demonstrate that sequence length based architecture selection leads to better synthetic data generation for multiple output sequences (CGM, CHO, Insulin) and forecasting accuracy.
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Polsky S, Buschur E, Dungan K, Garcetti R, Nease E, Malecha E, Bartholomew A, Johnson C, Pyle L, Snell-Bergeon J. Randomized Trial of Assisted Hybrid Closed-Loop Therapy Versus Sensor-Augmented Pump Therapy in Pregnancy. Diabetes Technol Ther 2024; 26:547-555. [PMID: 38386437 DOI: 10.1089/dia.2024.0012] [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: 02/24/2024]
Abstract
Objective: Examine gestational safety, glycemic and health outcomes, of a hybrid closed-loop (HCL) system without pregnancy-specific glucose targets. Research Design: This was a pilot feasibility investigator-initiated, two-site, single-blind, randomized controlled trial of sensor-augmented pump therapy (SAPT) versus HCL therapy in type 1 diabetes pregnancies. Participants were enrolled in the first trimester and randomized at 14-18 weeks of gestation and used SAPT or HCL until 4-6 weeks postpartum. We compared continuous glucose monitoring (CGM) metrics, severe hypoglycemia (SH), diabetic ketoacidosis (DKA), adverse skin reactions, and pregnancy outcomes between groups. Results: Baseline characteristics were similar between groups (n = 11 HCL and n = 12 SAPT). There was no SH or DKA episode after randomization. Time spent <54 mg/dL did not differ between groups. Time spent <63 mg/dL decreased in both groups, significantly in the HCL group (3.5% [1.3% standard error] second trimester and 2.8% [1.3%] third trimester vs. 7.9% [1.3%] run-in phase, P < 0.05 for both). Mean sensor glucose was lower with SAPT compared to HCL therapy in the third trimester (119 [4] mg/dL SAPT vs. 132 [4] mg/dL HCL, P < 0.05). Third trimester time-in-range (TIR; 63-140 mg/dL) increased with SAPT (68.2% [3.1%] vs. 64.3% [3.1%] run-in phase, P < 0.05). Gestational health outcomes did not differ between groups. The HCL group used assistive techniques, such as fake carbohydrate boluses and exiting HCL overnight. Conclusions: CGM within group differences were seen for time <63 mg/dL favoring HCL therapy and TIR favoring SAPT (third trimester vs. baseline). Safety and adverse pregnancy outcomes were similar between groups.
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Affiliation(s)
- Sarit Polsky
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Elizabeth Buschur
- Division of Diabetes, Endocrinology and Metabolism, Ohio State University, Columbus, Ohio, USA
| | - Kathleen Dungan
- Division of Diabetes, Endocrinology and Metabolism, Ohio State University, Columbus, Ohio, USA
| | - Rachel Garcetti
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Emily Nease
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Emily Malecha
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Anna Bartholomew
- Division of Maternal and Fetal Medicine, Ohio State University, Columbus, Ohio, USA
| | - Carly Johnson
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
| | - Laura Pyle
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA
| | - Janet Snell-Bergeon
- Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, Colorado, USA
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Ware J, Boughton CK, Allen JM, Wilinska ME, Hartnell S, Thankamony A, Randell T, Ghatak A, Besser RE, Elleri D, Trevelyan N, Campbell FM, Sibayan J, Bailey R, Calhoun P, Dunseath G, Hovorka R. Effect of 48 Months of Closed-Loop Insulin Delivery on Residual C-Peptide Secretion and Glycemic Control in Newly Diagnosed Youth With Type 1 Diabetes: A Randomized Trial. Diabetes Care 2024; 47:1441-1448. [PMID: 38924772 PMCID: PMC11272979 DOI: 10.2337/dc24-0360] [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: 02/19/2024] [Accepted: 05/15/2024] [Indexed: 06/28/2024]
Abstract
OBJECTIVE We evaluated the effect of long-term intensive metabolic control with hybrid closed-loop (CL) on residual C-peptide secretion and glucose control compared with standard insulin therapy in youth with type 1 diabetes over 48 months. RESEARCH DESIGN AND METHODS Following the 24-month primary phase of a multicenter, randomized, parallel trial of 96 newly diagnosed youth aged 10 to 16.9 years, participants were invited to an extension phase using treatment allocated at randomization. They continued with hybrid CL using the Cambridge algorithm or standard insulin therapy (control) until 48 months after diagnosis. Analysis was by intention-to-treat. RESULTS At 24 months after diagnosis, 81 participants (mean ± SD age 14 ± 2 years) continued in the extension phase (47 CL, 34 control). There was no difference in fasting C-peptide corrected for fasting glucose at 48 months between groups (CL: 5 ± 9 vs. control: 6 ± 14 pmol/L per mmol/L; mean adjusted difference -2 [95% CI -7, 4; P = 0.54]). Central laboratory HbA1c remained lower in the CL group by 0.9% (10 mmol/mol [95% CI 0.2, 1.5; 3, 17 mmol/mol); P = 0.009). Time in target range of 3.9 to 10.0 mmol/L was 12 percentage points (95% CI 3, 20; P = 0.008) higher in the CL group compared with control. There were 11 severe hypoglycemic events (6 CL, 5 control) and 7 diabetic ketoacidosis events (3 CL, 4 control) during the extension phase. CONCLUSIONS Improved glycemic control was sustained over 48 months after diagnosis with CL insulin delivery compared with standard therapy in youth with type 1 diabetes. This did not appear to confer a protective effect on residual C-peptide secretion.
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Affiliation(s)
- Julia Ware
- Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge, Cambridge, U.K
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Charlotte K. Boughton
- Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge, Cambridge, U.K
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, U.K
| | - Janet M. Allen
- Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge, Cambridge, U.K
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Malgorzata E. Wilinska
- Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge, Cambridge, U.K
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals National Health Service Foundation Trust, Cambridge, U.K
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
| | - Tabitha Randell
- Department of Paediatric Diabetes and Endocrinology, Nottingham Children's Hospital, Nottingham, U.K
| | - Atrayee Ghatak
- Department of Diabetes, Alder Hey Children's National Health Service Foundation Trust, Liverpool, U.K
| | - Rachel E.J. Besser
- Department of Paediatrics, University of Oxford, Oxford, U.K
- National Institute for Health and Care Research Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, U.K
| | - Daniela Elleri
- Department of Diabetes, Royal Hospital for Sick Children, Edinburgh, U.K
| | - Nicola Trevelyan
- Paediatric Diabetes, Southampton Children’s Hospital, Southampton, U.K
| | - Fiona M. Campbell
- Department of Paediatric Diabetes, Leeds Children’s Hospital, Leeds, U.K
| | | | | | | | | | - Roman Hovorka
- Institute of Metabolic Science-Metabolic Research Laboratories and Medical Research Council Metabolic Diseases Unit, University of Cambridge, Cambridge, U.K
- Department of Paediatrics, University of Cambridge, Cambridge, U.K
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6
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Watso JC, Robinson AT, Singar SAB, Cuba JN, Koutnik AP. Advanced cardiovascular physiology in an individual with type 1 diabetes after 10-year ketogenic diet. Am J Physiol Cell Physiol 2024; 327:C446-C461. [PMID: 38912731 DOI: 10.1152/ajpcell.00694.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 06/18/2024] [Accepted: 06/18/2024] [Indexed: 06/25/2024]
Abstract
Adults with type 1 diabetes (T1D) have an elevated risk for cardiovascular disease (CVD) compared with the general population. HbA1c is the primary modifiable risk factor for CVD in T1D. Fewer than 1% of patients achieve euglycemia (<5.7% HbA1c). Ketogenic diets (KD; ≤50 g carbohydrate/day) may improve glycemia and downstream vascular dysfunction in T1D by reducing HbA1c and insulin load. However, there are concerns regarding the long-term CVD risk from a KD. Therefore, we compared data collected in a 60-day window in an adult with T1D on exogenous insulin who consumed a KD for 10 years versus normative values in those with T1D (T1D norms). The participant achieved euglycemia with an HbA1c of 5.5%, mean glucose of 98 [5] mg/dL (median [interquartile range]), 90 [11]% time-in-range 70-180 mg/dL (T1D norms: 1st percentile for all), and low insulin requirements of 0.38 ± 0.03 IU/kg/day (T1D norms: 8th percentile). Seated systolic blood pressure (SBP) was 113 mmHg (T1D norms: 18th percentile), while ambulatory awake SBP was 132 ± 15 mmHg (T1D target: <130 mmHg), blood triglycerides were 69 mg/dL (T1D norms: 34th percentile), low-density lipoprotein was 129 mg/dL (T1D norms: 60th percentile), heart rate was 56 beats/min (T1D norms: >1SD below the mean), carotid-femoral pulse wave velocity was 7.17 m/s (T1D norms: lowest quartile of risk), flow-mediated dilation was 12.8% (T1D norms: >1SD above mean), and cardiac vagal baroreflex gain was 23.5 ms/mmHg (T1D norms: >1SD above mean). Finally, there was no indication of left ventricular diastolic dysfunction from echocardiography. Overall, these data demonstrate below-average CVD risk relative to T1D norms despite concerns regarding the long-term impact of a KD on CVD risk.NEW & NOTEWORTHY Adults with type 1 diabetes (T1D) have a 10-fold higher risk for cardiovascular disease (CVD) compared with the general population. We assessed cardiovascular health metrics in an adult with T1D who presented with a euglycemic HbA1c after following a ketogenic diet for the past 10 years. Despite concerns about the ketogenic diet increasing CVD risk, the participant exhibited below-average CVD risk relative to others with T1D when considering all outcomes together.
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Affiliation(s)
- Joseph C Watso
- Cardiovascular and Applied Physiology Laboratory, Department of Health, Nutrition, and Food Sciences, Florida State University, Tallahassee, Florida, United States
| | - Austin T Robinson
- Neurovascular Physiology Laboratory, Indiana University, Bloomington, Indiana, United States
| | - Saiful Anuar Bin Singar
- Department of Health, Nutrition, and Food Sciences, Florida State University, Tallahassee, Florida, United States
| | - Jens N Cuba
- Cardiovascular and Applied Physiology Laboratory, Department of Health, Nutrition, and Food Sciences, Florida State University, Tallahassee, Florida, United States
| | - Andrew P Koutnik
- Sansum Diabetes Research Institute, Santa Barbara, California, United States
- Human Healthspan, Resilience, and Performance, Florida Institute for Human and Machine Cognition, Pensacola, Florida, United States
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Sheng B, Pushpanathan K, Guan Z, Lim QH, Lim ZW, Yew SME, Goh JHL, Bee YM, Sabanayagam C, Sevdalis N, Lim CC, Lim CT, Shaw J, Jia W, Ekinci EI, Simó R, Lim LL, Li H, Tham YC. Artificial intelligence for diabetes care: current and future prospects. Lancet Diabetes Endocrinol 2024; 12:569-595. [PMID: 39054035 DOI: 10.1016/s2213-8587(24)00154-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Revised: 03/28/2024] [Accepted: 05/16/2024] [Indexed: 07/27/2024]
Abstract
Artificial intelligence (AI) use in diabetes care is increasingly being explored to personalise care for people with diabetes and adapt treatments for complex presentations. However, the rapid advancement of AI also introduces challenges such as potential biases, ethical considerations, and implementation challenges in ensuring that its deployment is equitable. Ensuring inclusive and ethical developments of AI technology can empower both health-care providers and people with diabetes in managing the condition. In this Review, we explore and summarise the current and future prospects of AI across the diabetes care continuum, from enhancing screening and diagnosis to optimising treatment and predicting and managing complications.
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Affiliation(s)
- Bin Sheng
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China; Key Laboratory of Artificial Intelligence, Ministry of Education, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Shanghai, China
| | - Krithi Pushpanathan
- Centre of Innovation and Precision Eye Health, Department of Ophthalmology, National University of Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Zhouyu Guan
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Quan Hziung Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Zhi Wei Lim
- Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Samantha Min Er Yew
- Centre of Innovation and Precision Eye Health, Department of Ophthalmology, National University of Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | | | - Yong Mong Bee
- Department of Endocrinology, Singapore General Hospital, Singapore; SingHealth Duke-National University of Singapore Diabetes Centre, Singapore Health Services, Singapore
| | - Charumathi Sabanayagam
- Ophthalmology and Visual Sciences Academic Clinical Program, Duke-National University of Singapore Medical School, Singapore; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore
| | - Nick Sevdalis
- Centre for Behavioural and Implementation Science Interventions, National University of Singapore, Singapore
| | | | - Chwee Teck Lim
- Department of Biomedical Engineering, National University of Singapore, Singapore; Institute for Health Innovation and Technology, National University of Singapore, Singapore; Mechanobiology Institute, National University of Singapore, Singapore
| | - Jonathan Shaw
- Baker Heart and Diabetes Institute, Melbourne, VIC, Australia
| | - Weiping Jia
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China
| | - Elif Ilhan Ekinci
- Australian Centre for Accelerating Diabetes Innovations, Melbourne Medical School and Department of Medicine, University of Melbourne, Melbourne, VIC, Australia; Department of Endocrinology, Austin Health, Melbourne, VIC, Australia
| | - Rafael Simó
- Diabetes and Metabolism Research Unit, Vall d'Hebron University Hospital and Vall d'Hebron Research Institute, Barcelona, Spain; Centro de Investigación Biomédica en Red de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, Madrid, Spain
| | - Lee-Ling Lim
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia; Department of Medicine and Therapeutics, Chinese University of Hong Kong, Hong Kong Special Administrative Region, China; Asia Diabetes Foundation, Hong Kong Special Administrative Region, China
| | - Huating Li
- Shanghai Belt and Road International Joint Laboratory for Intelligent Prevention and Treatment of Metabolic Disorders, Department of Computer Science and Engineering, School of Electronic, Information, and Electrical Engineering, Shanghai Jiao Tong University, Department of Endocrinology and Metabolism, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai, China.
| | - Yih-Chung Tham
- Centre of Innovation and Precision Eye Health, Department of Ophthalmology, National University of Singapore, Singapore; Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Ophthalmology and Visual Sciences Academic Clinical Program, Duke-National University of Singapore Medical School, Singapore; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore.
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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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9
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Ferguson AM, Lin AC. Themes, Rates, and Risk of Adverse Events of the Artificial Pancreas in the United States Using MAUDE. Ann Biomed Eng 2024; 52:2282-2286. [PMID: 38740730 PMCID: PMC11247049 DOI: 10.1007/s10439-024-03529-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024]
Abstract
Three manufacturers sell artificial pancreas systems in the United States for management of Type 1 Diabetes. Given the life-saving task required of an artificial pancreas there needs to be a high level of trust and safety in the devices. This evaluation sought to find the adjusted safety event reporting rate and themes along with device-associated risk in events reported utilizing the MAUDE database. We searched device names in the MAUDE database over the period from 2016 until August 2023 (the date of retrieval). Thematic analysis was performed using dual-reviewer examination with a 96% concurrence. Relative risk (RR) was calculated for injury, malfunction, and overall, for each manufacturer, as well as adjusted event rate per manufacturer. Most events reported related to defects in the manufacturing of the casing materials which resulted in non-delivery of therapy. Tandem Diabetes Care, Inc. had an adjusted event rate of 50 per 100,000 units and RR of 0.0225. Insulet had an adjusted event rate of 300 per 100,000 units and RR of 0.1684. Medtronic has an adjusted event rate of 2771.43 per 100,000 units and RR of 20.7857. The newer Medtronic devices show improvements in likely event rate. While the artificial pancreas is still in its infancy, these event rates are not at an acceptable level for a device which can precipitate death from malfunctions. Further exploration into safety events and much more research and development is needed for devices to reduce the event rates. Improved manufacturing practices, especially the casing materials, are highly recommended. The artificial pancreas holds promise for millions but must be improved before it becomes a true life-saving device that it has the potential to become.
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Affiliation(s)
- Andrew M Ferguson
- University of Cincinnati College of Medicine, Cincinnati, USA.
- University of Cincinnati College of Pharmacy, Cincinnati, USA.
| | - Alex C Lin
- University of Cincinnati College of Pharmacy, Cincinnati, USA
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10
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Polderman J, Hermanides J, Hulst A. Update on the perioperative management of diabetes mellitus. BJA Educ 2024; 24:261-269. [PMID: 39099754 PMCID: PMC11293569 DOI: 10.1016/j.bjae.2024.04.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/23/2024] [Indexed: 08/06/2024] Open
Affiliation(s)
- J.A.W. Polderman
- Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - J. Hermanides
- Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | - A.H. Hulst
- Amsterdam University Medical Centres, Amsterdam, The Netherlands
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11
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Mameli C, Smylie GM, Marigliano M, Zagaroli L, Mancioppi V, Maffeis C, Salpietro V, Zuccotti G, Delvecchio M. Safety and Psychological Outcomes of Tandem t:Slim X2 Insulin Pump with Control-IQ Technology in Children, Adolescents, and Young Adults with Type 1 Diabetes: A Systematic Review. Diabetes Ther 2024:10.1007/s13300-024-01618-2. [PMID: 39008237 DOI: 10.1007/s13300-024-01618-2] [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] [Received: 05/31/2024] [Accepted: 06/26/2024] [Indexed: 07/16/2024] Open
Abstract
The Tandem t:slim X2 insulin pump is a second-generation automated insulin delivery system with Control-IQ technology. It consists of an X2 insulin pump, an integrated Dexcom sensor, and an embedded 'Control-IQ' algorithm, which predicts glucose levels 30 min in the future, adapting the programmed basal insulin rates to get glucose levels between 112.5 and 160 mg/dl (8.9 mmol/l). The system delivers automatic correction boluses of insulin when glucose levels are predicted to rise > 180 mg/dl (10 mmol/l). It has been commercially available since 2016. We reviewed the current evidence about the psychological, safety, and exercise-related outcomes of this device in children, adolescents, and young adults living with type 1 diabetes. We screened 552 papers, but only 21 manuscripts were included in this review. Fear of hypoglycemia is significantly reduced in young people with diabetes and their parents. Interestingly, diabetes-related distress is decreased; thus, the system is well accepted by the users. The sleeping quality of subjects living with diabetes and their caregivers is improved to a lesser extent as well. Despite the small number of data, this system is associated with a low rate of exercise-related hypoglycemia. Finally, evidence from the literature shows that this system is safe and effective in improving psychological personal outcomes. Even if further steps toward the fully closed loop are still mandatory, this second-generation automated insulin delivery system reduces the burden of diabetes. It properly addresses most psychological issues in children, adolescents, and young adults with type 1 diabetes mellitus; thus, it appears to be well accepted.
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Affiliation(s)
- Chiara Mameli
- Department of Pediatrics, Buzzi Children's Hospital, Milan, Italy
- Department of Biomedical and Clinical Science, Università Di Milano, Milan, Italy
| | | | - Marco Marigliano
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Luca Zagaroli
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Valentina Mancioppi
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Claudio Maffeis
- Department of Surgery, Dentistry, Pediatrics, and Gynecology, Section of Pediatric Diabetes and Metabolism, University and Azienda Ospedaliera, Universitaria Integrata of Verona, Verona, Italy
| | - Vincenzo Salpietro
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, Buzzi Children's Hospital, Milan, Italy
- Department of Biomedical and Clinical Science, Università Di Milano, Milan, Italy
| | - Maurizio Delvecchio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
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12
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DeRidder LB, Hare KA, Lopes A, Jenkins J, Fitzgerald N, MacPherson E, Fabian N, Morimoto J, Chu JN, Kirtane AR, Madani W, Ishida K, Kuosmanen JLP, Zecharias N, Colangelo CM, Huang HW, Chilekwa M, Lal NB, Srinivasan SS, Hayward AM, Wolpin BM, Trumper D, Quast T, Rubinson DA, Langer R, Traverso G. Closed-loop automated drug infusion regulator: A clinically translatable, closed-loop drug delivery system for personalized drug dosing. MED 2024; 5:780-796.e10. [PMID: 38663403 DOI: 10.1016/j.medj.2024.03.020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 01/26/2024] [Accepted: 03/21/2024] [Indexed: 07/15/2024]
Abstract
BACKGROUND Dosing of chemotherapies is often calculated according to the weight and/or height of the patient or equations derived from these, such as body surface area (BSA). Such calculations fail to capture intra- and interindividual pharmacokinetic variation, which can lead to order of magnitude variations in systemic chemotherapy levels and thus under- or overdosing of patients. METHODS We designed and developed a closed-loop drug delivery system that can dynamically adjust its infusion rate to the patient to reach and maintain the drug's target concentration, regardless of a patient's pharmacokinetics (PK). FINDINGS We demonstrate that closed-loop automated drug infusion regulator (CLAUDIA) can control the concentration of 5-fluorouracil (5-FU) in rabbits according to a range of concentration-time profiles (which could be useful in chronomodulated chemotherapy) and over a range of PK conditions that mimic the PK variability observed clinically. In one set of experiments, BSA-based dosing resulted in a concentration 7 times above the target range, while CLAUDIA keeps the concentration of 5-FU in or near the targeted range. Further, we demonstrate that CLAUDIA is cost effective compared to BSA-based dosing. CONCLUSIONS We anticipate that CLAUDIA could be rapidly translated to the clinic to enable physicians to control the plasma concentration of chemotherapy in their patients. FUNDING This work was supported by MIT's Karl van Tassel (1925) Career Development Professorship and Department of Mechanical Engineering and the Bridge Project, a partnership between the Koch Institute for Integrative Cancer Research at MIT and the Dana-Farber/Harvard Cancer Center.
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Affiliation(s)
- Louis B DeRidder
- Harvard-MIT Division of Health Science Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Kyle A Hare
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Aaron Lopes
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Josh Jenkins
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nina Fitzgerald
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Emmeline MacPherson
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Niora Fabian
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Josh Morimoto
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jacqueline N Chu
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Harvard Medical School, Boston, MA 02115, USA; Division of Gastroenterology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Ameya R Kirtane
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Wiam Madani
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Keiko Ishida
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Johannes L P Kuosmanen
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Naomi Zecharias
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Hen-Wei Huang
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Makaya Chilekwa
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Nikhil B Lal
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Shriya S Srinivasan
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Alison M Hayward
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Division of Comparative Medicine, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Brian M Wolpin
- Harvard Medical School, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - David Trumper
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Troy Quast
- College of Public Health, University of South Florida, Tampa, FL 33612, USA
| | - Douglas A Rubinson
- Harvard Medical School, Boston, MA 02115, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA 02215, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Robert Langer
- Harvard-MIT Division of Health Science Technology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Giovanni Traverso
- David H. Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA; Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA.
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13
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Scully KJ, Marks BE, Putman MS. Advances in diabetes technology to improve the lives of people with cystic fibrosis. Diabetologia 2024:10.1007/s00125-024-06223-3. [PMID: 38995399 DOI: 10.1007/s00125-024-06223-3] [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: 02/27/2024] [Accepted: 05/17/2024] [Indexed: 07/13/2024]
Abstract
People with cystic fibrosis (CF) are at risk for dysglycaemia caused by progressive beta cell dysfunction and destruction due to pancreatic exocrine disease and fibrosis. CF-related diabetes (CFRD) is a unique form of diabetes that has distinctive features from both type 1 and type 2 diabetes. Recent advances in diabetes technology may be of particular benefit in this population given the complex, multi-system organ involvement and challenging health issues that people with CFRD often face. This review summarises how diabetes technologies, such as continuous glucose monitors (CGMs) and insulin delivery devices: (1) have improved our understanding of CFRD, including how hyperglycaemia affects clinical outcomes in people with CF; (2) may be helpful in the screening and diagnosis of CFRD; and (3) offer promise for improving the management of CFRD and easing the burden that this diagnosis can add to an already medically complicated patient population.
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Affiliation(s)
- Kevin J Scully
- Hasbro Children's Hospital, Warren Alpert School of Medicine, Providence, RI, USA
| | - Brynn E Marks
- Children's Hospital of Philadelphia, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Melissa S Putman
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA.
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14
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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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15
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Rosselot C, Li Y, Wang P, Alvarsson A, Beliard K, Lu G, Kang R, Li R, Liu H, Gillespie V, Tzavaras N, Kumar K, DeVita RJ, Stewart AF, Stanley SA, Garcia-Ocaña A. Harmine and exendin-4 combination therapy safely expands human β cell mass in vivo in a mouse xenograft system. Sci Transl Med 2024; 16:eadg3456. [PMID: 38985854 DOI: 10.1126/scitranslmed.adg3456] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Accepted: 06/18/2024] [Indexed: 07/12/2024]
Abstract
Five hundred thirty-seven million people globally suffer from diabetes. Insulin-producing β cells are reduced in number in most people with diabetes, but most individuals still have some residual β cells. However, none of the many diabetes drugs in common use increases human β cell numbers. Recently, small molecules that inhibit dual tyrosine-regulated kinase 1A (DYRK1A) have been shown to induce immunohistochemical markers of human β cell replication, and this is enhanced by drugs that stimulate the glucagon-like peptide 1 (GLP1) receptor (GLP1R) on β cells. However, it remains to be demonstrated whether these immunohistochemical findings translate into an actual increase in human β cell numbers in vivo. It is also unknown whether DYRK1A inhibitors together with GLP1R agonists (GLP1RAs) affect human β cell survival. Here, using an optimized immunolabeling-enabled three-dimensional imaging of solvent-cleared organs (iDISCO+) protocol in mouse kidneys bearing human islet grafts, we demonstrate that combination of a DYRK1A inhibitor with exendin-4 increases actual human β cell mass in vivo by a mean of four- to sevenfold in diabetic and nondiabetic mice over 3 months and reverses diabetes, without alteration in human α cell mass. The augmentation in human β cell mass occurred through mechanisms that included enhanced human β cell proliferation, function, and survival. The increase in human β cell survival was mediated, in part, by the islet prohormone VGF. Together, these findings demonstrate the therapeutic potential and favorable preclinical safety profile of the DYRK1A inhibitor-GLP1RA combination for diabetes treatment.
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Affiliation(s)
- Carolina Rosselot
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yansui Li
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Peng Wang
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Alexandra Alvarsson
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kara Beliard
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Geming Lu
- Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope Beckman Research Institute, Duarte, CA 91010, USA
| | - Randy Kang
- Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope Beckman Research Institute, Duarte, CA 91010, USA
| | - Rosemary Li
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Hongtao Liu
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Virginia Gillespie
- Center for Comparative Medicine and Surgery, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Nikolaos Tzavaras
- Microscopy CoRE and Advanced Bioimaging Center, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Kunal Kumar
- Drug Discovery Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Robert J DeVita
- Drug Discovery Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Andrew F Stewart
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Sarah A Stanley
- Diabetes, Obesity and Metabolism Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
- Nash Family Department of Neuroscience and Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Adolfo Garcia-Ocaña
- Department of Molecular and Cellular Endocrinology, Arthur Riggs Diabetes and Metabolism Research Institute, City of Hope Beckman Research Institute, Duarte, CA 91010, USA
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16
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Julla JB, Jacquemier P, Bonnemaison E, Fagherazzi G, Hanaire H, Bellicar Schaepelynck P, Mihaileanu M, Renard E, Reznik Y, Riveline JP. Assessment of the Impact of Subcutaneous Catheter Change on Glucose Control in Patients with Type 1 Diabetes Treated by Insulin Pump in Open- and Closed-Loop Modes. Diabetes Technol Ther 2024; 26:442-448. [PMID: 38350126 DOI: 10.1089/dia.2023.0568] [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: 02/15/2024]
Abstract
Introduction: Most continuous subcutaneous insulin infusion (CSII) catheters (KT) are changed every 3 days. This study aims at evaluating whether KT changes impact glucose control while under open-loop (OL) or automated insulin delivery (AID) modes. Methods: We included patients with type 1 diabetes who used Tandem t:slim x2 insulin pump and Dexcom G6 glucose sensor for 20 days in OL, then as AID. CSII and sensor glucose data in OL and for the past 20 days of 3-month AID were retrospectively analyzed. The percentage of time spent with sensor glucose above 180 mg/dL (%TAR180) was compared between the calendar day of KT change (D0), the next day (D1), and 2 days later (D2). Values were adjusted for age, gender, body mass index (BMI), hemoglobin A1c (HbA1c) at inclusion, and %TAR180 for the 2 h before KT change. Results: A total of 1636 KT changes were analyzed in 134 patients: 72 women (54%), age: 35.6 ± 15.7 years, BMI: 25.2 ± 4.7 kg/m2, and HbA1c: 7.5 ± 0.8%. %TAR180 in the 2 h before the KT change was 51.3 ± 37.0% in OL and 33.2 ± 30.0% in AID mode. In OL, significant absolute increases of %TAR180 at D0 versus D1 (+6.9%; P < 0.0001) or versus D2 (+6.8%; P < 0.0001) were observed. In AID, significant absolute increases of %TA180R at D0 versus D1 (+4.8%; P < 0.0001) or versus D2 (+4.2%; P < 0.0001) were also observed. Conclusion: This study shows an increase in time spent in hyperglycemia on the day of the KT change both in OL and AID modes. This additional information should be taken into account to improve current AID algorithms. ClinicalTrials.gov: NCT04939766.
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Affiliation(s)
- Jean-Baptiste Julla
- Department of Endocrinology and Diabetes, Centre Universitaire du diabète et de ses complications, APHP, Hôpital Lariboisière, Université Paris-Cité, Paris, Île-de-France, France
- Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
| | - Pauline Jacquemier
- Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Centre Explor, ALHIST-Air Liquide Healthcare, Bagneux, France
| | | | - Guy Fagherazzi
- Luxembourg Institute of Health, Deep Digital Phenotyping Research Unit, Department of Precision Health, Strassen, Luxembourg
| | - Hélène Hanaire
- Department of Diabetology, Rangueil, Toulouse University Hospital, Toulouse, France
| | | | | | - Eric Renard
- Department of Endocrinology and Diabetes, Montpellier University Hospital, Montpellier, France and Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Yves Reznik
- Department of Endocrinology and Diabetes, CHU Côte de Nacre, Caen Cedex, France and Unicaen, Caen Cedex, France
| | - Jean-Pierre Riveline
- Department of Endocrinology and Diabetes, Centre Universitaire du diabète et de ses complications, APHP, Hôpital Lariboisière, Université Paris-Cité, Paris, Île-de-France, France
- Institut Necker Enfants Malades, INSERM U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
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Jalilova A, Pilan BŞ, Demir G, Özbaran B, Balkı HG, Arslan E, Köse SG, Özen S, Darcan Ş, Gökşen D. The psychosocial outcomes of advanced hybrid closed-loop system in children and adolescents with type 1 diabetes. Eur J Pediatr 2024; 183:3095-3103. [PMID: 38661816 PMCID: PMC11192657 DOI: 10.1007/s00431-024-05551-1] [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: 02/06/2024] [Revised: 03/14/2024] [Accepted: 03/30/2024] [Indexed: 04/26/2024]
Abstract
The study was carried out to determine the psychosocial outcomes of advanced hybrid closed-loop (AHCL) systems in children and adolescents with type 1 diabetes (T1D). Single-center and cohort study with a duration 6 months consisted of 60 children and adolescents with T1D. Standard clinical procedures, including both glycemic indicators, e.g., sensor-measured time within the 70-180 mg/dL range and glycated hemoglobin (HbA1c) levels, and psychosocial metrics were used for data collection. The psychosocial metrics included the Pediatric Quality of Life Inventory (PedsQL) 3.0 Diabetes Module for both children (8-12 years) and parents; the Quality of Life for Youth scale for adolescents (13-18 years); the Strengths and Difficulties Questionnaire (SDQ); the Hypoglycemia Fear Survey for Children (HFS-C); the Revised Child Anxiety and Depression Scale (R-CADS); and AHCLS-specific DTSEQ satisfaction and expectation survey. These metrics were evaluated at the baseline and after 6 months of AHCL use. Of the 60 children and adolescents with T1D for whom the AHCL system was utilized, 41 of them, 23 female and 18 male, completed the surveys. The mean age of the 41 children and adolescents was 12.5 ± 3.2 (min. 6.7, max. 18) years. The time spent within the target glycemic range, i.e., time-in-range (TIR), improved from 76.9 ± 9% at the baseline to 80.4 ± 5% after 6 months of AHCL system use (p = 0.03). Additionally, HbA1c levels reduced from 7.1% ± 0.7% at the baseline to 6.8% ± 0.8% after 6 months of AHCL system use (p = 0.03). The most notable decline in HbA1c was observed in participants with higher baseline HbA1c levels. All patients' HFS-C and AHCL system-specific DTSEQ satisfaction and expectation survey scores were within the normal range at the baseline and remained unchanged during the follow-up period. No significant difference was found in the R-CADS scores of children and adolescents between baseline and after 6 months of AHCL system use. However, there was a significant decrease in the R-CADS scores of the parents. Patients' PedsQL scores were high both at the baseline and after 6 months. The SDQ scores were high at baseline, and there was no significant improvement at the end of 6 months. Conclusion: This is the first study to investigate in detail the psychosocial outcomes of AHCL system use in T1D patients and their parents. Although state-of-the-art technologies such as AHCL provide patients with more flexibility in their daily lives and information about glucose fluctuations, the AHCL resulted in a TIR above the recommended target range without a change in QOL, HFS-C, SDQ, and R-CADS scores. The scores obtained from the R-CADS conducted by the parents of the children indicated that the use of pumps caused a psychological improvement in the long term, with a significant decrease in the R-CADS scores of the children and adolescents with T1D. What is Known: • Previous studies focused on clinical outcomes of AHCL systems in pediatric T1D patients, showing glycemic control improvements. • Limited attention given to psychosocial outcomes of AHCL systems in children and adolescents with T1D. • Crucial psychosocial factors like quality of life, emotional well-being, and fear of hypoglycemia underexplored in AHCL system context. What is New: • First study to comprehensively examine psychosocial outcomes of AHCL systems in pediatric T1D patients. • Study's robust methodology sets new standard for diabetes technology research and its impact on qualiy of life.
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Affiliation(s)
- Arzu Jalilova
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey.
| | - Birsen Şentürk Pilan
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Günay Demir
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Burcu Özbaran
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Hanife Gul Balkı
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Emrullah Arslan
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Sezen Gökcen Köse
- Department of Child and Adolescent Psychiatry, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Samim Özen
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Şükran Darcan
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
| | - Damla Gökşen
- Department of Pediatric Endocrinology, Faculty of Medicine, Ege University, Izmir, Turkey
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18
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Kim JY, Jin SM, Kang ES, Kwak SH, Yang Y, Yoo JH, Bae JH, Moon JS, Jung CH, Bae JC, Suh S, Moon SJ, Song SO, Chon S, Kim JH. Comparison between a tubeless, on-body automated insulin delivery system and a tubeless, on-body sensor-augmented pump in type 1 diabetes: a multicentre randomised controlled trial. Diabetologia 2024; 67:1235-1244. [PMID: 38634887 DOI: 10.1007/s00125-024-06155-y] [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: 12/31/2023] [Accepted: 03/05/2024] [Indexed: 04/19/2024]
Abstract
AIMS/HYPOTHESIS This study compares the efficacy and safety of a tubeless, on-body automated insulin delivery (AID) system with that of a tubeless, on-body sensor-augmented pump (SAP). METHODS This multicentre, parallel-group, RCT was conducted at 13 tertiary medical centres in South Korea. Adults aged 19-69 years with type 1 diabetes who had HbA1c levels of <85.8 mmol/mol (<10.0%) were eligible. The participants were assigned at a 1:1 ratio to receive a tubeless, on-body AID system (intervention group) or a tubeless, on-body SAP (control group) for 12 weeks. Stratified block randomisation was conducted by an independent statistician. Blinding was not possible due to the nature of the intervention. The primary outcome was the percentage of time in range (TIR), blood glucose between 3.9 and 10.0 mmol/l, as measured by continuous glucose monitoring. ANCOVAs were conducted with baseline values and study centres as covariates. RESULTS A total of 104 participants underwent randomisation, with 53 in the intervention group and 51 in the control group. The mean (±SD) age of the participants was 40±11 years. The mean (±SD) TIR increased from 62.1±17.1% at baseline to 71.5±10.7% over the 12 week trial period in the intervention group and from 64.7±17.0% to 66.9±15.0% in the control group (difference between the adjusted means: 6.5% [95% CI 3.6%, 9.4%], p<0.001). Time below range, time above range, CV and mean glucose levels were also significantly better in the intervention group compared with the control group. HbA1c decreased from 50.9±9.9 mmol/mol (6.8±0.9%) at baseline to 45.9±7.4 mmol/mol (6.4±0.7%) after 12 weeks in the intervention group and from 48.7±9.1 mmol/mol (6.6±0.8%) to 45.7±7.5 mmol/mol (6.3±0.7%) in the control group (difference between the adjusted means: -0.7 mmol/mol [95% CI -2.0, 0.8 mmol/mol] (-0.1% [95% CI -0.2%, 0.1%]), p=0.366). No diabetic ketoacidosis or severe hypoglycaemia events occurred in either group. CONCLUSIONS/INTERPRETATION The use of a tubeless, on-body AID system was safe and associated with superior glycaemic profiles, including TIR, time below range, time above range and CV, than the use of a tubeless, on-body SAP. TRIAL REGISTRATION Clinical Research Information Service (CRIS) KCT0008398 FUNDING: The study was funded by a grant from the Korea Medical Device Development Fund supported by the Ministry of Science and ICT; the Ministry of Trade, Industry and Energy; the Ministry of Health and Welfare; and the Ministry of Food and Drug Safety (grant number: RS-2020-KD000056).
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Affiliation(s)
- Ji Yoon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sang-Man Jin
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Eun Seok Kang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Soo Heon Kwak
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Yeoree Yang
- Division of Endocrinology, Department of Internal Medicine, Seoul St Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea
| | - Jee Hee Yoo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Jae Hyun Bae
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
| | - Jun Sung Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Republic of Korea
| | - Chang Hee Jung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
| | - Ji Cheol Bae
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea
| | - Sunghwan Suh
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Changwon Hospital, Sungkyunkwan University School of Medicine, Changwon, Republic of Korea
| | - Sun Joon Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Sun Ok Song
- Division of Endocrinology and Metabolism, Department of Internal Medicine, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea
| | - Suk Chon
- Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
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19
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Wilkinson TM, de Bock M. Analysis of "Hybrid Closed Loop Using a Do-It-Yourself Artificial Pancreas System in Adults With Type 1 Diabetes". J Diabetes Sci Technol 2024; 18:897-898. [PMID: 37850586 DOI: 10.1177/19322968231208216] [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: 10/19/2023]
Abstract
In an article in Journal of Diabetes Science and Technology, Nanayakkara and colleagues assessed the glycemic efficacy and safety of AndroidAPS, an open-source automated delivery (AID) system, in a crossover randomized controlled trial. Although the trial included only 20 participants during a relatively short 4-week intervention period, glycemic outcomes attained were similar to commercial AID systems and there were no safety concerns. Validation of open-source AID systems in studies such as this should help address clinician hesitancy regarding these systems, and affirms the role of patient-centered innovation and self-management in diabetes care.
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Affiliation(s)
- Tom M Wilkinson
- Department of Paediatrics, University of Otago, Christchurch, Christchurch, New Zealand
| | - Martin de Bock
- Department of Paediatrics, University of Otago, Christchurch, Christchurch, New Zealand
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20
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Galindo RJ, Aleppo G, Parkin CG, Baidal DA, Carlson AL, Cengiz E, Forlenza GP, Kruger DF, Levy C, McGill JB, Umpierrez GE. Increase Access, Reduce Disparities: Recommendations for Modifying Medicaid CGM Coverage Eligibility Criteria. J Diabetes Sci Technol 2024; 18:974-987. [PMID: 36524477 DOI: 10.1177/19322968221144052] [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: 12/23/2022]
Abstract
Numerous studies have demonstrated the clinical value of continuous glucose monitoring (CGM) in type 1 diabetes (T1D) and type 2 diabetes (T2D) populations. However, the eligibility criteria for CGM coverage required by the Centers for Medicare & Medicaid Services (CMS) ignore the conclusive evidence that supports CGM use in various diabetes populations that are currently deemed ineligible. In an earlier article, we discussed the limitations and inconsistencies of the agency's CGM eligibility criteria relative to current scientific evidence and proposed practice solutions to address this issue and improve the safety and care of Medicare beneficiaries with diabetes. Although Medicaid is administered through CMS, there is no consistent Medicaid policy for CGM coverage in the United States. This article presents a rationale for modifying and standardizing Medicaid CGM coverage eligibility across the United States.
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Affiliation(s)
- Rodolfo J Galindo
- Emory University School of Medicine, Atlanta, GA, USA
- Center for Diabetes Metabolism Research, Emory University Hospital Midtown, Atlanta, GA, USA
- Hospital Diabetes Taskforce, Emory Healthcare System, Atlanta, GA, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | | | - David A Baidal
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Anders L Carlson
- International Diabetes Center, Minneapolis, MN, USA
- Regions Hospital & HealthPartners Clinics, St. Paul, MN, USA
- Diabetes Education Programs, HealthPartners and Stillwater Medical Group, Stillwater, MN, USA
- University of Minnesota Medical School, Minneapolis, MN, USA
| | - Eda Cengiz
- Pediatric Diabetes Program, Division of Pediatric Endocrinology, Department of Pediatrics, University of California, San Francisco, San Francisco, CA, USA
| | - Gregory P Forlenza
- Barbara Davis Center, Division of Pediatric Endocrinology, Department of Pediatrics, University of Colorado Denver, Denver, CO, USA
| | - Davida F Kruger
- Division of Endocrinology, Diabetes, Bone & Mineral, Henry Ford Health System, Detroit, MI, USA
| | - Carol Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Mount Sinai Diabetes Center and T1D Clinical Research, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Janet B McGill
- Division of Endocrinology, Metabolism & Lipid Research, School of Medicine, Washington University in St. Louis, St. Louis, MO, USA
| | - Guillermo E Umpierrez
- Division of Endocrinology, Metabolism, Emory University School of Medicine, Atlanta, GA, USA
- Diabetes and Endocrinology, Grady Memorial Hospital, Atlanta, GA, USA
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21
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Ware J, Wilinska ME, Ruan Y, Allen JM, Boughton CK, Hartnell S, Bally L, de Beaufort C, Besser REJ, Campbell FM, Draxlbauer K, Elleri D, Evans ML, Fröhlich-Reiterer E, Ghatak A, Hofer SE, Kapellen TM, Leelarathna L, Mader JK, Mubita WM, Narendran P, Poettler T, Rami-Merhar B, Tauschmann M, Randell T, Thabit H, Thankamony A, Trevelyan N, Hovorka R. Safety of User-Initiated Intensification of Insulin Delivery Using Cambridge Hybrid Closed-Loop Algorithm. J Diabetes Sci Technol 2024; 18:882-888. [PMID: 36475908 DOI: 10.1177/19322968221141924] [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: 12/13/2022]
Abstract
OBJECTIVE Many hybrid closed-loop (HCL) systems struggle to manage unusually high glucose levels as experienced with intercurrent illness or pre-menstrually. Manual correction boluses may be needed, increasing hypoglycemia risk with overcorrection. The Cambridge HCL system includes a user-initiated algorithm intensification mode ("Boost"), activation of which increases automated insulin delivery by approximately 35%, while remaining glucose-responsive. In this analysis, we assessed the safety of "Boost" mode. METHODS We retrospectively analyzed data from closed-loop studies involving young children (1-7 years, n = 24), children and adolescents (10-17 years, n = 19), adults (≥24 years, n = 13), and older adults (≥60 years, n = 20) with type 1 diabetes. Outcomes were calculated per participant for days with ≥30 minutes of "Boost" use versus days with no "Boost" use. Participants with <10 "Boost" days were excluded. The main outcome was time spent in hypoglycemia <70 and <54 mg/dL. RESULTS Eight weeks of data for 76 participants were analyzed. There was no difference in time spent <70 and <54 mg/dL between "Boost" days and "non-Boost" days; mean difference: -0.10% (95% confidence interval [CI] -0.28 to 0.07; P = .249) time <70 mg/dL, and 0.03 (-0.04 to 0.09; P = .416) time < 54 mg/dL. Time in significant hyperglycemia >300 mg/dL was 1.39 percentage points (1.01 to 1.77; P < .001) higher on "Boost" days, with higher mean glucose and lower time in target range (P < .001). CONCLUSIONS Use of an algorithm intensification mode in HCL therapy is safe across all age groups with type 1 diabetes. The higher time in hyperglycemia observed on "Boost" days suggests that users are more likely to use algorithm intensification on days with extreme hyperglycemic excursions.
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Affiliation(s)
- Julia Ware
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Malgorzata E Wilinska
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Yue Ruan
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Janet M Allen
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Charlotte K Boughton
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Sara Hartnell
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, Bern, Switzerland
| | - Carine de Beaufort
- Diabetes & Endocrine Care Clinique Pediatrique, Centre Hospitalier de Luxembourg, Luxembourg City, Luxembourg
- Department of Paediatric Endocrinology, UZ-VUB, Brussels, Belgium
| | - Rachel E J Besser
- NIHR Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
- Department of Paediatrics, University of Oxford, Oxford, UK
| | - Fiona M Campbell
- Department of Paediatric Diabetes, Leeds Children's Hospital, Leeds, UK
| | | | - Daniela Elleri
- Department of Diabetes, Royal Hospital for Sick Children, Edinburgh, UK
| | - Mark L Evans
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes and Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Elke Fröhlich-Reiterer
- Department of Pediatric and Adolescent Medicine, Medical University of Graz, Graz, Austria
| | - Atrayee Ghatak
- Department of Diabetes, Alder Hey Children's NHS Foundation Trust, Liverpool, UK
| | - Sabine E Hofer
- Department of Pediatrics I, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas M Kapellen
- Hospital for Children and Adolescents, Leipzig University, Leipzig, Germany
| | - Lalantha Leelarathna
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Diabetes, Endocrinology & Gastroenterology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Julia K Mader
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Womba M Mubita
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Parth Narendran
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK
- Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK
| | - Tina Poettler
- Division of Endocrinology and Diabetology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Birgit Rami-Merhar
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Martin Tauschmann
- Department of Paediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Tabitha Randell
- Department of Paediatric Diabetes and Endocrinology, Nottingham Children's Hospital, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Hood Thabit
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
- Division of Diabetes, Endocrinology & Gastroenterology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Nicola Trevelyan
- Department of Paediatric Endocrinology and Diabetes, Southampton Children's Hospital, Southampton General Hospital, Southampton, UK
| | - Roman Hovorka
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
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22
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Schiaffini R, Lumaca A, Martino M, Rapini N, Deodati A, Amodeo ME, Ciampalini P, Matteoli MC, Pampanini V, Cianfarani S. Time In Tight Range in children and adolescents with type 1 diabetes: A cross-sectional observational single centre study evaluating efficacy of new advanced technologies. Diabetes Metab Res Rev 2024; 40:e3826. [PMID: 38824455 DOI: 10.1002/dmrr.3826] [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: 01/03/2024] [Revised: 03/16/2024] [Accepted: 04/22/2024] [Indexed: 06/03/2024]
Abstract
INTRODUCTION Early and tight glycaemic control is crucial to prevent long-term complications of Type 1 Diabetes (T1D). The aim of our study was to compare glucose metrics, including Time In Tight Range (TITR), in a real-world setting. METHODS We performed a single-centre cross-sectional study in 534 children and adolescents with T1D. Participants were divided into four groups (multiple daily injections + real-time Continuous glucose monitoring (CGM), multiple daily injections + intermittently scanned CGM, sensor augmented pump (SAP), and Advanced Hybrid Closed-Loop (AHCL). Demographical and clinical data were collected and analysed. RESULTS The group with AHCL showed significantly higher Time In Range (TIR) (71.31% ± 10.88) than SAP (57.82% ± 14.98; p < 0.001), MDI + rtCGM (54.56% ± 17.04; p < 0.001) and MDI + isCGM (52.17% ± 19.36; p < 0.001) groups with a lower Time Above Range (p < 0.001). The group with AHCL also showed lower Time Below Range than MDI + isCGM and SAP groups (p < 0.01). The overall TITR was 37% ± 14 with 19% of participants who reached a TITR ≥50% with a mean TIR of 81%. AHCL had significantly higher TITR (45.46% ± 11.77) than SAP (36.25% ± 13.53; p < 0.001), MDI + rtCGM (34.03% ± 13.89; p < 0.001) and MDI + isCGM (33.37% ± 15.84; p < 0.001) groups with a lower Coefficient of Variation (p < 0.001). CONCLUSIONS Our study indicates that AHCL ensures a better glycaemic control with an improvement in both TIR and TITR, along with a reduction in CV. Implementation of automated insulin delivery systems should be considered in the treatment of children and adolescents with T1D.
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Affiliation(s)
- Riccardo Schiaffini
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Alessandra Lumaca
- Pediatric Unit - Azienda Ospedaliero-Universitaria S. Anna - Via Aldo Moro, Ferrara, Italy
| | - Mariangela Martino
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
- University of Rome 'Tor Vergata', Rome, Italy
| | - Novella Rapini
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Annalisa Deodati
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
- Department of Systems Medicine, University of Rome 'Tor Vergata', Rome, Italy
| | - Maria Elisa Amodeo
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Paolo Ciampalini
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Maria Cristina Matteoli
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Valentina Pampanini
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
| | - Stefano Cianfarani
- Endocrine and Diabetes Unit - Bambino Gesù Childrens' Hospital - IRCCS-Piazza S Onofrio, Rome, Italy
- Department of Systems Medicine, University of Rome 'Tor Vergata', Rome, Italy
- Department of Women's and Children's Health, Karolinska Institutet, Stockholm, Sweden
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23
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Moon JS, Kang S, Choi JH, Lee KA, Moon JH, Chon S, Kim DJ, Kim HJ, Seo JA, Kim MK, Lim JH, Song YJ, Yang YS, Kim JH, Lee YB, Noh J, Hur KY, Park JS, Rhee SY, Kim HJ, Kim HM, Ko JH, Kim NH, Kim CH, Ahn J, Oh TJ, Kim SK, Kim J, Han E, Jin SM, Bae J, Jeon E, Kim JM, Kang SM, Park JH, Yun JS, Cha BS, Moon MK, Lee BW. 2023 Clinical Practice Guidelines for Diabetes Management in Korea: Full Version Recommendation of the Korean Diabetes Association. Diabetes Metab J 2024; 48:546-708. [PMID: 39091005 DOI: 10.4093/dmj.2024.0249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2024] [Accepted: 06/20/2024] [Indexed: 08/04/2024] Open
Affiliation(s)
- Jun Sung Moon
- Department of Internal Medicine, Yeungnam University College of Medicine, Daegu, Korea
| | - Shinae Kang
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Jong Han Choi
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Konkuk University Medical Center, Konkuk University School of Medicine, Seoul, Korea
| | - Kyung Ae Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Jeonbuk National University Hospital, Jeonbuk National University Medical School, Jeonju, Korea
| | - Joon Ho Moon
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Suk Chon
- Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, Seoul, Korea
| | - Dae Jung Kim
- Department of Endocrinology and Metabolism, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea
| | - Hyun Jin Kim
- Department of Internal Medicine, Chungnam National University Hospital, Chungnam National University College of Medicine, Daejeon, Korea
| | - Ji A Seo
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University Ansan Hospital, Korea University College of Medicine, Ansan, Korea
| | - Mee Kyoung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yeouido St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Jeong Hyun Lim
- Department of Food Service and Nutrition Care, Seoul National University Hospital, Seoul, Korea
| | - Yoon Ju Song
- Department of Food Science and Nutrition, The Catholic University of Korea, Bucheon, Korea
| | - Ye Seul Yang
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - You-Bin Lee
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Junghyun Noh
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Inje University Ilsan Paik Hospital, Inje University College of Medicine, Goyang, Korea
| | - Kyu Yeon Hur
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jong Suk Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, Korea
| | - Sang Youl Rhee
- Department of Endocrinology and Metabolism, College of Medicine, Kyung Hee University, Seoul, Korea
| | - Hae Jin Kim
- Department of Endocrinology and Metabolism, Ajou University Hospital, Ajou University School of Medicine, Suwon, Korea
| | - Hyun Min Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Chung-Ang University College of Medicine, Seoul, Korea
| | - Jung Hae Ko
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Inje University Haeundae Paik Hospital, Inje University College of Medicine, Busan, Korea
| | - Nam Hoon Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Chong Hwa Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Sejong General Hospital, Bucheon, Korea
| | - Jeeyun Ahn
- Department of Ophthalmology, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea
| | - Tae Jung Oh
- Department of Internal Medicine, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Soo-Kyung Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, CHA Bundang Medical Center, CHA University School of Medicine, Seongnam, Korea
| | - Jaehyun Kim
- Department of Pediatrics, Seoul National University Bundang Hospital, Seoul National University College of Medicine, Seongnam, Korea
| | - Eugene Han
- Department of Internal Medicine, Keimyung University School of Medicine, Daegu, Korea
| | - Sang-Man Jin
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jaehyun Bae
- Department of Internal Medicine, Hallym University Kangnam Sacred Heart Hospital, College of Medicine, Hallym University, Seoul, Korea
| | - Eonju Jeon
- Department of Internal Medicine, Daegu Catholic University School of Medicine, Daegu, Korea
| | - Ji Min Kim
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Chungnam National University College of Medicine, Daejeon, Korea
| | - Seon Mee Kang
- Department of Internal Medicine, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon, Korea
| | - Jung Hwan Park
- Division of Endocrinology & Metabolism, Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Korea
| | - Jae-Seung Yun
- Division of Endocrinology and Metabolism, Department of Internal Medicine, St. Vincent's Hospital, College of Medicine, The Catholic University of Korea, Suwon, Korea
| | - Bong-Soo Cha
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
| | - Min Kyong Moon
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul, Korea
| | - Byung-Wan Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea
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Andreadi A, Lodeserto P, Todaro F, Meloni M, Romano M, Minasi A, Bellia A, Lauro D. Nanomedicine in the Treatment of Diabetes. Int J Mol Sci 2024; 25:7028. [PMID: 39000136 PMCID: PMC11241380 DOI: 10.3390/ijms25137028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2024] [Revised: 06/16/2024] [Accepted: 06/25/2024] [Indexed: 07/16/2024] Open
Abstract
Nanomedicine could improve the treatment of diabetes by exploiting various therapeutic mechanisms through the use of suitable nanoformulations. For example, glucose-sensitive nanoparticles can release insulin in response to high glucose levels, mimicking the physiological release of insulin. Oral nanoformulations for insulin uptake via the gut represent a long-sought alternative to subcutaneous injections, which cause pain, discomfort, and possible local infection. Nanoparticles containing oligonucleotides can be used in gene therapy and cell therapy to stimulate insulin production in β-cells or β-like cells and modulate the responses of T1DM-associated immune cells. In contrast, viral vectors do not induce immunogenicity. Finally, in diabetic wound healing, local delivery of nanoformulations containing regenerative molecules can stimulate tissue repair and thus provide a valuable tool to treat this diabetic complication. Here, we describe these different approaches to diabetes treatment with nanoformulations and their potential for clinical application.
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Affiliation(s)
- Aikaterini Andreadi
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Pietro Lodeserto
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Federica Todaro
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
| | - Marco Meloni
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Maria Romano
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Alessandro Minasi
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Alfonso Bellia
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
| | - Davide Lauro
- Section of Endocrinology and Metabolic Diseases, Department of Systems Medicine, University of Rome Tor Vergata, 00133 Rome, Italy; (P.L.); (F.T.); (M.M.); (A.B.); (D.L.)
- Division of Endocrinology and Diabetology, Department of Medical Sciences, Fondazione Policlinico Tor Vergata, 00133 Rome, Italy; (M.R.); (A.M.)
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25
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Annicchiarico A, Barile B, Buccoliero C, Nicchia GP, Brunetti G. Alternative therapeutic strategies in diabetes management. World J Diabetes 2024; 15:1142-1161. [PMID: 38983831 PMCID: PMC11229975 DOI: 10.4239/wjd.v15.i6.1142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 02/17/2024] [Accepted: 04/12/2024] [Indexed: 06/11/2024] Open
Abstract
Diabetes is a heterogeneous metabolic disease characterized by elevated blood glucose levels resulting from the destruction or malfunction of pancreatic β cells, insulin resistance in peripheral tissues, or both, and results in a non-sufficient production of insulin. To adjust blood glucose levels, diabetic patients need exogenous insulin administration together with medical nutrition therapy and physical activity. With the aim of improving insulin availability in diabetic patients as well as ameliorating diabetes comorbidities, different strategies have been investigated. The first approaches included enhancing endogenous β cell activity or transplanting new islets. The protocol for this kind of intervention has recently been optimized, leading to standardized procedures. It is indicated for diabetic patients with severe hypoglycemia, complicated by impaired hypoglycemia awareness or exacerbated glycemic lability. Transplantation has been associated with improvement in all comorbidities associated with diabetes, quality of life, and survival. However, different trials are ongoing to further improve the beneficial effects of transplantation. Furthermore, to overcome some limitations associated with the availability of islets/pancreas, alternative therapeutic strategies are under evaluation, such as the use of mesenchymal stem cells (MSCs) or induced pluripotent stem cells for transplantation. The cotransplantation of MSCs with islets has been successful, thus providing protection against proinflammatory cytokines and hypoxia through different mechanisms, including exosome release. The use of induced pluripotent stem cells is recent and requires further investigation. The advantages of MSC implantation have also included the improvement of diabetes-related comorbidities, such as wound healing. Despite the number of advantages of the direct injection of MSCs, new strategies involving biomaterials and scaffolds have been developed to improve the efficacy of mesenchymal cell delivery with promising results. In conclusion, this paper offered an overview of new alternative strategies for diabetes management while highlighting some limitations that will need to be overcome by future approaches.
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Affiliation(s)
- Alessia Annicchiarico
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Barbara Barile
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Cinzia Buccoliero
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Grazia Paola Nicchia
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
| | - Giacomina Brunetti
- Department of Biosciences, Biotechnologies and Environment, University of Bari Aldo Moro, Bari 70125, Italy
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26
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Baxter F, Baillie N, Dover A, Stimson RH, Gibb F, Forbes S. A cross-sectional questionnaire study: Impaired awareness of hypoglycaemia remains prevalent in adults with type 1 diabetes and is associated with the risk of severe hypoglycaemia. PLoS One 2024; 19:e0297601. [PMID: 38875308 PMCID: PMC11178233 DOI: 10.1371/journal.pone.0297601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Accepted: 05/14/2024] [Indexed: 06/16/2024] Open
Abstract
OBJECTIVE Impaired awareness of hypoglycaemia (IAH) is a risk factor for severe hypoglycaemia (SH) in type 1 diabetes (T1D). Much of the IAH prevalence data comes from older studies where participants did not have the benefit of the latest insulins and technologies. This study surveyed the prevalence of IAH and SH in a tertiary adult clinic population and investigated the associated factors. METHODS Adults (≥18 years) attending a tertiary T1D clinic completed a questionnaire, including a Gold and Clarke score. Background information was collected from health records. RESULTS 189 people (56.1% female) with T1D (median [IQR] disease duration 19.3 [11.5, 29.1] years and age of 41.0 [29.0, 52.0] years) participated. 17.5% had IAH and 16.0% reported ≥1 episode of SH in the previous 12 months. Those with IAH were more likely to report SH (37.5% versus 11.7%, p = 0.001) a greater number of SH episodes per person (median [IQR] 0 [0,2] versus 0 [0,0] P<0.001) and be female (72.7% versus 52.6%, p = 0.036). Socio-economic deprivation was associated with IAH (p = 0.032) and SH (p = 0.005). Use of technology was the same between IAH vs aware groups, however, participants reporting SH were more likely to use multiple daily injections (p = 0.026). Higher detectable C-peptide concentrations were associated with a reduced risk of SH (p = 0.04). CONCLUSION Insulin pump and continuous glucose monitor use was comparable in IAH versus aware groups. Despite this, IAH remains a risk factor for SH and is prevalent in females and in older people. Socioeconomic deprivation was associated with IAH and SH, making this an important population to target for interventions.
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Affiliation(s)
- Faye Baxter
- BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicola Baillie
- BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Anna Dover
- Department of Diabetes and Endocrinology, Outpatient Department 2, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Roland H Stimson
- BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Department of Diabetes and Endocrinology, Outpatient Department 2, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Fraser Gibb
- Department of Diabetes and Endocrinology, Outpatient Department 2, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
| | - Shareen Forbes
- BHF Centre for Cardiovascular Science, Queen's Medical Research Institute, University of Edinburgh, Edinburgh, United Kingdom
- Department of Diabetes and Endocrinology, Outpatient Department 2, Royal Infirmary of Edinburgh, Edinburgh, United Kingdom
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27
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Fresa R, Bitterman O, Cavallaro V, Di Filippi M, Dimarzo D, Mosca C, Nappi F, Rispoli M, Napoli A. An automated insulin delivery system from pregestational care to postpartum in women with type 1 diabetes. Preliminary experience with telemedicine in 6 patients. Acta Diabetol 2024:10.1007/s00592-024-02315-z. [PMID: 38849658 DOI: 10.1007/s00592-024-02315-z] [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] [Received: 02/16/2024] [Accepted: 05/29/2024] [Indexed: 06/09/2024]
Abstract
INTRODUCTION The use of most commercially available automated insulin delivery (AID) systems is off-label in pregnancy. However, an increasing number of women with type 1 diabetes (T1D) use such devices throughout pregnancy and delivery. We analysed the data of six women with T1D from a single centre (Diabetology Outpatient Clinic of District-63/Asl Salerno, Italy) who were able to start and maintain AID therapy with the MiniMed™ 780G (Medtronic, Minneapolis, MN, USA) throughout the pregestational care period, pregnancy, delivery, and postpartum. METHODS We retrospectively collected data from six patients with T1D who received training and initiation on use of the MiniMed™ 780G and attended follow-up visits throughout pregnancy (these visits were virtual because of the COVID-19 pandemic). All patients maintained their devices in the closed-loop setting throughout pregnancy and during labour and delivery. We analysed data from the pregestational phase to the first 30 days postpartum. RESULTS All patients achieved the recommended metabolic goals before conception [median time in range (TIR) of 88% for 70-180 mg/dL; median pregnancy-specific TIR 63-140 mg/dL (ps-TIR) of 66% and maintained the ps-TIR until delivery (median ps-TIR 83%). All patients had slightly better metrics during the night than during the day, with a very low time below range of < 63 mg/dL. Optimal glycaemic values were also maintained on the day of labour and delivery (median ps-TIR 92.5%) and in the first 30 days postpartum, with no severe hypoglycaemia. The only neonatal complications were jaundice in one child and an interatrial defect in another child. CONCLUSION In our well-selected and trained patients, use of the MiniMed™ 780G helped to achieve and maintain ps-metrics from the pregestational period to delivery despite the fact that the algorithm is not set to achieve the ambitious glycaemic values recommended for pregnancy.
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Affiliation(s)
- Raffaella Fresa
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | - Olimpia Bitterman
- Diabetology Unit, San Paolo Hospital, ASL Roma 4, Civitavecchia, Rome, Italy.
| | - Vincenzo Cavallaro
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | | | - Daniela Dimarzo
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | - Carmela Mosca
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | - Francesca Nappi
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | - Marilena Rispoli
- Diabetology Outpatient Clinic , Asl Salerno, District 63, Salerno, Italy
| | - Angela Napoli
- Israelitico Hospital, Rome, Italy
- International Medical University Unicamillus, Rome, Italy
- Cdc Santa Famiglia, Rome, Italy
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28
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Scidà G, Corrado A, Abuqwider J, Lupoli R, Rainone C, Della Pepa G, Masulli M, Annuzzi G, Bozzetto L. Postprandial Glucose Control With Different Hybrid Closed-Loop Systems According to Type of Meal in Adults With Type 1 Diabetes. J Diabetes Sci Technol 2024:19322968241256475. [PMID: 38840523 DOI: 10.1177/19322968241256475] [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: 06/07/2024]
Abstract
BACKGROUND Hybrid Closed-Loop Systems (HCLs) may not perform optimally on postprandial glucose control. We evaluated how first-generation and advanced HCLs manage meals varying in carbohydrates, fat, and protein. METHOD According to a cross-sectional design, seven-day food records and HCLs reports from 120 adults with type 1 diabetes (MiniMed670G: n = 40, MiniMed780G: n = 49, Control-IQ [C-IQ]: n = 31) were analyzed. Breakfasts (n = 570), lunches (n = 658), and dinners (n = 619) were divided according to the median of their carbohydrate (g)/fat (g) plus protein (g) ratio (C/FP). After breakfast (4-hour), lunch (6-hour), and dinner (6-hour), continuous glucose monitoring (CGM) metrics and early and late glucose incremental area under the curves (iAUCs) and delivered insulin doses were evaluated. The association of C/FP and HCLs with postprandial glucose and insulin patterns was analyzed by univariate analysis of variance (ANOVA) with a two-factor design. RESULTS Postprandial glucose time-in-range 70 to 180 mg/dL was optimal after breakfast (78.3 ± 26.9%), lunch (72.7 ± 26.1%), and dinner (70.8 ± 27.3%), with no significant differences between HCLs. Independent of C/FP, late glucose-iAUC after lunch was significantly lower in C-IQ users than 670G and 780G (P < .05), with no significant differences at breakfast and dinner. Postprandial insulin pattern (Ins3-6h minus Ins0-3h) differed by type of HCLs at lunch (P = .026) and dinner (P < .001), being the early insulin dose (Ins0-3h) higher than the late dose (Ins3-6h) in 670G and 780G users with an opposite pattern in C-IQ users. CONCLUSIONS Independent of different proportions of dietary carbohydrates, fat, and protein, postprandial glucose response was similar in users of different HCLs, although obtained through different automatic insulin delivery patterns.
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Affiliation(s)
- Giuseppe Scidà
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Alessandra Corrado
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Jumana Abuqwider
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Roberta Lupoli
- Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy
| | - Carmen Rainone
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Giuseppe Della Pepa
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Maria Masulli
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Giovanni Annuzzi
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
| | - Lutgarda Bozzetto
- Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
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29
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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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30
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Boucsein A, Zhou Y, Haszard JJ, Jefferies CA, Wiltshire EJ, Styles SE, Crocket HR, Galland BC, Pasha M, Petrovski G, Paul RG, de Bock MI, Wheeler BJ. Protocol for a prospective, multicenter, parallel-group, open-label randomized controlled trial comparing standard care with Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control: the CO-PILOT trial. J Diabetes Metab Disord 2024; 23:1397-1407. [PMID: 38932805 PMCID: PMC11196497 DOI: 10.1007/s40200-024-01397-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Accepted: 02/04/2024] [Indexed: 06/28/2024]
Abstract
Purpose Advanced hybrid closed loop (AHCL) systems have the potential to improve glycemia and reduce burden for people with type 1 diabetes (T1D). Children and youth, who are at particular risk for out-of-target glycemia, may have the most to gain from AHCL. However, no randomized controlled trial (RCT) specifically targeting this age group with very high HbA1c has previously been attempted. Therefore, the CO-PILOT trial (Closed lOoP In chiLdren and yOuth with Type 1 diabetes and high-risk glycemic control) aims to evaluate the efficacy and safety of AHCL in this group. Methods A prospective, multicenter, parallel-group, open-label RCT, comparing MiniMed™ 780G AHCL to standard care (multiple daily injections or continuous subcutaneous insulin infusion). Eighty participants aged 7-25 years with T1D, a current HbA1c ≥ 8.5% (69 mmol/mol), and naïve to automated insulin delivery will be randomly allocated to AHCL or control (standard care) for 13 weeks. The primary outcome is change in HbA1c between baseline and 13 weeks. Secondary outcomes include standard continuous glucose monitor glycemic metrics, psychosocial factors, sleep, platform performance, safety, and user experience. This RCT will be followed by a continuation phase where the control arm crosses over to AHCL and all participants use AHCL for a further 39 weeks to assess longer term outcomes. Conclusion This study will evaluate the efficacy and safety of AHCL in this population and has the potential to demonstrate that AHCL is the gold standard for children and youth with T1D experiencing out-of-target glucose control and considerable diabetes burden. Trial registration This trial was prospectively registered with the Australian New Zealand Clinical Trials Registry on 14 November 2022 (ACTRN12622001454763) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1284-8452). Supplementary Information The online version contains supplementary material available at 10.1007/s40200-024-01397-4.
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Affiliation(s)
- Alisa Boucsein
- Department of Women’s and Children’s Health, University of Otago, Dunedin, New Zealand
| | - Yongwen Zhou
- Department of Women’s and Children’s Health, University of Otago, Dunedin, New Zealand
- Department of Endocrinology, Institute of Endocrine and Metabolic Diseases, Division of Life Sciences and Medicine, The First Affiliated Hospital of USTC, Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China (USTC), 230001 Hefei, Anhui China
| | | | - Craig A. Jefferies
- Starship Child Health, Te Whatu Ora Te Toka Tumai Auckland, Auckland, New Zealand
- Liggins Institute, Department of Paediatrics, The University of Auckland, Auckland, New Zealand
| | - Esko J. Wiltshire
- Department of Paediatrics and Child Health, University of Otago Wellington, Wellington, New Zealand
- Te Whatu Ora Capital, Coast and Hutt Valley, Wellington, New Zealand
| | - Sara E. Styles
- Department of Human Nutrition, University of Otago, Dunedin, New Zealand
| | - Hamish R. Crocket
- Te Huatakia Waiora School of Health, University of Waikato, Hamilton, New Zealand
| | - Barbara C. Galland
- Department of Women’s and Children’s Health, University of Otago, Dunedin, New Zealand
| | | | | | - Ryan G. Paul
- Te Huatakia Waiora School of Health, University of Waikato, Hamilton, New Zealand
- Waikato Regional Diabetes Service, Te Whatu Ora Waikato, Hamilton, New Zealand
| | - Martin I. de Bock
- Department of Paediatrics, University of Otago, Christchurch, New Zealand
- Te Whatu Ora Waitaha Canterbury, Christchurch, New Zealand
| | - Benjamin J. Wheeler
- Department of Women’s and Children’s Health, University of Otago, Dunedin, New Zealand
- Te Whatu Ora Southern, Dunedin, New Zealand
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31
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Steenkamp D, Brouillard E, Aia C, Fantasia K, Sullivan C, Atakov-Castillo A, Wolpert H. Reducing Inequity in the Use of Automated Insulin Delivery Systems by Adults With Type 1 Diabetes: Key Learnings From a Safety Net Diabetes Clinic Program. Endocr Pract 2024; 30:558-563. [PMID: 38583773 DOI: 10.1016/j.eprac.2024.04.001] [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] [Received: 01/25/2024] [Revised: 03/28/2024] [Accepted: 04/01/2024] [Indexed: 04/09/2024]
Abstract
BACKGROUND Recent advancements in diabetes technology have significantly improved Type 1 diabetes (T1D) management, but disparities persist, particularly in the adoption of automated insulin delivery (AID) systems within minoritized communities. We aimed to improve patient access to AID system training and overcome clinical inertia to referral. METHODS We report on a transformative program implemented at Boston Medical Center, the largest safety-net hospital in New England, aimed at reducing disparities in AID system utilization. We employed a multidisciplinary team and quality improvement principles to identify barriers and develop solutions. Strategies included increasing access to diabetes educators, creating a referral system, and developing telemedicine education classes. We also made efforts to raise clinician awareness and confidence in recommending AID therapy. RESULTS At baseline, 13.5% of our clinic T1D population was using an insulin pump. The population referred included 97 people with T1D (49% female, mean A1c 8.7%, 68% public insurance beneficiaries, 25% Hispanic and 25% non-Hispanic Black). Results from the first year showed a 166% increase in AID system use rates, with 64% of referred patients starting on AID. Notably, 78% of patients with A1c >8.5% adopted AID systems, addressing a gap in representation observed in clinical efficacy trials. The initiative successfully narrowed disparities in AID use among minoritized populations. CONCLUSIONS The program's success among minoritized patients underscores the significance of tailored, collaborative, team-based care and targeted educational initiatives. Our experience provides a foundation for future efforts to ensure equitable access to diabetes technologies, emphasizing the potential of local quality improvement interventions.
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Affiliation(s)
- Devin Steenkamp
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts.
| | - Elizabeth Brouillard
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts
| | - Corinne Aia
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts
| | - Kathryn Fantasia
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts; Evans Center for Implementation and Improvement Sciences, Boston University Chobanian & Avedisian School of Medicine, Boston, Massachusetts
| | - Catherine Sullivan
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts
| | - Astrid Atakov-Castillo
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts
| | - Howard Wolpert
- Section of Endocrinology, Diabetes and Nutrition, Department of Medicine, Boston University Chobanian & Avedisian School of Medicine, and Boston Medical Center, Boston, Massachusetts
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Ortiz La Banca Barber R, Volkening LK, Mehta SN, Dassau E, Laffel LM. Effects of Macronutrient Intake and Number of Meals on Glycemic Outcomes Over 1 Year in Youth with Type 1 Diabetes. Diabetes Technol Ther 2024; 26:420-425. [PMID: 38277162 DOI: 10.1089/dia.2023.0464] [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: 01/27/2024]
Abstract
Objective: Insulin bolus doses derive from glucose levels and planned carbohydrate intake, although fat and protein impact glycemic excursions. We examined the impact of macronutrients and number of daily meals/snacks on glycemic outcomes in youth with type 1 diabetes. Methods: Youth (N = 136, ages 8-17) with type 1 diabetes completed 3-day food records, wore 3-day masked continuous glucose monitoring, and had A1c measurements every 3 months for 1 year. Diet data were analyzed using Nutrition Data System for Research. Longitudinal mixed models assessed effects of macronutrient intake and number of meals/snacks on glycemic outcomes. Results: At baseline, youth (48% male) had mean age of 12.8 ± 2.5 years and diabetes duration of 5.9 ± 3.1 years; 73% used insulin pumps. Baseline A1c was 8.1% ± 1.0%, percent time in range 70-180 mg/dL (%TIR) was 49% ± 17%, % time below range <70 mg/dL (%TBR) was 6% ± 8%, % time above range >180 mg/dL (%TAR) was 44% ± 20%, and glycemic variability as coefficient of variation (CV) was 41% ± 8%; macronutrient intake included 48% ± 5% carbohydrate, 36% ± 5% fat, and 16% ± 2% protein. Most youth (56%) reported 3-4 meals/snacks daily (range 1-9). Over 1 year, greater carbohydrate intake was associated with lower A1c (P = 0.0003), more %TBR (P = 0.0006), less %TAR (P = 0.002), and higher CV (P = 0.03). Greater fat intake was associated with higher A1c (P = 0.006), less %TBR (P = 0.002), and more %TAR (P = 0.005). Greater protein intake was associated with higher A1c (P = 0.01). More daily meals/snacks were associated with lower A1c (P = 0.001), higher %TIR (P = 0.0006), and less %TAR (P = 0.0001). Conclusions: Both fat and protein impact glycemic outcomes. Future automated insulin delivery systems should consider all macronutrients for timely insulin provision. The present research study derived from secondary analysis of the study registered under NCT00999375.
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Affiliation(s)
- Rebecca Ortiz La Banca Barber
- Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
- Institute for Nursing and Interprofessional Research, Children's Hospital Los Angeles, Los Angeles, California, USA
| | - Lisa K Volkening
- Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Sanjeev N Mehta
- Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Eyal Dassau
- Harvard John A. Paulson School of Engineering and Applied Sciences, Cambridge, Massachusetts, USA
| | - Lori M Laffel
- Section on Clinical, Behavioral and Outcomes Research, Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts, USA
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Lebech Cichosz S, Bender C. Development of Machine Learning Models for the Identification of Elevated Ketone Bodies During Hyperglycemia in Patients with Type 1 Diabetes. Diabetes Technol Ther 2024; 26:403-410. [PMID: 38456910 DOI: 10.1089/dia.2023.0531] [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: 03/09/2024]
Abstract
Aims: Diabetic ketoacidosis (DKA) is a serious life-threatening condition caused by a lack of insulin, which leads to elevated plasma glucose and metabolic acidosis. Early identification of developing DKA is important to start treatment and minimize complications and risk of death. The aim of the present study is to develop and test prediction model(s) that gives an alarm about their risk of developing elevated ketone bodies during hyperglycemia. Methods: We analyzed data from 138 type 1 diabetes patients with measurements of ketone bodies and continuous glucose monitoring (CGM) data from over 30,000 days of wear time. We utilized a supervised binary classification machine learning approach to identify elevated levels of ketone bodies (≥0.6 mmol/L). Data material was randomly divided at patient level in 70%/30% (training/test) dataset. Logistic regression (LR) and random forest (RF) classifier were compared. Results: Among included patients, 913 ketone samples were eligible for modeling, including 273 event samples with ketone levels ≥0.6 mmol/L. An area under the receiver operating characteristic curve from the RF classifier was 0.836 (confidence interval [CI] 90%, 0.783-0.886) and 0.710 (CI 90%, 0.646-0.77) for the LR classifier. Conclusions: The novel approach for identifying elevated ketone levels in patients with type 1 diabetes utilized in this study indicates that CGM could be a valuable resource for the early prediction of patients at risk of developing DKA. Future studies are needed to validate the results.
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Affiliation(s)
- Simon Lebech Cichosz
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Clara Bender
- Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
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Mosquera-Lopez C, Jacobs PG. Digital twins and artificial intelligence in metabolic disease research. Trends Endocrinol Metab 2024; 35:549-557. [PMID: 38744606 DOI: 10.1016/j.tem.2024.04.019] [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] [Received: 03/05/2024] [Revised: 04/25/2024] [Accepted: 04/25/2024] [Indexed: 05/16/2024]
Abstract
Digital twin technology is emerging as a transformative paradigm for personalized medicine in the management of chronic conditions. In this article, we explore the concept and key characteristics of a digital twin and its applications in chronic non-communicable metabolic disease management, with a focus on diabetes case studies. We cover various types of digital twin models, including mechanistic models based on ODEs, data-driven ML algorithms, and hybrid modeling strategies that combine the strengths of both approaches. We present successful case studies demonstrating the potential of digital twins in improving glucose outcomes for individuals with T1D and T2D, and discuss the benefits and challenges of translating digital twin research applications to clinical practice.
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Affiliation(s)
- Clara Mosquera-Lopez
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA
| | - Peter G Jacobs
- Artificial Intelligence for Medical Systems Lab, Department of Biomedical Engineering, Oregon Health and Science University, Portland, OR, USA.
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Fagherazzi G, Aguayo GA, Zhang L, Hanaire H, Picard S, Sablone L, Vergès B, Hamamouche N, Detournay B, Joubert M, Delemer B, Guilhem I, Vambergue A, Gourdy P, Hadjadj S, Velayoudom FL, Guerci B, Larger E, Jeandidier N, Gautier JF, Renard E, Potier L, Benhamou PY, Sola A, Bordier L, Bismuth E, Prévost G, Kessler L, Cosson E, Riveline JP. Heterogeneity of glycaemic phenotypes in type 1 diabetes. Diabetologia 2024:10.1007/s00125-024-06179-4. [PMID: 38780786 DOI: 10.1007/s00125-024-06179-4] [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] [Received: 10/05/2023] [Accepted: 04/08/2024] [Indexed: 05/25/2024]
Abstract
AIMS/HYPOTHESIS Our study aims to uncover glycaemic phenotype heterogeneity in type 1 diabetes. METHODS In the Study of the French-speaking Society of Type 1 Diabetes (SFDT1), we characterised glycaemic heterogeneity thanks to a set of complementary metrics: HbA1c, time in range (TIR), time below range (TBR), CV, Gold score and glycaemia risk index (GRI). Applying the Discriminative Dimensionality Reduction with Trees (DDRTree) algorithm, we created a phenotypic tree, i.e. a 2D visual mapping. We also carried out a clustering analysis for comparison. RESULTS We included 618 participants with type 1 diabetes (52.9% men, mean age 40.6 years [SD 14.1]). Our phenotypic tree identified seven glycaemic phenotypes. The 2D phenotypic tree comprised a main branch in the proximal region and glycaemic phenotypes in the distal areas. Dimension 1, the horizontal dimension, was positively associated with GRI (coefficient [95% CI]) (0.54 [0.52, 0.57]), HbA1c (0.39 [0.35, 0.42]), CV (0.24 [0.19, 0.28]) and TBR (0.11 [0.06, 0.15]), and negatively with TIR (-0.52 [-0.54, -0.49]). The vertical dimension was positively associated with TBR (0.41 [0.38, 0.44]), CV (0.40 [0.37, 0.43]), TIR (0.16 [0.12, 0.20]), Gold score (0.10 [0.06, 0.15]) and GRI (0.06 [0.02, 0.11]), and negatively with HbA1c (-0.21 [-0.25, -0.17]). Notably, socioeconomic factors, cardiovascular risk indicators, retinopathy and treatment strategy were significant determinants of glycaemic phenotype diversity. The phenotypic tree enabled more granularity than traditional clustering in revealing clinically relevant subgroups of people with type 1 diabetes. CONCLUSIONS/INTERPRETATION Our study advances the current understanding of the complex glycaemic profile in people with type 1 diabetes and suggests that strategies based on isolated glycaemic metrics might not capture the complexity of the glycaemic phenotypes in real life. Relying on these phenotypes could improve patient stratification in type 1 diabetes care and personalise disease management.
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Affiliation(s)
- Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg.
| | - Gloria A Aguayo
- Deep Digital Phenotyping Research Unit, Department of Precision Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Lu Zhang
- Bioinformatics Platform, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Hélène Hanaire
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
- Francophone Foundation for Diabetes Research, Paris, France
| | - Sylvie Picard
- Endocrinology and Diabetes, Point Medical, Dijon, France
| | - Laura Sablone
- Francophone Foundation for Diabetes Research, Paris, France
| | - Bruno Vergès
- Department of Endocrinology-Diabetology, Inserm LNC UMR1231, University of Burgundy, Dijon, France
| | | | | | - Michael Joubert
- Service d'Endocrinologie-Diabétologie (Endocrinology/Diabetes Unit), Centre Hospitalier Universitaire de Caen, Caen, France
| | - Brigitte Delemer
- Endocrinology, Diabetology and Nutrition Department, Robert Debré University Hospital, Reims, France
| | - Isabelle Guilhem
- Department of Endocrinology, Diabetes and Nutrition, University Hospital of Rennes, Rennes, France
| | - Anne Vambergue
- Endocrinology, Diabetology, Metabolism and Nutrition Department, Lille University Hospital, Lille, France
| | - Pierre Gourdy
- Department of Diabetology, Metabolic Diseases and Nutrition, CHU Toulouse, University of Toulouse, Toulouse, France
- Institute of Metabolic and Cardiovascular Diseases, UMR1297 Inserm/UPS, Toulouse University, Toulouse, France
| | - Samy Hadjadj
- Institut du thorax, INSERM, CNRS, Université Nantes, CHU Nantes, Nantes, France
| | - Fritz-Line Velayoudom
- Department of Endocrinology-Diabetology, University Hospital of Guadeloupe, Pointe-À-Pitre, France
- Inserm UMR1283, CNRS UMR8199, European Genomic Institute for Diabetes (EGID), Lille, France
| | - Bruno Guerci
- Department of Endocrinology, Diabetology, and Nutrition, Brabois Adult Hospital, University of Lorraine, Vandoeuvre-Lès-Nancy, France
| | - Etienne Larger
- University Paris Cité, Institut Cochin, U1016, Inserm, Paris, France
- Diabetology Department, Cochin Hospital, AP-HP, Paris, France
| | - Nathalie Jeandidier
- Department of Endocrinology, Diabetes and Nutrition, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Jean-François Gautier
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Centre Universitaire de Diabétologie et de ses Complications, AP-HP, Hôpital Lariboisière, Paris, France
| | - Eric Renard
- Institute of Functional Genomics, University of Montpellier, CNRS, Inserm, Montpellier, France
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, Montpellier, France
| | - Louis Potier
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Department of Diabetology, Endocrinology and Nutrition, AP-HP, Bichat Hospital, Paris, France
| | | | - Agnès Sola
- Diabetology Department, Cochin Hospital, AP-HP, Paris, France
| | - Lyse Bordier
- Service d'Endocrinologie, Hôpital Bégin, Saint Mandé, France
| | - Elise Bismuth
- Robert-Debré University Hospital, Department of Paediatric Endocrinology and Diabetology, AP-HP, University of Paris, Paris, France
| | - Gaëtan Prévost
- Department of Endocrinology, Diabetes and Metabolic Diseases, Normandie Université, UNIROUEN, Rouen University Hospital, Centre d'Investigation Clinique (CIC-CRB)-Inserm 1404, Rouen University Hospital, Rouen, France
| | - Laurence Kessler
- Department of Endocrinology, Diabetes and Nutrition, Hôpitaux Universitaires de Strasbourg, Université de Strasbourg, Strasbourg, France
| | - Emmanuel Cosson
- Department of Endocrinology-Diabetology-Nutrition, AP-HP, Avicenne Hospital, Paris 13 University, Sorbonne Paris Cité, CRNH-IdF, CINFO, Bobigny, France
- Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), Université Sorbonne Paris Nord and Université Paris CitéInserm, INRAE, CNAM, Centre of Research in Epidemiology and StatisticS (CRESS), Bobigny, France
| | - Jean-Pierre Riveline
- Institut Necker Enfants Malades, Inserm U1151, CNRS UMR 8253, IMMEDIAB Laboratory, Paris, France
- Centre Universitaire de Diabétologie et de ses Complications, AP-HP, Hôpital Lariboisière, Paris, France
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Levy CJ, Bailey R, Laffel LM, Forlenza G, DiMeglio LA, Hughes MS, Brown SA, Aleppo G, Bhargava A, Shah VN, Clements MA, Kipnes M, Bruggeman B, Daniels M, Rodriguez H, Calhoun P, Lum JW, Sasson-Katchalski R, Pinsker JE, Pollom R, Beck RW. Multicenter Evaluation of Ultra-Rapid Lispro Insulin with Control-IQ Technology in Adults, Adolescents, and Children with Type 1 Diabetes. Diabetes Technol Ther 2024. [PMID: 38696672 DOI: 10.1089/dia.2024.0048] [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: 05/04/2024]
Abstract
Objective: To evaluate the safety and explore the efficacy of use of ultra-rapid lispro (URLi, Lyumjev) insulin in the Tandem t:slim X2 insulin pump with Control-IQ 1.5 technology in children, teenagers, and adults living with type 1 diabetes (T1D). Methods: At 14 U.S. diabetes centers, youth and adults with T1D completed a 16-day lead-in period using lispro in a t:slim X2 insulin pump with Control-IQ 1.5 technology, followed by a 13-week period in which URLi insulin was used in the pump. Results: The trial included 179 individuals with T1D (age 6-75 years). With URLi, 1.7% (3 participants) had a severe hypoglycemia event over 13 weeks attributed to override boluses or a missed meal. No diabetic ketoacidosis events occurred. Two participants stopped URLi use because of infusion-site discomfort, and one stopped after developing a rash. Mean time 70-180 mg/dL increased from 65% ± 15% with lispro to 67% ± 13% with URLi (P = 0.004). Mean insulin treatment satisfaction questionnaire score improved from 75 ± 13 at screening to 80 ± 11 after 13 weeks of URLi use (mean difference = 6; 95% confidence interval 4-8; P < 0.001), with the greatest improvement reported for confidence avoiding symptoms of high blood sugar. Mean treatment-related impact measure-diabetes score improved from 74 ± 12 to 80 ± 12 (P < 0.001), and mean TRIM-Diabetes Device (score improved from 82 ± 11 to 86 ± 12 (P < 0.001). Conclusions: URLi use in the Tandem t:slim X2 insulin pump with Control-IQ 1.5 technology was safe for adult and pediatric participants with T1D, with quality-of-life benefits of URLi use perceived by the study participants. Clinicaltrials.gov registration: NCT05403502.
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Affiliation(s)
- Carol J Levy
- Division of Endocrinology, Icahn School of Medicine at Mount Sinai, New York City, New York, USA
| | - Ryan Bailey
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Lori M Laffel
- Research Division, Joslin Diabetes Center and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, USA
| | - Gregory Forlenza
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Linda A DiMeglio
- Department of Pediatrics, Division of Pediatric Endocrinology and Diabetology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Michael S Hughes
- Department of Medicine, Division of Endocrinology, Gerontology and Metabolism, Stanford University School of Medicine, Stanford, California, USA
| | - Sue A Brown
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Grazia Aleppo
- Division of Endocrinology, Metabolism and Molecular Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Anuj Bhargava
- Iowa Diabetes and Endocrinology Research Center, West Des Moines, Iowa, USA
| | - Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado, Anschutz Medical Campus, Aurora, Colorado, USA
| | - Mark A Clements
- Department of Pediatrics, Division of Endocrinology and Diabetes, Children's Mercy Kansas City, Kansas City, Missouri, USA
| | - Mark Kipnes
- Diabetes & Glandular Disease Clinic, San Antonio, Texas, USA
| | - Brittany Bruggeman
- Department of Pediatrics, Division of Endocrinology, University of Florida, Gainesville, Florida, USA
| | - Mark Daniels
- Division of Endocrinology and Diabetes, Children's Hospital of Orange County, Orange, California, USA
| | - Henry Rodriguez
- USF Diabetes and Endocrinology Center, University of South Florida, Tampa, Florida, USA
| | - Peter Calhoun
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - John W Lum
- Jaeb Center for Health Research, Tampa, Florida, USA
| | | | | | - Robyn Pollom
- Eli Lilly and Company, Lilly Corporate Center, Indianapolis, Indiana, USA
| | - Roy W Beck
- Jaeb Center for Health Research, Tampa, Florida, USA
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Boughton CK, Hovorka R. The role of automated insulin delivery technology in diabetes. Diabetologia 2024:10.1007/s00125-024-06165-w. [PMID: 38740602 DOI: 10.1007/s00125-024-06165-w] [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] [Received: 03/04/2024] [Accepted: 03/21/2024] [Indexed: 05/16/2024]
Abstract
The role of automated insulin delivery systems in diabetes is expanding. Hybrid closed-loop systems are being used in routine clinical practice for treating people with type 1 diabetes. Encouragingly, real-world data reflects the performance and usability observed in clinical trials. We review the commercially available hybrid closed-loop systems, their distinctive features and the associated real-world data. We also consider emerging indications for closed-loop systems, including the treatment of type 2 diabetes where variability of day-to-day insulin requirements is high, and other challenging applications for this technology. We discuss issues around access and implementation of closed-loop technology, and consider the limitations of present closed-loop systems, as well as innovative approaches that are being evaluated to improve their performance.
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Affiliation(s)
- Charlotte K Boughton
- Wellcome-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
| | - Roman Hovorka
- Wellcome-Medical Research Council Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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Jafar A, Pasqua MR. Postprandial glucose-management strategies in type 1 diabetes: Current approaches and prospects with precision medicine and artificial intelligence. Diabetes Obes Metab 2024; 26:1555-1566. [PMID: 38263540 DOI: 10.1111/dom.15463] [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] [Received: 11/28/2023] [Revised: 01/01/2024] [Accepted: 01/05/2024] [Indexed: 01/25/2024]
Abstract
Postprandial glucose control can be challenging for individuals with type 1 diabetes, and this can be attributed to many factors, including suboptimal therapy parameters (carbohydrate ratios, correction factors, basal doses) because of physiological changes, meal macronutrients and engagement in postprandial physical activity. This narrative review aims to examine the current postprandial glucose-management strategies tested in clinical trials, including adjusting therapy settings, bolusing for meal macronutrients, adjusting pre-exercise and postexercise meal boluses for postprandial physical activity, and other therapeutic options, for individuals on open-loop and closed-loop therapies. Then we discuss their challenges and future avenues. Despite advancements in insulin delivery devices such as closed-loop systems and decision-support systems, many individuals with type 1 diabetes still struggle to manage their glucose levels. The main challenge is the lack of personalized recommendations, causing suboptimal postprandial glucose control. We suggest that postprandial glucose control can be improved by (i) providing personalized recommendations for meal macronutrients and postprandial activity; (ii) including behavioural recommendations; (iii) using other personalized therapeutic approaches (e.g. glucagon-like peptide-1 receptor agonists, sodium-glucose co-transporter inhibitors, amylin analogues, inhaled insulin) in addition to insulin therapy; and (iv) integrating an interpretability report to explain to individuals about changes in treatment therapy and behavioural recommendations. In addition, we suggest a future avenue to implement precision recommendations for individuals with type 1 diabetes utilizing the potential of deep reinforcement learning and foundation models (such as GPT and BERT), employing different modalities of data including diabetes-related and external background factors (i.e. behavioural, environmental, biological and abnormal events).
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Affiliation(s)
- Adnan Jafar
- Department of Biomedical Engineering, McGill University, Montreal, Quebec, Canada
| | - Melissa-Rosina Pasqua
- Division of Endocrinology, Department of Medicine, McGill University, Montreal, Quebec, Canada
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Colmegna P, Diaz C. JL, Garcia-Tirado J, DeBoer MD, Breton MD. Adjusting Therapy Profiles When Switching to Ultra-Rapid Lispro in an Advanced Hybrid Closed-Loop System: An in Silico Study. J Diabetes Sci Technol 2024; 18:676-685. [PMID: 36424765 PMCID: PMC11089876 DOI: 10.1177/19322968221140401] [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: 11/27/2022]
Abstract
BACKGROUND It has been shown that insulin acceleration by itself might not be sufficient to see clear improvements in glycemic metrics, and insulin therapy may need to be adjusted to fully leverage the extra safety margin provided by faster pharmacokinetic (PK) and pharmacodynamic (PD) profiles. The objective of this work is to explore how to perform such adjustments on a commercially available automated insulin delivery (AID) system. METHODS Ultra-rapid lispro (URLi) is modeled within the UVA/Padova simulation platform using data from previously published clamp studies. The Control-IQ AID algorithm is selected as it leverages carbohydrate-to-insulin ratio (CR in g/U), correction factor (CF in mg/dL/U), and basal rate (BR in U/h) daily profiles that are fully customizable. An experiment roadmap is proposed to understand how to safely modify these profiles when switching from lispro to URLi. RESULTS Simulations show that a 7% decrease in CR (approximately an 8% increase in prandial insulin) and a 7.5% increase in BR lead to cumulative improvements in glucose control with URLi. Comparing with baseline metrics using lispro, a clinically significant increase in time in the range of 70 to 180 mg/dL (overall: 70.2%-75.2%, P < .001; 6 am-12 am: 62.4%-68.5%, P < .001) and a reduction in time below 70 mg/dL (overall: 1.8%-1.2%, P < .001; 6 am-12 am: 1.8%-1.3%, P < .001) were observed. CONCLUSION Properly adjusting therapy parameters allows to fully leverage glucose control benefits provided by faster insulin analogues, opening opportunities to take another step forward into a next generation of more effective AID solutions.
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Affiliation(s)
- Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Jenny L. Diaz C.
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Jose Garcia-Tirado
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Mark D. DeBoer
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, VA, USA
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Ng SM, Wright NP, Yardley D, Campbell F, Randell T, Trevelyan N, Ghatak A, Hindmarsh PC. Long-term assessment of the NHS hybrid closed-loop real-world study on glycaemic outcomes, time-in-range, and quality of life in children and young people with type 1 diabetes. BMC Med 2024; 22:175. [PMID: 38659016 PMCID: PMC11044460 DOI: 10.1186/s12916-024-03396-x] [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] [Received: 12/07/2023] [Accepted: 04/17/2024] [Indexed: 04/26/2024] Open
Abstract
Hybrid closed-loop (HCL) systems seamlessly interface continuous glucose monitoring (CGM) with insulin pumps, employing specialised algorithms and user-initiated automated insulin delivery. This study aimed to assess the efficacy of HCLs at 12 months post-initiation on glycated haemoglobin (HbA1c), time-in-range (TIR), hypoglycaemia frequency, and quality of life measures among children and young people (CYP) with type 1 diabetes mellitus (T1DM) and their caregivers in a real-world setting. Conducted between August 1, 2021, and December 10, 2022, the prospective recruitment took place in eight paediatric diabetes centres across England under the National Health Service England's (NHSE) HCL pilot real-world study. A cohort of 251 CYP (58% males, mean age 12.3 years) with T1DM participated (89% white, 3% Asian, 4% black, 3% mixed ethnicity, and 1% other). The study utilised three HCL systems: (1) Tandem Control-IQ AP system, which uses the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, San Diego, CA, USA) with the Dexcom G6® CGM (Dexcom, San Diego, CA, USA) sensor; (2) Medtronic MiniMed™ 780G with the Guardian 4 sensor (Medtronic, Northridge, CA, USA); and (3) the CamAPS FX (CamDiab, Cambridge, UK) with the Ypsomed insulin pump (Ypsomed Ltd, Escrick, UK) and Dexcom G6® CGM.All systems were fully funded by the NHS. Results demonstrated significant improvements in HbA1c (average reduction at 12 months 7 mmol/mol; P < 0.001), time-in-range (TIR) (average increase 13.4%; P < 0.001), hypoglycaemia frequency (50% reduction), hypoglycaemia fear, and quality of sleep (P < 0.001) among CYP over a 12-month period of HCL usage. Additionally, parents and carers experienced improvements in hypoglycaemia fear and quality of sleep after 6 and 12 months of use. In addition to the improvements in glycaemic management, these findings underscore the positive impact of HCL systems on both the well-being of CYP with T1DM and the individuals caring for them.
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Affiliation(s)
- Sze May Ng
- Faculty of Health, Social Care and Medicine, Edge Hill University, Ormskirk, UK.
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.
- Paediatric Department, Mersey and West Lancashire Teaching Hospitals, Ormskirk, L39 2AZ, UK.
| | | | - Diana Yardley
- Children's Diabetes Team, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Fiona Campbell
- Children's Diabetes Centre, Leeds Children's Hospital, Leeds, UK
| | - Tabitha Randell
- Department of Paediatric Endocrinology, Nottingham Children's Hospital, Nottingham, UK
| | | | | | - Peter C Hindmarsh
- Children and Young People's Diabetes Service, University College London Hospitals NHS Foundation Trust, London, UK
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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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Oliva Morgado Ferreira R, Trevisan T, Pasqualotto E, Schmidt P, Pedrotti Chavez M, Figueiredo Watanabe JM, van de Sande-Lee S. Efficacy of the hybrid closedloop insulin delivery system in children and adolescents with type 1 diabetes: a meta-analysis with trial sequential analysis. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2024; 68:e230280. [PMID: 38602747 PMCID: PMC11081057 DOI: 10.20945/2359-4292-2023-0280] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Accepted: 10/11/2023] [Indexed: 04/12/2024]
Abstract
The aim of this study was to assess the efficacy and safety of hybrid closed-loop (HCL) systems for insulin delivery in children and adolescents with type 1 diabetes (T1D). We searched Embase, PubMed, and Cochrane Library for randomized controlled trials (RCTs) published until March 2023 comparing the HCL therapy with control therapies for children and adolescents with T1D. We computed weighted mean differences (WMDs) for continuous outcomes and risk ratios (RRs) with 95% confidence intervals (CIs) for binary endpoints. Four RCTs and 501 patients were included, of whom 323 were randomized to HCL therapy. Compared with control therapies, HCL significantly improved the period during which glucose level was 70-180 mg/dL (WMD 10.89%, 95% CI 8.22-13.56%) and the number of participants with glycated hemoglobin (HbA1c) level < 7% (RR 2.61, 95% CI 1.29-5.28). Also, HCL significantly reduced the time during which glucoselevel was > 180 mg/dL (WMD-10.46%, 95% CI-13.99 to-6.93%) and the mean levels of glucose (WMD-16.67 mg/dL, 95% CI-22.25 to-11.09 mg/dL) and HbA1c (WMD-0.50%, 95% CI-0.68 to-0.31). There were no significant differences between therapies regarding time during which glucose level was < 70 mg/dL or <54 mg/dL or number of episodes of ketoacidosis, hyperglycemia, and hypoglycemia. In this meta-analysis, HCL compared with control therapies was associated with improved time in range and HbA1c control in children and adolescents with T1D and a similar profile of side effects. These findings support the efficacy of HCL in the treatment of T1D in this population.
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Affiliation(s)
| | - Talita Trevisan
- Clínica particular, Talita Trevisan Endocrinologia, Itajaí, SC, Brasil
| | - Eric Pasqualotto
- Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil
| | - Pedro Schmidt
- Universidade Federal de Santa Catarina, Florianópolis, SC, Brasil
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Christensen MB, Ranjan AG, Rytter K, McCarthy OM, Schmidt S, Nørgaard K. Automated Insulin Delivery in Adults With Type 1 Diabetes and Suboptimal HbA 1c During Prior Use of Insulin Pump and Continuous Glucose Monitoring: A Randomized Controlled Trial. J Diabetes Sci Technol 2024:19322968241242399. [PMID: 38600822 DOI: 10.1177/19322968241242399] [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: 04/12/2024]
Abstract
BACKGROUND Automated insulin delivery (AID) systems offer promise in improving glycemic outcomes for individuals with type 1 diabetes. However, data on those who struggle with suboptimal glycemic levels despite insulin pump and continuous glucose monitoring (CGM) are limited. We conducted a randomized controlled trial to assess the effects of an AID system in this population. METHODS Participants with hemoglobin A1c (HbA1c) ≥ 58 mmol/mol (7.5%) were allocated 1:1 to 14 weeks of treatment with the MiniMed 780G system (AID) or continuation of usual care (UC). The primary endpoint was change in time in range (TIR: 3·9-10·0 mmol/L) from baseline to week 14. After this trial period, the UC group switched to AID treatment while the AID group continued using the system. Both groups were monitored for a total of 28 weeks. RESULTS Forty adults (mean ± SD: age 52 ± 11 years, HbA1c 67 ± 7 mmol/mol [8.3% ± 0.6%], diabetes duration 29 ±13 years) were included. After 14 weeks, TIR increased by 18.7% (95% confidence interval [CI] = 14.5, 22.9%) in the AID group and remained unchanged in the UC group (P < .0001). Hemoglobin A1c decreased by 10.0 mmol/mol (95% CI = 7.0, 13.0 mmol/mol) (0.9% [95% CI = 0.6%, 1.2%]) in the AID group but remained unchanged in the UC group (P < .0001). The glycemic benefits of AID treatment were reproduced after the 14-week extension phase. There were no episodes of severe hypoglycemia or diabetic ketoacidosis during the study. CONCLUSIONS For adults with type 1 diabetes not meeting glycemic targets despite use of insulin pump and CGM, transitioning to an AID system confers considerable glycemic benefits.
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Affiliation(s)
- Merete B Christensen
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Ajenthen G Ranjan
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Karen Rytter
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Olivia M McCarthy
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Applied Sports, Technology, Exercise and Medicine Research Centre, Swansea University, Swansea, UK
| | - Signe Schmidt
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Kirsten Nørgaard
- Copenhagen University Hospital, Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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Castorani V, Rigamonti A, Frontino G, Morotti E, Sandullo F, Scialabba F, Arrigoni F, Dionisi B, Foglino R, Morosini C, Olivieri G, Bonfanti R. Turning the tides: achieving rapid and safe glucose control in adolescents with suboptimally controlled type 1 diabetes using advanced hybrid closed loop systems. Front Endocrinol (Lausanne) 2024; 15:1243565. [PMID: 38628580 PMCID: PMC11019566 DOI: 10.3389/fendo.2024.1243565] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 01/04/2024] [Indexed: 04/19/2024] Open
Abstract
Aim Many adolescents with T1D experience a decline in metabolic control due to erratic eating habits and subpar adherence to treatment regimens. The objective of our retrospective observational study was to assess the effect of the Tandem Control IQ (CIQ) advanced hybrid closed-loop (AHCL) system on a cohort of adolescents with suboptimal glucose control. Methods We retrospectively evaluated 20 non-adherent patients with T1D, who were inconsistently using Multiple Daily Injections (MDIs) and flash glucose monitoring and were subsequently started and on CIQ. Glucometrics and the Glucose Risk Index were assessed at baseline and after 2 weeks, 1 month, and 6 months of CIQ use. Results The study included 20 adolescents with T1D (HbA1c: 10.0% ± 1.7). Time in range (TIR) increased from 27.1% ± 13.7 at baseline to 68.6% ± 14.2 at 2 weeks, 66.6% ± 10.7 at 1 month, and 60.4% ± 13.3 at 6 months of CIQ use. Time above range (TAR) >250 mg/dL decreased from 46.1% ± 23.8 to 9.9% ± 9.5 at 2 weeks, 10.8% ± 6.1 at 1 month, and 15.5% ± 10.5 at 6 months of AHCL use. Mean glucose levels improved from 251 mg/dL ± 68.9 to 175mg/dL ± 25.5 after 6 months of CIQ use. The Glucose Risk Index (GRI) also significantly reduced from 102 to 48 at 6 months of CIQ. HbA1c also improved from 10.0% ± 1.7 at baseline to 7.0% ± 0.7 after 6 months. Two patients experienced a single episode of mild diabetic ketoacidosis (DKA). Conclusions AHCL systems provide a significant, rapid, and safe improvement in glucose control. This marks a pivotal advancement in technology that primarily benefited those who were already compliant.
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Affiliation(s)
- Valeria Castorani
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Andrea Rigamonti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Giulio Frontino
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Elisa Morotti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Federica Sandullo
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Francesco Scialabba
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Francesca Arrigoni
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Benedetta Dionisi
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Riccardo Foglino
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Camilla Morosini
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Gabriele Olivieri
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Riccardo Bonfanti
- Department of Pediatrics, Pediatric Diabetes Unit, IRCCS San Raffaele Scientific Institute, Milano, Italy
- Diabetes Research Institute, IRCCS San Raffaele Scientific Institute, Milano, Italy
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Folk S, Zappe J, Wyne K, Dungan KM. Comparative Effectiveness of Hybrid Closed-Loop Automated Insulin Delivery Systems Among Patients with Type 1 Diabetes. J Diabetes Sci Technol 2024:19322968241234948. [PMID: 38557128 DOI: 10.1177/19322968241234948] [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: 04/04/2024]
Abstract
BACKGROUND Clinical trials have demonstrated the efficacy and safety of hybrid closed-loop (HCL) systems, yet few studies have compared outcomes in the real-world setting. METHOD This retrospective study analyzed patients from an academic endocrinology practice between January 1, 2018, and November 18, 2022. The inclusion criteria were diagnosis code for type I diabetes (T1D), >18 years of age, new to any HCL system [Medtronic 670G/770G (MT), Tandem Control IQ (CIQ), or Omnipod 5 (OP5)], and availability of a pump download within three months. The outcomes included %time in range (TIR) of 70 to 180 mg/dL, %time below range (TBR) <70 mg/dL at 90 days, and HbA1c for 91 to 180 days. RESULT Of the 176 participants, 47 were MT, 74 CIQ, and 55 OP5. Median (25%, 75%) change in HbA1c was -0.1 (-0.8, 0.3), -0.6 (-1.1, -0.15), and -0.55 (-0.98, 0)% for MT, CIQ, and OP5, respectively, (P = .04). TIR was 70 (57, 76), 67 (59, 75), and 68 (60, 76)% (P = .95) at 90 days while TBR was 2 (1, 3), 1 (0, 2), and 1 (0, 1)%, respectively, (P = .002). The %time in automated delivery was associated with TIR and change in HbA1c. After controlling other factors including %time in automated delivery, HCL type was not an independent predictor of change in HbA1c nor TIR but remained a significant predictor of TBR. CONCLUSION There were significant reductions in HbA1c in CIQ and OP5. TIR was similar across pumps, but TBR was highest with MT. The %time in automated delivery likely explains differences in change in HbA1c but not TBR between HCL systems.
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Affiliation(s)
- Sara Folk
- The Ohio State University College of Medicine, Columbus, OH, USA
| | - Janet Zappe
- Division of Endocrinology, Diabetes and Metabolism, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Kathleen Wyne
- Division of Endocrinology, Diabetes and Metabolism, The Ohio State University College of Medicine, Columbus, OH, USA
| | - Kathleen M Dungan
- Division of Endocrinology, Diabetes and Metabolism, The Ohio State University College of Medicine, Columbus, OH, USA
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Propper-Lewinsohn T, Elran-Barak R, Gillon-Keren M, Yackobovitch-Gavan M, Liberman A, Phillip M, Shalitin S. Disordered Eating Behaviors Among Adolescents and Young Adults with Type 1 Diabetes Treated with Insulin Pumps and Hybrid Closed-Loop Systems. Diabetes Technol Ther 2024; 26:229-237. [PMID: 38090768 DOI: 10.1089/dia.2023.0500] [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: 01/04/2024]
Abstract
Background and Aims: Disordered eating behaviors (DEB) are more common among individuals with type 1 diabetes (T1D) compared to those without, and for insulin pump users may be associated with higher hemoglobin A1c (HbA1c). We investigated DEB risk factors among insulin pump-treated individuals with T1D and clinical characteristics of hybrid closed-loop (HCL) systems' users by DEB level. Methods: An observational, cross-sectional study of 167 insulin pump-treated individuals with T1D, 13-21 years of age. Data were obtained from patients' medical charts with additional self-reported questionnaires, including assessment of DEB. Results: DEB were found in 71 (42.5%) individuals, and positively associated with female sex (β = 2.98 [standard error (SE) = 1.31], P = 0.025), body mass index (BMI)-Z-score (β = 2.12 [SE = 0.64], P = 0.001), HbA1c (β = 1.40 [SE = 0.45], P = 0.02), and higher rate of pump discontinuation (β = 4.48 [SE = 1.99], P = 0.026). The use of HCL systems compared to insulin pumps was associated with higher BMI-Z-score (odds ratio [OR]: 3.46 [95% confidence interval, CI: 1.52-7.87], P = 0.003) and tendency to lower HbA1c level (OR: 0.44 [95% CI: 0.18-1.09], P = 0.078) among individuals without DEB, and with lower HbA1c level (OR: 0.29 [95% CI: 0.10-0.83], P = 0.022) and higher socioeconomic status (OR: 1.73 [95% CI: 1.09-2.74], P = 0.020) among individuals with DEB. Conclusions: DEB are common among individuals with T1D treated with insulin pumps and are associated with higher HbA1c levels. Among T1D individuals with DEB, HCL system use is associated with lower HbA1c compared to insulin pump treatment. Our findings highlight the importance of regular screening for DEB and its risk factors to improve pump treatment and diabetes management. Moreover, individuals with DEB using HCL systems may benefit from reduced HbA1c levels.
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Affiliation(s)
- Tamar Propper-Lewinsohn
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- School of Public Health, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
| | - Roni Elran-Barak
- School of Public Health, Faculty of Social Welfare and Health Sciences, University of Haifa, Haifa, Israel
| | - Michal Gillon-Keren
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Sciences, Kibbutzim College of Education Technology and the Arts, Tel Aviv, Israel
| | - Michal Yackobovitch-Gavan
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Department of Epidemiology and Preventive Medicine, School of Public Health, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Alon Liberman
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
| | - Moshe Phillip
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Shlomit Shalitin
- The Institute of Endocrinology and Diabetes, Schneider Children's Medical Center, Petah Tikva, Israel
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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Eichenlaub M, Pleus S, Rothenbühler M, Bailey TS, Bally L, Brazg R, Bruttomesso D, Diem P, Eriksson Boija E, Fokkert M, Haug C, Hinzmann R, Jendle J, Klonoff DC, Mader JK, Makris K, Moser O, Nichols JH, Nørgaard K, Pemberton J, Selvin E, Spanou L, Thomas A, Tran NK, Witthauer L, Slingerland RJ, Freckmann G. Comparator Data Characteristics and Testing Procedures for the Clinical Performance Evaluation of Continuous Glucose Monitoring Systems. Diabetes Technol Ther 2024; 26:263-275. [PMID: 38194227 PMCID: PMC10979680 DOI: 10.1089/dia.2023.0465] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Abstract
Comparing the performance of different continuous glucose monitoring (CGM) systems is challenging due to the lack of comprehensive guidelines for clinical study design. In particular, the absence of concise requirements for the distribution of comparator (reference) blood glucose (BG) concentrations and their rate of change (RoC) that are used to evaluate CGM performance, impairs comparability. For this article, several experts in the field of CGM performance testing have collaborated to propose characteristics of the distribution of comparator measurements that should be collected during CGM performance testing. Specifically, it is proposed that at least 7.5% of comparator BG concentrations are <70 mg/dL (3.9 mmol/L) and >300 mg/dL (16.7 mmol/L), respectively, and that at least 7.5% of BG-RoC combinations indicate fast BG changes with impending hypo- or hyperglycemia, respectively. These proposed characteristics of the comparator data can facilitate the harmonization of testing conditions across different studies and CGM systems and ensure that the most relevant scenarios representing real-life situations are established during performance testing. In addition, a study protocol and testing procedure for the manipulation of glucose levels are suggested that enable the collection of comparator data with these characteristics. This work is an important step toward establishing a future standard for the performance evaluation of CGM systems.
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Affiliation(s)
- Manuel Eichenlaub
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Stefan Pleus
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
| | | | | | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital Bern, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Ronald Brazg
- Rainier Clinical Research Center, Renton, Washington, USA
| | - Daniela Bruttomesso
- Division of Metabolic Disease, Department of Medicine, University of Padua, Padua, Italy
| | - Peter Diem
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Endokrinologie Diabetologie Bern, Bern, Switzerland
| | - Elisabet Eriksson Boija
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Equalis AB, Uppsala, Sweden
| | - Marion Fokkert
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands
| | - Cornelia Haug
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Rolf Hinzmann
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Roche Diabetes Care GmbH, Mannheim, Germany
| | - Johan Jendle
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - David C. Klonoff
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Diabetes Research Institute of Mills-Peninsula Medical Center, San Mateo, California, USA
| | - Julia K. Mader
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
| | - Konstantinos Makris
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Clinical Biochemistry Department, KAT General Hospital, Athens, Greece
| | - Othmar Moser
- Division of Endocrinology and Diabetology, Medical University of Graz, Graz, Austria
- Department of Exercise Physiology and Metabolism, University of Bayreuth, Bayreuth, Germany
| | - James H. Nichols
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Department of Pathology, Microbiology and Immunology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Kirsten Nørgaard
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark
| | - John Pemberton
- Birmingham Women's and Children's Foundation Trust, Birmingham, United Kingdom
| | - Elizabeth Selvin
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Department of Cardiovascular and Clinical Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Loukia Spanou
- Department of Endocrinology, Diabetes and Metabolism, Hellenic Red Cross Hospital, Athens, Greece
| | - Andreas Thomas
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Independent Scientific Consulting, Pirna, Germany
| | - Nam K. Tran
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Department of Pathology and Laboratory Medicine, University of California Davis Health, Sacramento, California, USA
| | - Lilian Witthauer
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Diabetes Center Berne, Bern, Switzerland
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital Bern, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Robbert J. Slingerland
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
- Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands
| | - Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
- IFCC Scientific Division, Working Group on Continuous Glucose Monitoring
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48
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Tatulashvili S, Dreves B, Meyer L, Cosson E, Joubert M. Carbohydrate counting knowledge and ambulatory glucose profile in persons living with type 1 diabetes. Diabetes Res Clin Pract 2024; 210:111592. [PMID: 38437987 DOI: 10.1016/j.diabres.2024.111592] [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] [Received: 10/10/2023] [Revised: 02/05/2024] [Accepted: 02/22/2024] [Indexed: 03/06/2024]
Abstract
CONTEXT The amount of consumed carbohydrates is the strongest factor influencing glucose levels during the four hours following a meal. Our aim was to evaluate the association between carbohydrate counting knowledge and continuous glucose monitoring (CGM) parameters in patients with type 1 diabetes (T1D) using different insulin regimens. METHOD In this multicenter prospective study, the GluciQuizz questionnaire was used to evaluate carbohydrate knowledge. CGM data for the 14 days preceding completion of the questionnaire were analyzed. The primary endpoint was evaluation of the correlation between the GluciQuizz total score and time in range (TIR) in the study population. RESULTS The mean age of the 170 participants was 40.7 ± 14.8 years and duration of T1D 18.8 ± 12.1 years. The mean GluciQuizz total score for all participants was 66 ± 13 %. Mean TIR was 58.6 ± 18.7 %. GluciQuizz total score positively correlated with TIR (r = 0.3001; p < 0.0001). This correlation was observed in CSII users (r = 0.2526; p < 0.05) but not in MDI (r = 0.2510; p = 0.1134) and HCL users (r = -0.1065; p = 0.4914). TIR was also negatively correlated with the mean carb count error in all study participants (r = -0.2317; p < 0.01). CONCLUSION In conclusion, as the Gluciquizz score was associated with metabolic control, this easy-to-use self-administered questionnaire could be used widely on a routine basis to assess the carbohydrate knowledge of T1D patients and to offer them targeted education tailored to their needs.
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Affiliation(s)
- Sopio Tatulashvili
- AP-HP, Department of Endocrinology-Diabetology-Nutrition, Avicenne Hospital, Université Sorbonne Paris Nord, CINFO, CRNH-IDF, Bobigny, France; Equipe de Recherche en Epidémiologie Nutritionnelle (EREN); Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Bobigny, France
| | | | | | - Emmanuel Cosson
- AP-HP, Department of Endocrinology-Diabetology-Nutrition, Avicenne Hospital, Université Sorbonne Paris Nord, CINFO, CRNH-IDF, Bobigny, France; Equipe de Recherche en Epidémiologie Nutritionnelle (EREN); Université Sorbonne Paris Nord and Université Paris Cité, INSERM, INRAE, CNAM, Center of Research in Epidemiology and StatisticS (CRESS), Bobigny, France
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49
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van Bon AC, Blauw H, Jansen TJP, Laverman GD, Urgert T, Geessink-Mennink J, Mulder AH, Out M, Groote Veldman R, Onvlee AJ, Schouwenberg BJJW, Vermeulen MAR, Diekman MJM, Gerding MN, van Wijk JPH, Klaassen M, Witkop M, DeVries JH. Bihormonal fully closed-loop system for the treatment of type 1 diabetes: a real-world multicentre, prospective, single-arm trial in the Netherlands. Lancet Digit Health 2024; 6:e272-e280. [PMID: 38443309 DOI: 10.1016/s2589-7500(24)00002-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 11/15/2023] [Accepted: 01/05/2024] [Indexed: 03/07/2024]
Abstract
BACKGROUND Management of insulin administration for intake of carbohydrates and physical activity can be burdensome for people with type 1 diabetes on hybrid closed-loop systems. Bihormonal fully closed-loop (FCL) systems could help reduce this burden. In this trial, we assessed the long-term performance and safety of a bihormonal FCL system. METHODS The FCL system (Inreda AP; Inreda Diabetic, Goor, Netherlands) that uses two hormones (insulin and glucagon) was assessed in a 1 year, multicentre, prospective, single-arm intervention trial in adults with type 1 diabetes. Participants were recruited in eight outpatient clinics in the Netherlands. We included adults with type 1 diabetes aged 18-75 years who had been using flash glucose monitoring or continuous glucose monitors for at least 3 months. Study visits were integrated into standard care, usually every three months, to evaluate glycaemic control, adverse events, and person-reported outcomes. The primary endpoint was time in range (TIR; glucose concentration 3·9-10·0 mmol/L) after 1 year. The study is registered in the Dutch Trial Register, NL9578. FINDINGS Between June 1, 2021, and March 2, 2022, we screened 90 individuals and enrolled 82 participants; 78 were included in the analyses. 79 started the intervention and 71 were included in the 12 month analysis. Mean age was 47.7 (SD 12·4) years and 38 (49%) were female participants. The mean preintervention TIR of participants was 55·5% (SD 17·2). After 1 year of FCL treatment, mean TIR was 80·3% (SD 5·4) and median time below range was 1·36% (IQR 0·80-2·11). Questionnaire scores improved on Problem Areas in Diabetes (PAID) from 30·0 (IQR 18·8-41·3) preintervention to 10·0 (IQR 3·8-21·3; p<0·0001) at 12 months and on World Health Organization-Five Well-Being Index (WHO-5) from 60·0 (IQR 44·0-72·0) preintervention to 76·0 (IQR 60·0-80·0; p<0·0001) at 12 months. Five serious adverse events were reported (one cerebellar stroke, two severe hypoglycaemic, and two hyperglycaemic events). INTERPRETATION Real-world data obtained in this trial demonstrate that use of the bihormonal FCL system was associated with good glycaemic control in patients who completed 1 year of treatment, and could help relieve these individuals with type 1 diabetes from making treatment decisions and the burden of carbohydrate counting. FUNDING Inreda Diabetic.
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Affiliation(s)
- A C van Bon
- Department of Internal Medicine, Rijnstate Hospital, Arnhem, Netherlands.
| | - H Blauw
- Inreda Diabetic, Goor, Netherlands
| | | | - G D Laverman
- Department of Internal Medicine, ZGT Hospital, Hengelo, Netherlands
| | - T Urgert
- Department of Internal Medicine, ZGT Hospital, Hengelo, Netherlands
| | - J Geessink-Mennink
- Department of Internal Medicine, Slingeland Hospital, Doetinchem, Netherlands
| | - A H Mulder
- Department of Internal Medicine, Slingeland Hospital, Doetinchem, Netherlands
| | - M Out
- Department of Internal Medicine, MST, Enschede, Netherlands
| | | | - A J Onvlee
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | - B J J W Schouwenberg
- Department of Internal Medicine, Radboud University Medical Center, Nijmegen, Netherlands
| | | | - M J M Diekman
- Department of Internal Medicine, Deventer Hospital, Deventer, Netherlands
| | - M N Gerding
- Department of Internal Medicine, Deventer Hospital, Deventer, Netherlands
| | - J P H van Wijk
- Department of Internal Medicine, Hospital Gelderse Vallei, Ede, Netherlands
| | | | - M Witkop
- Inreda Diabetic, Goor, Netherlands
| | - J H DeVries
- Department of Internal Medicine, Amsterdam UMC, Amsterdam, Netherlands
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50
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Fox DS, Ware J, Boughton CK, Allen JM, Wilinska ME, Tauschmann M, Denvir L, Thankamony A, Campbell F, Wadwa RP, Buckingham BA, Davis N, DiMeglio LA, Mauras N, Besser REJ, Ghatak A, Weinzimer SA, Kanapka L, Kollman C, Sibayan J, Beck RW, Hood KK, Hovorka R. Cost-Effectiveness of Closed-Loop Automated Insulin Delivery Using the Cambridge Hybrid Algorithm in Children and Adolescents with Type 1 Diabetes: Results from a Multicenter 6-Month Randomized Trial. J Diabetes Sci Technol 2024:19322968241231950. [PMID: 38494876 DOI: 10.1177/19322968241231950] [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: 03/19/2024]
Abstract
BACKGROUND/OBJECTIVE The main objective of this study is to evaluate the incremental cost-effectiveness (ICER) of the Cambridge hybrid closed-loop automated insulin delivery (AID) algorithm versus usual care for children and adolescents with type 1 diabetes (T1D). METHODS This multicenter, binational, parallel-controlled trial randomized 133 insulin pump using participants aged 6 to 18 years to either AID (n = 65) or usual care (n = 68) for 6 months. Both within-trial and lifetime cost-effectiveness were analyzed. Analysis focused on the treatment subgroup (n = 21) who received the much more reliable CamAPS FX hardware iteration and their contemporaneous control group (n = 24). Lifetime complications and costs were simulated via an updated Sheffield T1D policy model. RESULTS Within-trial, both groups had indistinguishable and statistically unchanged health-related quality of life, and statistically similar hypoglycemia, severe hypoglycemia, and diabetic ketoacidosis (DKA) event rates. Total health care utilization was higher in the treatment group. Both the overall treatment group and CamAPS FX subgroup exhibited improved HbA1C (-0.32%, 95% CI: -0.59 to -0.04; P = .02, and -1.05%, 95% CI: -1.43 to -0.67; P < .001, respectively). Modeling projected increased expected lifespan of 5.36 years and discounted quality-adjusted life years (QALYs) of 1.16 (U.K. tariffs) and 1.52 (U.S. tariffs) in the CamAPS FX subgroup. Estimated ICERs for the subgroup were £19 324/QALY (United Kingdom) and -$3917/QALY (United States). For subgroup patients already using continuous glucose monitors (CGM), ICERs were £10 096/QALY (United Kingdom) and -$33 616/QALY (United States). Probabilistic sensitivity analysis generated mean ICERs of £19 342/QALY (95% CI: £15 903/QALY to £22 929/QALY) (United Kingdom) and -$28 283/QALY (95% CI: -$59 607/QALY to $1858/QALY) (United States). CONCLUSIONS For children and adolescents with T1D on insulin pump therapy, AID using the Cambridge algorithm appears cost-effective below a £20 000/QALY threshold (United Kingdom) and cost saving (United States).
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Affiliation(s)
- D Steven Fox
- Department of Pharmaceutical and Health Economics, Mann School of Pharmacy, University of Southern California, Los Angeles, CA, USA
| | - Julia Ware
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Diabetes & Endocrinology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Janet M Allen
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Malgorzata E Wilinska
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Martin Tauschmann
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Louise Denvir
- Department of Paediatric Diabetes and Endocrinology, Nottingham University Hospitals NHS Trust, Nottingham, UK
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Fiona Campbell
- Department of Paediatric Diabetes, Leeds Children's Hospital, Leeds, UK
| | - R Paul Wadwa
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Bruce A Buckingham
- Stanford University School of Medicine, Stanford Diabetes Research Center, Stanford, CA, USA
| | - Nikki Davis
- Department of Paediatric Endocrinology and Diabetes, Southampton Children's Hospital, Southampton General Hospital, Southampton, UK
| | - Linda A DiMeglio
- Division of Pediatric Endocrinology and Diabetology, Department of Pediatrics, Wells Center for Pediatric Research, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nelly Mauras
- Nemours Children's Health, Jacksonville, FL, USA
| | - Rachel E J Besser
- Oxford University Hospitals NHS Foundation Trust, NIHR Oxford Biomedical Research Centre, Oxford, UK
- Department of Paediatrics, University of Oxford, Oxford, UK
| | | | | | | | | | - Judy Sibayan
- The Jaeb Center for Health Research, Tampa, FL, USA
| | - Roy W Beck
- The Jaeb Center for Health Research, Tampa, FL, USA
| | - Korey K Hood
- Stanford University School of Medicine, Stanford Diabetes Research Center, Stanford, CA, USA
| | - Roman Hovorka
- Department of Pharmaceutical and Health Economics, Mann School of Pharmacy, University of Southern California, Los Angeles, CA, USA
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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