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Passanisi S, Lombardo F, Mameli C, Bombaci B, Macedoni M, Zuccotti G, Dovc K, Battelino T, Salzano G, Delvecchio M. Safety, Metabolic and Psychological Outcomes of Medtronic MiniMed 780G™ in Children, Adolescents and Young Adults: A Systematic Review. Diabetes Ther 2024; 15:343-365. [PMID: 38038896 PMCID: PMC10838896 DOI: 10.1007/s13300-023-01501-6] [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: 08/11/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023] Open
Abstract
The MiniMed™ 780G is a second-generation automated insulin delivery system that implements a modified proportional-integral-derivative algorithm with some features of an MD-Logic artificial pancreas algorithm. The system may deliver automatic correction boluses up to every 5 min, and it allows the user to choose between three glucose target setpoints (100, 110 and 120 mg/dL). We aimed to review the current evidence on this device in children, adolescents, and young adults living with type 1 diabetes. We screened 783 papers, but only 31 manuscripts were included in this review. Data on metabolic outcomes show that this system is safe as regards severe hypoglycaemia and diabetic ketoacidosis. The glycated haemoglobin may drop to levels about 7%, with CGM reports showing a time in range of 75-80%. The time above range and the time below range are within the recommended target in most of the subjects. Few studies evaluated the psychological outcomes. This system seems to be more effective than the first-generation automated insulin delivery systems. The MiniMed™ 780G has been associated with an improvement in sleep quality in subjects living with diabetes and their caregivers, along with an improvement in treatment satisfaction. Psychological distress is as reduced as the glucose control is improved. We also discuss some case reports describing particular situations in clinical practice. Finally, we think that data show that this system is a further step towards the improvement of the treatment of diabetes as concerns both metabolic and psychological outcomes.
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Affiliation(s)
- Stefano Passanisi
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Fortunato Lombardo
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Chiara Mameli
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Bruno Bombaci
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Maddalena Macedoni
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
| | - Gianvincenzo Zuccotti
- Department of Pediatrics, Buzzi Children's Hospital, University of Milan, Milan, Italy
- Department of Biomedical and Clinical Science, University of Milan, Milan, Italy
| | - Klemen Dovc
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- University Medical Center Ljubljana, University of Ljubljana, Ljubljana, Slovenia
| | - Giuseppina Salzano
- Department of Human Pathology in Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Maurizio Delvecchio
- Department of Biotechnological and Applied Clinical Sciences, University of L'Aquila, L'Aquila, Italy.
- Metabolic Disorders and Clinical Genetics, "Giovanni XXIII" Children's Hospital, AOU Policlinico-Giovanni XXIII, Via Giovanni Amendola 207, 70126, Bari, BA, Italy.
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Nandam N, Thung S, Venkatesh KK, Gabbe S, Ma J, Peng J, Dungan K, Buschur EO. Tandem T:Slim X2 Insulin Pump Use in Clinical Practice Among Pregnant Individuals With Type 1 Diabetes: A Retrospective Observational Cohort Study. Cureus 2024; 16:e52369. [PMID: 38361690 PMCID: PMC10868538 DOI: 10.7759/cureus.52369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/15/2024] [Indexed: 02/17/2024] Open
Abstract
BACKGROUND Insulin pump use is increasing in frequency among pregnant individuals with type 1 diabetes (T1D). Automated insulin delivery (AID) technologies have not been studied extensively in pregnancy. METHOD We present a retrospective case series of eight individuals with T1D who used the Tandem t:slim X2 insulin pump (Tandem Diabetes Care, Inc., CA, USA) during pregnancy. Weekly continuous glucose monitor and insulin pump data were analyzed from electronic medical records and data-sharing portals. Safety, glycemic control, and pregnancy outcomes were examined with both the control IQ (CIQ) and basal IQ (BIQ) algorithms. RESULTS Six CIQ and two BIQ users were studied. The mean glycated hemoglobin (A1C) during pregnancy was 6.1%, and the average time in pregnancy-recommended glycemic range (TIR; 63-140mg/dL) was 67.9%. There were no instances of diabetic ketoacidosis or severe hypoglycemia. CIQ users had a higher mean sensor glucose (127.6 mg/dL) compared to BIQ participants (118.4 mg/dL). However, the average time below range (<63 mg/dL) was 6.1% in BIQ participants compared to 1.5% in CIQ participants. CIQ participants used several strategies to achieve glycemic targets, including daytime use of sleep activity. An increased basal-to-bolus insulin ratio was negatively correlated with TIR (r=-0.415). CONCLUSIONS Tandem t:slim X2 insulin pumps were safely used during pregnancy in eight individuals with T1D, with variable success in achieving recommended glycemic targets. Further research is needed to understand differences in CIQ and BIQ use in pregnancy. AID device manufacturers must additionally develop further methods to target lower glucose for pregnant users.
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Affiliation(s)
- Neeharika Nandam
- Department of Endocrinology, Diabetes, and Metabolism, Cleveland Clinic, Cleveland, USA
| | - Stephen Thung
- Division of Maternal Fetal-Medicine, Department of Obstetrics, Gynecology, and Reproductive Sciences, Yale School of Medicine, Bridgeport, USA
| | - Kartik K Venkatesh
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, Ohio State University Wexner Medical Center, Columbus, USA
| | - Steven Gabbe
- Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, Ohio State University Wexner Medical Center, Columbus, USA
| | - Jianing Ma
- Center for Biostatistics, Ohio State University Wexner Medical Center, Columbus, USA
| | - Jing Peng
- Center for Biostatistics, Ohio State University Wexner Medical Center, Columbus, USA
| | - Kathleen Dungan
- Division of Endocrinology, Diabetes, and Metabolism, Ohio State University Wexner Medical Center, Columbus, USA
| | - Elizabeth O Buschur
- Division of Endocrinology, Diabetes, and Metabolism, Ohio State University Wexner Medical Center, Columbus, USA
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Diaz C JL, Villa-Tamayo MF, Moscoso-Vasquez M, Colmegna P. Simulation-driven optimization of insulin therapy profiles in a commercial hybrid closed-loop system. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2023; 242:107830. [PMID: 37806122 DOI: 10.1016/j.cmpb.2023.107830] [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: 06/07/2023] [Revised: 09/19/2023] [Accepted: 09/23/2023] [Indexed: 10/10/2023]
Abstract
BACKGROUND Automated insulin delivery (AID) has represented a breakthrough in managing type 1 diabetes (T1D), showing safe and effective glucose control extensively across the board. However, metabolic variability still poses a challenge to commercial hybrid closed-loop (HCL) solutions, whose performance depends on customizable insulin therapy profiles. In this work, we propose an Identification-Replay-Optimization (IRO) approach to optimize gradually and safely such profiles for the Control-IQ AID algorithm. METHODS Closed-loop data are generated using the full adult cohort of the UVA/Padova T1D simulation platform in diverse glycemic scenarios. For each subject, daily records are processed and used to estimate a personalized model of the underlying insulin-glucose dynamics. Every two weeks, all identified models are integrated into an optimization procedure where daily basal and bolus profiles are adjusted so as to minimize the risks for hypo- and hyperglycemia. The proposed strategy is tested under different scenarios of metabolic and behavioral variability in order to evaluate the efficacy and convergence of the proposed strategy. Finally, glycemic metrics between cycles are compared using paired t-tests with p<0.05 as the significance threshold. RESULTS Simulations reveal that the proposed IRO approach was able to improve glucose control over time by safely mitigating the risks for both hypo- and hyperglycemia. Furthermore, smaller changes were recommended at each cycle, indicating convergence when simulation conditions were maintained. CONCLUSIONS The use of reliable simulation-driven tools capable of accurately reproducing field-collected data and predicting changes can substantially shorten the process of optimizing insulin therapy, adjusting it to metabolic changes and leading to improved glucose control.
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Affiliation(s)
- Jenny L Diaz C
- Center for Diabetes Technology, University of Virginia, Charlottesville, 22903, VA, USA.
| | - María F Villa-Tamayo
- Center for Diabetes Technology, University of Virginia, Charlottesville, 22903, VA, USA
| | | | - Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, 22903, VA, USA
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Winterdijk P, Aanstoot HJ, Nefs G. The impact of real-time sensor technology on quality of life for adults with type 1 diabetes: A Dutch national survey. Diabetes Res Clin Pract 2023; 203:110886. [PMID: 37604282 DOI: 10.1016/j.diabres.2023.110886] [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: 04/13/2023] [Revised: 07/19/2023] [Accepted: 08/18/2023] [Indexed: 08/23/2023]
Abstract
AIMS To examine the impact of real-time continuous glucose monitoring (RT-CGM) on quality of life in Dutch adults with type 1 diabetes, inside/outside automated insulin delivery (AID) systems. METHODS In this cross-sectional retrospective observational study, RT-CGM users completed an online survey including (adapted) validated questionnaires, study-specific items and open-ended questions. RESULTS Of 893 participating adults, 69% used the RT-CGM as part of AID. The overall sample reported improvements in quality of life related to RT-CGM use (irrespective of initial indication), particularly with respect to physical health, emotional wellbeing and energy. Merits for sleep, intimacy and cognitive diabetes load lagged somewhat behind, mostly when RT-CGM was not integrated in AID. Users of AID had significantly larger improvements in overall quality of life, fatigue and diabetes-specific distress than users of sensor-augmented pump or Open Loop treatment. In regression analyses, user evaluations were associated with perceptions of benefit and burden. In qualitative content analysis, benefits (e.g. life 'normalization', increased perceptions of control) outweighed burdens (e.g. technology frustrations, confrontation with diabetes). CONCLUSIONS RT-CGM positively impacted the quality of life of adults with type 1 diabetes. This justifies a (re-)consideration of broader access. Increased support to maximize device benefits and minimize burdens is also warranted.
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Affiliation(s)
- Per Winterdijk
- Diabeter, Center for Type 1 Diabetes Care and Research, Blaak 6, 3011 TA Rotterdam, the Netherlands.
| | - Henk-Jan Aanstoot
- Diabeter, Center for Type 1 Diabetes Care and Research, Blaak 6, 3011 TA Rotterdam, the Netherlands.
| | - Giesje Nefs
- Diabeter, Center for Type 1 Diabetes Care and Research, Blaak 6, 3011 TA Rotterdam, the Netherlands; Radboud University Medical Center, Department of Medical Psychology, Huispost 926, PO Box 9101, 6500 HB Nijmegen, the Netherlands; Tilburg University, Center of Research on Psychological Disorders and Somatic Diseases (CoRPS), Department of Medical and Clinical Psychology, PO Box 90153, 5000 LE Tilburg, the Netherlands.
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Ghatak A, Boughton CK, Allen JM, Ware J, Wilinska ME, Hartnell S, Thankamony A, Randell T, Besser REJ, Elleri D, Trevelyan N, Campbell FM, Hovorka R. Closed-Loop from Diagnosis of Type 1 Diabetes in Children and Young People. Diabetes Technol Ther 2023; 25:673-674. [PMID: 37384862 DOI: 10.1089/dia.2023.0217] [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] [Indexed: 07/01/2023]
Affiliation(s)
- Atrayee Ghatak
- Department of Diabetes, Alder Hey Children's NHS Foundation Trust, Liverpool, United Kingdom
| | - Charlotte K Boughton
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Janet M Allen
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Julia Ware
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Malgorzata E Wilinska
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
| | - Ajay Thankamony
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
| | - Tabitha Randell
- Department of Paediatric Diabetes and Endocrinology, Nottingham Children's Hospital, Nottingham, United Kingdom
| | - Rachel E J Besser
- Department of Paediatrics, University of Oxford, Oxford, United Kingdom
- NIHR Oxford Biomedical Research Centre, John Radcliffe Hospital, Oxford, United Kingdom
| | - Daniela Elleri
- Department of Diabetes and Endocrinology, Royal Hospital for Children and Young People, Edinburgh, United Kingdom
| | - Nicola Trevelyan
- Department of Paediatrics, Southampton Children's Hospital, Southampton, United Kingdom
| | - Fiona M Campbell
- Department of Paediatric Diabetes, Leeds Children's Hospital, Leeds, United Kingdom
| | - Roman Hovorka
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, United Kingdom
- Department of Paediatrics, University of Cambridge, Cambridge, United Kingdom
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Lakshman R, Boughton C, Hovorka R. The changing landscape of automated insulin delivery in the management of type 1 diabetes. Endocr Connect 2023; 12:e230132. [PMID: 37289734 PMCID: PMC10448576 DOI: 10.1530/ec-23-0132] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Accepted: 06/08/2023] [Indexed: 06/10/2023]
Abstract
Automated insulin delivery systems, also known as closed-loop or 'artificial pancreas' systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonstrating their glycaemic and psychosocial benefits. We also address future directions in automated insulin delivery such as dual-hormone systems and adjunct therapy as well as the challenges around ensuring equitable access to closed-loop technology.
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Affiliation(s)
- Rama Lakshman
- Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
| | - Charlotte Boughton
- Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
- Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Roman Hovorka
- Wellcome-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, UK
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7
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Diaz C. JL, Colmegna P, Breton MD. Maximizing Glycemic Benefits of Using Faster Insulin Formulations in Type 1 Diabetes: In Silico Analysis Under Open- and Closed-Loop Conditions. Diabetes Technol Ther 2023; 25:219-230. [PMID: 36595379 PMCID: PMC10066764 DOI: 10.1089/dia.2022.0468] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Background: Ultrarapid-acting insulin analogs that could improve or even prevent postprandial hyperglycemia are now available for both research and clinical care. However, clear glycemic benefits remain elusive, especially when combined with automated insulin delivery (AID) systems. In this work, we study two insulin formulations in silico and highlight adjustments of both open-loop and closed-loop insulin delivery therapies as a critical step to achieve clinically meaningful improvements. Methods: Subcutaneous insulin transport models for two faster analogs, Fiasp (Novo Nordisk, Bagsværd, Denmark) and AT247 (Arecor, Saffron Walden, United Kingdom), were identified using data collected from prior clamp experiments, and integrated into the UVA/Padova type 1 diabetes simulator (adult cohort, N = 100). Pump therapy parameters and the aggressiveness of our full closed-loop algorithm were adapted to the new insulin pharmacokinetic and pharmacodynamic profiles through a sequence of in silico studies. Finally, we assessed these analogs' glycemic impact with and without modified therapy parameters in simulated conditions designed to match clinical trial data. Results: Simply switching to faster insulin analogs shows limited improvements in glycemic outcomes. However, when insulin acceleration is accompanied by therapy adaptation, clinical significance is found comparing time-in-range (70-180 mg/dL) with Aspart versus AT247 in open-loop (+5.1%); and Aspart versus Fiasp (+5.4%) or AT247 (+10.6%) in full closed-loop with no clinically significant differences in the exposure to hypoglycemia. Conclusion: In silico results suggest that properly adjusting intensive insulin therapy profiles, or AID tuning, to faster insulin analogs is necessary to obtain clinically significant improvements in glucose control.
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Affiliation(s)
- Jenny L. Diaz C.
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Patricio Colmegna
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Marc D. Breton
- Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
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8
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Tseretopoulou X, Viswanath V, Hartnell S, Ware J, Thankamony A, Webb EA, Hysted H, Ashford J, Hendriks E, Teoh Y, Williams RM. Safe and effective use of a hybrid closed-loop system from diagnosis in children under 18 months with type 1 diabetes. Pediatr Diabetes 2022; 23:90-97. [PMID: 34820972 DOI: 10.1111/pedi.13292] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 10/07/2021] [Accepted: 11/15/2021] [Indexed: 11/30/2022] Open
Abstract
The management of type 1 diabetes in infancy presents significant challenges. Hybrid closed loop systems have been shown to be effective in a research setting and are now available for clinical use. There are relatively little reported data regarding their safety and efficacy in a real world clinical setting. We report two cases of very young children diagnosed with type 1 diabetes at ages 18 (Case 1) and 7 months (Case 2), who were commenced on hybrid closed-loop insulin delivery using the CamAPS FX™ system from diagnosis. At diagnosis, total daily dose (TDD) was 6 and 3.3 units for Case 1 and 2, respectively. Closed loop was started during the inpatient stay and weekly follow up was provided via video call on discharge. Seven months from diagnosis, Case 1 has an HbA1C of 49 mmol/mol, 61% time in range (TIR, 3.9-10 mmol/L) with 2% time in hypoglycemia (<3.9 mmol/L) with no incidents of very low blood glucose (BG; <3 mmol/L, 54 mg/dL) over 6 months. Given the extremely small TDD of insulin in Case 2, we elected to use diluted insulin (insulin aspart injection, NovoLog, Novo Nordisk Inc., Plainsboro, NJ, Diluting Medium for NovoLog®). Six months from diagnosis, the estimated HbA1c is 50 mmol/mol, TIR 76% with 1% hypoglycemia and no incidents of very low BG (<3 mmol/L, 54 mg/dL) over 6 months. We conclude that the use hybrid closed-loop can be safe and effective from diagnosis in children under 2 years of age with type 1 diabetes.
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Affiliation(s)
- Xanthippi Tseretopoulou
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Vidya Viswanath
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Julia Ware
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.,Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Ajay Thankamony
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Emma A Webb
- Department of Paediatric Endocrinology and Diabetes, Norfolk and Norwich University Hospital, Norwich, UK.,Norwich Medical School, University of East Anglia, Norwich, UK
| | - Helen Hysted
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Jennifer Ashford
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Emile Hendriks
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK.,Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Yun Teoh
- Pharmacy Department, Cambridge University Hospitals NHS Trust, Cambridge, UK
| | - Rachel M Williams
- Department of Paediatric Endocrinology and Diabetes, Cambridge University Hospitals NHS Trust, Cambridge, UK
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Newman C, Ero A, Dunne FP. Glycaemic control and novel technology management strategies in pregestational diabetes mellitus. Front Endocrinol (Lausanne) 2022; 13:1109825. [PMID: 36714590 PMCID: PMC9877346 DOI: 10.3389/fendo.2022.1109825] [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: 11/28/2022] [Accepted: 12/21/2022] [Indexed: 01/15/2023] Open
Abstract
INTRODUCTION Pregestational diabetes (PGDM) is an increasingly common and complex condition that infers risk to both mother and infant. To prevent serious morbidity, strict glycaemic control is essential. The aim of this review is to review the glucose sensing and insulin delivering technologies currently available for women with PGDM. METHODS We reviewed online databases for articles relating to technology use in pregnancy using a combination of keywords and MeSH headings. Relevant articles are included below. RESULTS A number of technological advancements have improved care and outcomes for women with PGDM. Real time continuous glucose monitoring (rtCGM) offers clear advantages in terms of infants size and neonatal intensive care unit admissions; and further benefits are seen when combined with continuous subcutaneous insulin delivery (insulin pump) and algorithms which continuously adjust insulin levels to glucose targets (hybrid closed loop). Other advancements including flash or intermittent scanning CGM (isCGM) and stand-alone insulin pumps do not confer as many advantages for women and their infants, however they are increasingly used outside of pregnancy and many women enter pregnancy already using these devices. DISCUSSION This article offers a discussion of the most commonly used technologies in pregnancy and evaluates their current and future roles.
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Affiliation(s)
- Christine Newman
- School of Medicine, College of Medicine, Nursing and Health Science, University of Galway, Galway, Ireland
- Department of Diabetes and Endocrinology, Galway University Hospital, Galway, Ireland
- Diabetes Collaborative Clinical Trials Network, University of Galway, Galway, Ireland
- *Correspondence: Christine Newman,
| | - Adesuwa Ero
- Department of Diabetes and Endocrinology, Galway University Hospital, Galway, Ireland
| | - Fidelma P. Dunne
- School of Medicine, College of Medicine, Nursing and Health Science, University of Galway, Galway, Ireland
- Department of Diabetes and Endocrinology, Galway University Hospital, Galway, Ireland
- Diabetes Collaborative Clinical Trials Network, University of Galway, Galway, Ireland
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Pauley ME, Berget C, Messer LH, Forlenza GP. Barriers to Uptake of Insulin Technologies and Novel Solutions. MEDICAL DEVICES-EVIDENCE AND RESEARCH 2021; 14:339-354. [PMID: 34803408 PMCID: PMC8594891 DOI: 10.2147/mder.s312858] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 10/29/2021] [Indexed: 12/15/2022] Open
Abstract
Diabetes-related technology has undergone great advancement in recent years. These technological devices are more commonly utilized in the type 1 diabetes population, which requires insulin as the primary treatment modality. Available devices include insulin pumps, continuous glucose monitors, and hybrid systems referred to as automated insulin delivery systems or hybrid closed-loop systems, which combine those two devices along with software algorithms to achieve advanced therapeutic capabilities, including automatic modulation of insulin delivery based on sensor-derived glucose levels to minimize abnormal glucose trends. Use of diabetes technology is associated with significant positive health and psychosocial outcomes, yet utilization rates are generally lacking across both adult and pediatric type 1 diabetes populations in the United States and other countries. There are consistent themes in existing barriers to technology uptake reported by individuals with type 1 diabetes or parents of children with type 1 diabetes, including physical burdens associated with wearing the devices, concerns in navigating the technology and the devices’ abilities to meet user expectations, high cost, inadequate resources within the healthcare team to support device use, disparities in technology access, and psychosocial barriers. It is important to understand the common barriers to uptake of not only the automated insulin delivery systems but also their component devices (insulin pumps and continuous glucose monitors) to fully support individuals in utilizing these devices and optimizing health benefits. The purpose of this article is to summarize the current automated insulin delivery devices that are available for use in management of type 1 diabetes, review common barriers to uptake of those systems and their component devices, and provide expert opinion on existing and future solutions to identified barriers.
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Affiliation(s)
- Meghan E Pauley
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Cari Berget
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Laurel H Messer
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Gregory P Forlenza
- Barbara Davis Center for Childhood Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
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11
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Pinnaro CT, Tansey MJ. The Evolution of Insulin Administration in Type 1 Diabetes. JOURNAL OF DIABETES MELLITUS 2021; 11:249-277. [PMID: 37745178 PMCID: PMC10516284 DOI: 10.4236/jdm.2021.115021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Insulin has been utilized in the treatment of type 1 diabetes (T1D) for 100 years. While there is still no cure for T1D, insulin administration has undergone a remarkable evolution which has contributed to improvements in quality of life and life expectancy in individuals with T1D. The advent of faster-acting and longer-acting insulins allowed for the implementation of insulin regimens more closely resembling normal insulin physiology. These improvements afforded better glycemic control, which is crucial for limiting microvascular complications and improving T1D outcomes. Suspension of insulin delivery in response to actual and forecasted hypoglycemia has improved quality of life and mitigated hypoglycemia without compromising glycemic control. Advances in continuous glucose monitoring (CGM) and insulin pumps, efforts to model glucose and insulin kinetics, and the application of control theory to T1D have made the automation of insulin delivery a reality. This review will summarize the past, present, and future of insulin administration in T1D.
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Affiliation(s)
- Catherina T Pinnaro
- University of Iowa Stead Family Department of Pediatrics
- Fraternal Order of Eagles Diabetes Research Center
| | - Michael J Tansey
- University of Iowa Stead Family Department of Pediatrics
- Fraternal Order of Eagles Diabetes Research Center
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