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Fabris C, Kovatchev B. Real-Life Use of Automated Insulin Delivery in Individuals With Type 2 Diabetes. J Diabetes Sci Technol 2024:19322968241274786. [PMID: 39180292 DOI: 10.1177/19322968241274786] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/26/2024]
Abstract
BACKGROUND The objective of this work is to document performance of automated insulin delivery (AID) during real-life use in type 2 diabetes (T2D). METHODS A retrospective analysis was performed of continuous glucose monitoring and insulin delivery data from 796 individuals with T2D, who transitioned from 1-month predictive low-glucose suspend (PLGS) use to 3-month AID use, in real-life settings. Primary outcome was change of time in range (TIR = 70-180 mg/dL) from PLGS to AID. Secondary outcomes included time above/below range (TAR/TBR) and total daily insulin (TDI). RESULTS Compared with PLGS, AID increased TIR on average from 63.2% to 72.6%, decreased TAR from 36.2% to 26.8%, and increased TDI from 70.2 to 76.3 U (all P < .001), without significant change to TBR. Glycemic improvements were more pronounced in those with worse glycemic control during PLGS use (P < .001). CONCLUSIONS Real-life use of AID led to a rapid and sustained improvement of glycemic control in individuals with T2D.
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Affiliation(s)
- Chiara Fabris
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
| | - Boris Kovatchev
- Center for Diabetes Technology, Department of Psychiatry and Neurobehavioral Sciences, School of Medicine, University of Virginia, Charlottesville, VA, USA
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Visser MM, Vangoitsenhoven R, Gillard P, Mathieu C. Review Article - Diabetes Technology in the Hospital: An Update. Curr Diab Rep 2024; 24:173-182. [PMID: 38842632 DOI: 10.1007/s11892-024-01545-3] [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] [Accepted: 05/29/2024] [Indexed: 06/07/2024]
Abstract
PURPOSE OF REVIEW There have been many developments in diabetes technology in recent years, with continuous glucose monitoring (CGM), insulin pump therapy (CSII) and automated insulin delivery (AID) becoming progressively accepted in outpatient diabetes care. However, the use of such advanced diabetes technology in the inpatient setting is still limited for several reasons, including logistical challenges and staff training needs. On the other hand, hospital settings with altered diet and stress-induced hyperglycemia often pose challenges to tight glycemic control using conventional treatment tools. Integrating smarter glucose monitoring and insulin delivery devices into the increasingly technical hospital environment could reduce diabetes-related morbidity and mortality. This narrative review describes the most recent literature on the use of diabetes technology in the hospital and suggests avenues for further research. RECENT FINDINGS Advanced diabetes technology has the potential to improve glycemic control in hospitalized people with and without diabetes, and could add particular value in certain conditions, such as nutrition therapy or perioperative management. Taken together, CGM allows for more accurate and patient-friendly follow-up and ad hoc titration of therapy. AID may also provide benefits, including improved glycemic control and reduced nursing workload. Before advanced diabetes technology can be used on a large scale in the hospital, further research is needed on efficacy, accuracy and safety, while implementation factors such as cost and staff training must also be overcome.
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Affiliation(s)
| | | | - Pieter Gillard
- Department of Endocrinology, University Hospitals Leuven, Louvain, Belgium
| | - Chantal Mathieu
- Department of Endocrinology, University Hospitals Leuven, Louvain, Belgium.
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Thabit H, Schofield J. Technology in the management of diabetes in hospitalised adults. Diabetologia 2024:10.1007/s00125-024-06206-4. [PMID: 38953925 DOI: 10.1007/s00125-024-06206-4] [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: 03/04/2024] [Accepted: 05/14/2024] [Indexed: 07/04/2024]
Abstract
Suboptimal glycaemic management in hospitals has been associated with adverse clinical outcomes and increased financial costs to healthcare systems. Despite the availability of guidelines for inpatient glycaemic management, implementation remains challenging because of the increasing workload of clinical staff and rising prevalence of diabetes. The development of novel and innovative technologies that support the clinical workflow and address the unmet need for effective and safe inpatient diabetes care delivery is still needed. There is robust evidence that the use of diabetes technology such as continuous glucose monitoring and closed-loop insulin delivery can improve glycaemic management in outpatient settings; however, relatively little is known of its potential benefits and application in inpatient diabetes management. Emerging data from clinical studies show that diabetes technologies such as integrated clinical decision support systems can potentially mediate safer and more efficient inpatient diabetes care, while continuous glucose sensors and closed-loop systems show early promise in improving inpatient glycaemic management. This review aims to provide an overview of current evidence related to diabetes technology use in non-critical care adult inpatient settings. We highlight existing barriers that may hinder or delay implementation, as well as strategies and opportunities to facilitate the clinical readiness of inpatient diabetes technology in the future.
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Affiliation(s)
- Hood Thabit
- Diabetes, Endocrinology and Metabolism Centre, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester, UK.
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK.
| | - Jonathan Schofield
- Diabetes, Endocrinology and Metabolism Centre, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Diabetes, Endocrinology and Gastroenterology, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
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Liarakos AL, Lim JZM, Leelarathna L, Wilmot EG. The use of technology in type 2 diabetes and prediabetes: a narrative review. Diabetologia 2024:10.1007/s00125-024-06203-7. [PMID: 38951212 DOI: 10.1007/s00125-024-06203-7] [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: 03/05/2024] [Accepted: 05/09/2024] [Indexed: 07/03/2024]
Abstract
The increasing incidence of type 2 diabetes, which represents 90% of diabetes cases globally, is a major public health concern. Improved glucose management reduces the risk of vascular complications and mortality; however, only a small proportion of the type 2 diabetes population have blood glucose levels within the recommended treatment targets. In recent years, diabetes technologies have revolutionised the care of people with type 1 diabetes, and it is becoming increasingly evident that people with type 2 diabetes can also benefit from these advances. In this review, we describe the current knowledge regarding the role of technologies for people living with type 2 diabetes and the evidence supporting their use in clinical practice. We conclude that continuous glucose monitoring systems deliver glycaemic benefits for individuals with type 2 diabetes, whether treated with insulin or non-insulin therapy; further data are required to evaluate the role of these systems in those with prediabetes (defined as impaired glucose tolerance and/or impaired fasting glucose and/or HbA1c levels between 39 mmol/mol [5.7%] and 47 mmol/mol [6.4%]). The use of insulin pumps seems to be safe and effective in people with type 2 diabetes, especially in those with an HbA1c significantly above target. Initial results from studies exploring the impact of closed-loop systems in type 2 diabetes are promising. We discuss directions for future research to fully understand the potential benefits of integrating evidence-based technology into care for people living with type 2 diabetes and prediabetes.
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Affiliation(s)
- Alexandros L Liarakos
- Department of Diabetes and Endocrinology, University Hospitals of Derby and Burton NHS Foundation Trust, Royal Derby Hospital, Derby, UK
- School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK
| | - Jonathan Z M Lim
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Royal Infirmary, Manchester, UK
| | - Lalantha Leelarathna
- Diabetes, Endocrinology and Metabolism Centre, Manchester University NHS Foundation Trust, Manchester Royal Infirmary, Manchester, UK
- Department of Diabetes, Imperial College Healthcare NHS Trust, London, UK
- Faculty of Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Emma G Wilmot
- Department of Diabetes and Endocrinology, University Hospitals of Derby and Burton NHS Foundation Trust, Royal Derby Hospital, Derby, UK.
- School of Medicine, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, UK.
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Amer BE, Yaqout YE, Abozaid AM, Afifi E, Aboelkhier MM. Does fully closed-loop automated insulin delivery improve glycaemic control in patients with type 2 diabetes? A meta-analysis of randomized controlled trials. Diabet Med 2024; 41:e15196. [PMID: 37567739 DOI: 10.1111/dme.15196] [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: 05/31/2023] [Revised: 07/22/2023] [Accepted: 08/09/2023] [Indexed: 08/13/2023]
Abstract
AIMS This meta-analysis investigated the efficacy and safety of fully closed-loop automated insulin delivery (AID) in patients with type 2 diabetes. MATERIALS AND METHODS We systemically searched PubMed, Scopus, Web of Science, and Cochrane Central from inception until April 26, 2023. We included randomized controlled trials (RCTs) comparing fully closed-loop AID versus conventional insulin therapy. The outcomes were pooled as the mean difference (MD) and risk ratio with 95% confidence interval (CI) in the random effect model. Our primary outcome was the proportion of time in the target glucose range (5.6-10 mmol/L, 3.9-10 mmol/L, or 3.9-8 mmol/L, depending on the study). Key secondary outcomes included the proportion of time spent in hyperglycaemia or hypoglycaemia. RESULTS We included seven RCTs (three crossover and four parallel design), compromising 390 patients. Our analysis showed that compared to the control group, fully closed-loop AID increased the proportion of time spent within the target glucose range by additional 337 min per 24 h (MD = 23.39%, 95% CI [16.64%, 30.14%], p < 0.01), additional 108 min overnight (MD = 22.40%, 95% CI [12.88%, 31.91%], p < 0.01), and additional 258 min during the daytime period (MD = 26.85%, 95% CI [21.06%, 32.63%], p < 0.01). Compared to the control group, the overall time in hyperglycaemia was shortened by 326 min per 24 h (MD = -22.67%, 95% CI [-30.87%, -14.46%], p < 0.01). There was no significant difference between the two groups in terms of overall, overnight, and daytime periods spent in hypoglycaemia. CONCLUSIONS Our meta-analysis suggests that fully closed-loop AID may improve glycaemic control in patients with type 2 diabetes, particularly for those with more challenging diabetes management. Further research is required to establish the feasibility of implementing these systems in clinical practice. [Correction added on 26 August 2023 after first online publication: Under Results, the first sentence "We included seven RCTs (three crossover and one parallel designs)" has been changed to "We included seven RCTs (three crossover and four parallel designs)".].
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Affiliation(s)
- Basma Ehab Amer
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Benha University, Benha, Egypt
| | - Yasmeen Essam Yaqout
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Alexandria University, Alexandria, Egypt
| | - Ahmed Mohamed Abozaid
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Tanta University, Tanta, Egypt
| | - Eslam Afifi
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Medicine, Benha University, Benha, Egypt
| | - Menna M Aboelkhier
- Medical Research Group of Egypt, Negida Academy, Arlington, Massachusetts, USA
- Faculty of Science, Cairo University, Cairo, Egypt
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Gómez Medina AM, Henao-Carrillo DC, Yepes C, Silva J, Gómez González JA, Cortes D, Robledo S, Mejía G, Rondon M. Glycemic control metrics in a cohort of hospitalized patients with type 1 diabetes using hybrid closed-loop and advanced hybrid closed-loop systems. Diabetes Res Clin Pract 2023; 204:110897. [PMID: 37678728 DOI: 10.1016/j.diabres.2023.110897] [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: 07/11/2023] [Revised: 08/25/2023] [Accepted: 09/04/2023] [Indexed: 09/09/2023]
Abstract
AIMS To describe Hybrid closed-loop (HCL) and advanced hybrid closed-loop (AHCL) performance in the hospital setting based on the continuous glucose monitoring (CGM) metrics description. METHODS This was an observational study from a cohort of patients with T1D using HCL/AHCL with history of hospitalization. CGM metrics were analyzed during the hospital stay. CGM metrics sub-analysis of the population with active Automated Mode (AM) and SmartGuard (SG) during hospitalization and/or surgical procedure was performed. RESULTS Twenty-four patients were included (50 % women; mean age, 49 years [inter-quartile range (IQR), 39-62 years]). During hospitalization 70.8 % patients achieved %Time in Range (TIR) between 70 and 180 mg/dL ≥ 70 %. The overall %TIR was 75.5 % (IQR, 67.3-81.5 %), % time below range (TBR) < 70 mg/dL was 2.1 % (IQR, 0.7-5.4 %) and %TBR < 54 mg/dL was 0 % (IQR, 0-5.4 %). Users of the AHCL with active SG achieved a non-significant higher %TIR during hospitalization (79 % [73.8.88 %] vs. 76 % [72.81 %], p = 0.312) and had a shorter stay (3[IQR, 2.4] vs. 6 days[IQR, 5.7], p = 0.045) compared to the users of the HCL with AM active. No device-related serious adverse events occurred for users of either system. CONCLUSIONS HCL/AHCL systems with active AM/SG in patients with T1D in the hospital environment leads to %TIR > 70 % in ranges of 70-180 mg/dL in patients without increasing hypoglycemia.
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Affiliation(s)
- Ana María Gómez Medina
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Diana Cristina Henao-Carrillo
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Carlos Yepes
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Julio Silva
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Javier Alberto Gómez González
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - David Cortes
- Endocrinology Unit, Hospital Universitario San Ignacio, Carrera 7 # 45-62, Colombia; Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Sofia Robledo
- Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Gabriela Mejía
- Faculty of Medicine, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
| | - Martin Rondon
- Department of Epidemiology, Pontificia Universidad Javeriana, Carrera 7 # 40-62, Colombia.
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Davis GM, Hughes MS, Brown SA, Sibayan J, Perez-Guzman MC, Stumpf M, Thompson Z, Basina M, Patel RM, Hester J, Abraham A, Ly TT, Chaney C, Tan M, Hsu L, Kollman C, Beck RW, Lal R, Buckingham B, Pasquel FJ. Automated Insulin Delivery with Remote Real-Time Continuous Glucose Monitoring for Hospitalized Patients with Diabetes: A Multicenter, Single-Arm, Feasibility Trial. Diabetes Technol Ther 2023; 25:677-688. [PMID: 37578778 PMCID: PMC10611957 DOI: 10.1089/dia.2023.0304] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Introduction: Multiple daily injection insulin therapy frequently fails to meet hospital glycemic goals and is prone to hypoglycemia. Automated insulin delivery (AID) with remote glucose monitoring offers a solution to these shortcomings. Research Design and Methods: In a single-arm multicenter pilot trial, we tested the feasibility, safety, and effectiveness of the Omnipod 5 AID System with real-time continuous glucose monitoring (CGM) for up to 10 days in hospitalized patients with insulin-requiring diabetes on nonintensive care unit medical-surgical units. Primary endpoints included the proportion of time in automated mode and percent time-in-range (TIR 70-180 mg/dL) among participants with >48 h of CGM data. Safety endpoints included incidence of severe hypoglycemia and diabetes-related ketoacidosis (DKA). Additional glycemic endpoints, CGM accuracy, and patient satisfaction were also explored. Results: Twenty-two participants were enrolled; 18 used the system for a total of 96 days (mean 5.3 ± 3.1 days per patient), and 16 had sufficient CGM data required for analysis. Median percent time in automated mode was 95% (interquartile range 92%-98%) for the 18 system users, and the 16 participants with >48 h of CGM data achieved an overall TIR of 68% ± 16%, with 0.17% ± 0.3% time <70 mg/dL and 0.06% ± 0.2% time <54 mg/dL. Sensor mean glucose was 167 ± 21 mg/dL. There were no DKA or severe hypoglycemic events. All participants reported satisfaction with the system at study end. Conclusions: The use of AID with a disposable tubeless patch-pump along with remote real-time CGM is feasible in the hospital setting. These results warrant further investigation in randomized trials.
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Affiliation(s)
- Georgia M. Davis
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Michael S. Hughes
- Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA
| | - Sue A. Brown
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Judy Sibayan
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - M. Citlalli Perez-Guzman
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Meaghan Stumpf
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | | | - Marina Basina
- Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA
| | - Ronak M. Patel
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Joi Hester
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Amalia Abraham
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Trang T. Ly
- Insulet Corporation, Acton, Massachusetts, USA
| | - Cherie Chaney
- Division of Endocrinology, Center for Diabetes Technology, University of Virginia, Charlottesville, Virginia, USA
| | - Marilyn Tan
- Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA
| | - Liana Hsu
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Craig Kollman
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Roy W. Beck
- Jaeb Center for Health Research, Tampa, Florida, USA
| | - Rayhan Lal
- Division of Endocrinology, Gerontology and Metabolism, Department of Medicine, Stanford University, Stanford, California, USA
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Bruce Buckingham
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California, USA
| | - Francisco J. Pasquel
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, Georgia, USA
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Faggionato E, Guazzo A, Pegolo E, Carli R, Bruschetta M, Favero SD. An Adaptive Model Predictive Controller to Address the Biovariability in Blood Clotting Response During Therapy With Warfarin. IEEE Trans Biomed Eng 2023; 70:2667-2678. [PMID: 37030797 DOI: 10.1109/tbme.2023.3261962] [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: 03/29/2023]
Abstract
OBJECTIVE Effective dosing of anticoagulants aims to prevent blood clot formation while avoiding hemorrhages. This complex task is challenged by several disturbing factors and drug-effect uncertainties, requesting frequent monitoring and adjustment. Biovariability in drug absorption and action further complicates titration and calls for individualized strategies. In this paper, we propose an adaptive closed-loop control algorithm to assist in warfarin therapy management. METHODS The controller was designed and tested in silico using an established pharmacometrics model of warfarin, which accounts for inter-subject variability. The control algorithm is an adaptive Model Predictive Control (a-MPC) that leverages a simplified patient model, whose parameters are updated with a Bayesian strategy. Performance was quantitatively evaluated in simulations performed on a population of virtual subjects against an algorithm reproducing medical guidelines (MG) and an MPC controller available in the literature (l-MPC). RESULTS The proposed a-MPC significantly (p 0.05) lowers rising time (2.8 vs. 4.4 and 11.2 days) and time out of range (3.3 vs. 7.2 and 12.9 days) with respect to both MG and l-MPC, respectively. Adaptivity grants a significantly (p 0.05) lower number of subjects reaching unsafe INR values compared to when this feature is not present (8.9% vs.15% of subjects presenting an overshoot outside the target range and 0.08% vs. 0.28% of subjects reaching dangerous INR values). CONCLUSION The a-MPC algorithm improve warfarin therapy compared to the benchmark therapies. SIGNIFICANCE This in-silico validation proves effectiveness of the a-MPC algorithm for anticoagulant administration, paving the way for clinical testing.
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Lei M, Lin B, Ling P, Liu Z, Yang D, Deng H, Yang X, Lv J, Xu W, Yan J. Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial. BMJ Open 2023; 13:e073263. [PMID: 37558445 PMCID: PMC10414065 DOI: 10.1136/bmjopen-2023-073263] [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: 03/01/2023] [Accepted: 07/28/2023] [Indexed: 08/11/2023] Open
Abstract
INTRODUCTION Do-it-yourself artificial pancreas system (DIY APS) is built using commercially available insulin pump, continuous glucose monitoring (CGM) and an open-source algorithm. Compared with commercial products, DIY systems are affordable, allow personalised settings and provide updated algorithms, making them a more promising therapy for most patients with type 1 diabetes mellitus (T1DM). Many small and self-reported observational studies have found that their real-world use was associated with potential metabolic and psychological benefits. However, rigorous-designed studies are urgently needed to confirm its efficacy and safety. METHODS AND ANALYSIS In this 26-week randomised, open-label, two-arm, two-phase, crossover trial, participants aged 18-75 years, with T1DM and glycated haemoglobin (HbA1c) 7-11%, will use AndroidAPS during one 12-week period and sensor-augmented pump during another 12-week period. This study will recruit at least 24 randomised participants. AndroidAPS consists of three components: (1) real-time CGM; (2) insulin pump; (3) AndroidAPS algorithm implemented in Android smartphone. The primary endpoint is time in range (3.9-10.0 mmol/L) derived from CGM. The main secondary endpoints include percentage of sensor glucose values below, within and above target range; mean sensor glucose value; measures of glycaemic variability and centralised HbA1c. Safety endpoints mainly include the frequency of hypoglycaemia events, diabetic ketoacidosis and other serious adverse events. ETHICS AND DISSEMINATION This study has been approved by the Ethics Committee of the Third Affiliated Hospital of Sun Yat-sen University. There will be verbal and written information regarding the trial given to each participant. The study will be disseminated through peer-reviewed publications and conference presentations. OVERALL STATUS Recruiting. STUDY START 11 February 2023. PRIMARY COMPLETION 31 July 2024. TRIAL REGISTRATION NUMBER ClinicalTrials.gov Registry (NCT05726461).
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Affiliation(s)
- Mengyun Lei
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Beisi Lin
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Ping Ling
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Zhigu Liu
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Daizhi Yang
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Hongrong Deng
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Xubin Yang
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jing Lv
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Wen Xu
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Jinhua Yan
- Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, Third Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, China
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Boughton CK, Hartnell S, Hobday N, Lake A, Davenport K, Daly A, Ward C, Taylor C, Hovorka R, Bansiya V. Implementation of fully closed-loop insulin delivery for inpatients with diabetes: Real-world outcomes. Diabet Med 2023; 40:e15092. [PMID: 36947090 DOI: 10.1111/dme.15092] [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: 01/30/2023] [Revised: 03/06/2023] [Accepted: 03/13/2023] [Indexed: 03/23/2023]
Abstract
AIMS Fully closed-loop insulin delivery has been shown in clinical trials to be safe and improve glucose control compared with standard insulin therapy in the inpatient setting. We investigated the feasibility of implementing the approved CamAPS HX fully closed-loop system in a hospital setting. METHODS This implementation project was conducted in a large teaching hospital in Cambridge, UK. Healthcare professional training was multimodal including face-to-face workshops, online learning modules and supported by standard operating procedures. Set-up and maintenance of closed-loop devices were undertaken by the inpatient diabetes team. Selection of suitable patients was multidisciplinary and prioritised those with more challenging diabetes management. Demographic and clinical data were collected from electronic health records and diabetes data management platforms. RESULTS In the 12 months since the closed-loop system was implemented, 32 inpatients (mean ± SD age 61 ± 16 years, 8 females, 24 males) used closed-loop insulin delivery during their admission, across medical and surgical wards in the hospital with a total of 555 days of closed-loop glucose control (median [IQR]: 14 [6, 22] days per inpatient). The time spent in target glucose range 3.9-10.0 mmol/L was 53.3 ± 18.3%. Mean glucose was 10.7 ± 1.9 mmol/L with 46.0 ± 18.2% of time spent with glucose >10.0 mmol/L. Time spent with sensor glucose below 3.9 mmol/L was low (median [IQR]: 0.38 [0.00, 0.85]). There were no episodes of severe hypoglycaemia or diabetic ketoacidosis during closed-loop use. CONCLUSIONS We have demonstrated that the fully closed-loop system can be safely and effectively implemented by a diabetes outreach team in complex medical and surgical inpatients with challenging glycaemic control.
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Affiliation(s)
- Charlotte K Boughton
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Nicola Hobday
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Andrea Lake
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Katy Davenport
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Aideen Daly
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Candice Ward
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Caroline Taylor
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Roman Hovorka
- Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Vishakha Bansiya
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
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11
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Diez Alvarez S, Fellas A, Santos D, Sculley D, Wynne K, Acharya S, Navathe P, Girones X, Coda A. The Clinical Impact of Flash Glucose Monitoring-a Digital Health App and Smartwatch Technology in Patients With Type 2 Diabetes: Scoping Review. JMIR Diabetes 2023; 8:e42389. [PMID: 36920464 PMCID: PMC10131890 DOI: 10.2196/42389] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 12/29/2022] [Accepted: 01/19/2023] [Indexed: 01/20/2023] Open
Abstract
BACKGROUND Type 2 diabetes has a growing prevalence and confers significant cost burden to the health care system, raising the urgent need for cost-effective and easily accessible solutions. The management of type 2 diabetes requires significant commitment from the patient, caregivers, and the treating team to optimize clinical outcomes and prevent complications. Technology and its implications for the management of type 2 diabetes is a nascent area of research. The impact of some of the more recent technological innovations in this space, such as continuous glucose monitoring, flash glucose monitoring, web-based applications, as well as smartphone- and smart watch-based interactive apps has received limited attention in the research literature. OBJECTIVE This scoping review aims to explore the literature available on type 2 diabetes, flash glucose monitoring, and digital health technology to improve diabetic clinical outcomes and inform future research in this area. METHODS A scoping review was undertaken by searching Ovid MEDLINE and CINAHL databases. A second search using all identified keywords and index terms was performed on Ovid MEDLINE (January 1966 to July 2021), EMBASE (January 1980 to July 2021), Cochrane Central Register of Controlled Trials (CENTRAL; the Cochrane Library, latest issue), CINAHL (from 1982), IEEE Xplore, ACM Digital Libraries, and Web of Science databases. RESULTS There were very few studies that have explored the use of mobile health and flash glucose monitoring in type 2 diabetes. These studies have explored somewhat disparate and limited areas of research, and there is a distinct lack of methodological rigor in this area of research. The 3 studies that met the inclusion criteria have addressed aspects of the proposed research question. CONCLUSIONS This scoping review has highlighted the lack of research in this area, raising the opportunity for further research in this area, focusing on the clinical impact and feasibility of the use of multiple technologies, including flash glucose monitoring in the management of patients with type 2 diabetes.
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Affiliation(s)
- Sergio Diez Alvarez
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Antoni Fellas
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Ourimbah, Australia
| | - Derek Santos
- School of Health Sciences, Queen Margaret University, Edinburgh, United Kingdom
| | - Dean Sculley
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | - Katie Wynne
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
- Equity in Health and Wellbeing Research Program, Hunter Medical Research Institute, Newcastle, Australia
- Department of Diabetes and Endocrinology, Hunter New England Health, John Hunter Hospital, Newcastle, Australia
| | - Shamasunder Acharya
- School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
- Department of Diabetes and Endocrinology, Hunter New England Health, John Hunter Hospital, Newcastle, Australia
| | - Pooshan Navathe
- Central Queensland Hospital and Health Service, Brisbane, Australia
| | - Xavier Girones
- Department of Research, Universities de Catalunya, Generalitat de Catalunya, Barcelona, Cataluna, Spain
| | - Andrea Coda
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Ourimbah, Australia
- Equity in Health and Wellbeing Research Program, Hunter Medical Research Institute, Newcastle, Australia
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12
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Phillip M, Nimri R, Bergenstal RM, Barnard-Kelly K, Danne T, Hovorka R, Kovatchev BP, Messer LH, Parkin CG, Ambler-Osborn L, Amiel SA, Bally L, Beck RW, Biester S, Biester T, Blanchette JE, Bosi E, Boughton CK, Breton MD, Brown SA, Buckingham BA, Cai A, Carlson AL, Castle JR, Choudhary P, Close KL, Cobelli C, Criego AB, Davis E, de Beaufort C, de Bock MI, DeSalvo DJ, DeVries JH, Dovc K, Doyle FJ, Ekhlaspour L, Shvalb NF, Forlenza GP, Gallen G, Garg SK, Gershenoff DC, Gonder-Frederick LA, Haidar A, Hartnell S, Heinemann L, Heller S, Hirsch IB, Hood KK, Isaacs D, Klonoff DC, Kordonouri O, Kowalski A, Laffel L, Lawton J, Lal RA, Leelarathna L, Maahs DM, Murphy HR, Nørgaard K, O’Neal D, Oser S, Oser T, Renard E, Riddell MC, Rodbard D, Russell SJ, Schatz DA, Shah VN, Sherr JL, Simonson GD, Wadwa RP, Ward C, Weinzimer SA, Wilmot EG, Battelino T. Consensus Recommendations for the Use of Automated Insulin Delivery Technologies in Clinical Practice. Endocr Rev 2023; 44:254-280. [PMID: 36066457 PMCID: PMC9985411 DOI: 10.1210/endrev/bnac022] [Citation(s) in RCA: 111] [Impact Index Per Article: 111.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Revised: 07/22/2022] [Indexed: 02/06/2023]
Abstract
The significant and growing global prevalence of diabetes continues to challenge people with diabetes (PwD), healthcare providers, and payers. While maintaining near-normal glucose levels has been shown to prevent or delay the progression of the long-term complications of diabetes, a significant proportion of PwD are not attaining their glycemic goals. During the past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials and real-world studies have shown that the use of AID systems is safe and effective in helping PwD achieve their long-term glycemic goals while reducing hypoglycemia risk. Thus, AID systems have recently become an integral part of diabetes management. However, recommendations for using AID systems in clinical settings have been lacking. Such guided recommendations are critical for AID success and acceptance. All clinicians working with PwD need to become familiar with the available systems in order to eliminate disparities in diabetes quality of care. This report provides much-needed guidance for clinicians who are interested in utilizing AIDs and presents a comprehensive listing of the evidence payers should consider when determining eligibility criteria for AID insurance coverage.
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Affiliation(s)
- Moshe Phillip
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Revital Nimri
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
- Sacker Faculty of Medicine, Tel-Aviv University, 39040 Tel-Aviv, Israel
| | - Richard M Bergenstal
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | | | - Thomas Danne
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Boris P Kovatchev
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Laurel H Messer
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | | | | | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Bern University Hospital and University of Bern, Bern, Switzerland
| | - Roy W Beck
- Jaeb Center for Health Research Foundation, Inc., Tampa, FL 33647, USA
| | - Sarah Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Torben Biester
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | - Julia E Blanchette
- College of Nursing, University of Utah, Salt Lake City, UT 84112, USA
- Center for Diabetes and Obesity, University Hospitals Cleveland Medical Center, Cleveland, OH 44106, USA
| | - Emanuele Bosi
- Diabetes Research Institute, IRCCS San Raffaele Hospital and San Raffaele Vita Salute University, Milan, Italy
| | - Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Marc D Breton
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Sue A Brown
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
- Division of Endocrinology, University of Virginia, Charlottesville, VA 22903, USA
| | - Bruce A Buckingham
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Albert Cai
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Anders L Carlson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Jessica R Castle
- Harold Schnitzer Diabetes Health Center, Oregon Health & Science University, Portland, OR 97239, USA
| | - Pratik Choudhary
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Kelly L Close
- The diaTribe Foundation/Close Concerns, San Diego, CA 94117, USA
| | - Claudio Cobelli
- Department of Woman and Child’s Health, University of Padova, Padova, Italy
| | - Amy B Criego
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Elizabeth Davis
- Telethon Kids Institute, University of Western Australia, Perth Children’s Hospital, Perth, Australia
| | - Carine de Beaufort
- Diabetes & Endocrine Care Clinique Pédiatrique DECCP/Centre Hospitalier Luxembourg, and Faculty of Sciences, Technology and Medicine, University of Luxembourg, Esch sur Alzette, GD Luxembourg/Department of Paediatrics, UZ-VUB, Brussels, Belgium
| | - Martin I de Bock
- Department of Paediatrics, University of Otago, Christchurch, New Zealand
| | - Daniel J DeSalvo
- Division of Pediatric Diabetes and Endocrinology, Baylor College of Medicine, Texas Children’s Hospital, Houston, TX 77598, USA
| | - J Hans DeVries
- Amsterdam UMC, University of Amsterdam, Internal Medicine, Amsterdam, The Netherlands
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Francis J Doyle
- Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA 02138, USA
| | - Laya Ekhlaspour
- Lucile Packard Children’s Hospital—Pediatric Endocrinology, Stanford University School of Medicine, Palo Alto, CA 94304, USA
| | - Naama Fisch Shvalb
- The Jesse Z and Sara Lea Shafer Institute for Endocrinology and Diabetes, National Center for Childhood Diabetes, Schneider Children’s Medical Center of Israel, 49202 Petah Tikva, Israel
| | - Gregory P Forlenza
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | | | - Satish K Garg
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Dana C Gershenoff
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - Linda A Gonder-Frederick
- Center for Diabetes Technology, School of Medicine, University of Virginia, Charlottesville, VA 22903, USA
| | - Ahmad Haidar
- Department of Biomedical Engineering, McGill University, Montreal, Canada
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | | | - Simon Heller
- Department of Oncology and Metabolism, University of Sheffield, Sheffield, UK
| | - Irl B Hirsch
- Department of Medicine, University of Washington Diabetes Institute, University of Washington, Seattle, WA, USA
| | - Korey K Hood
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Diana Isaacs
- Cleveland Clinic, Endocrinology and Metabolism Institute, Cleveland, OH 44106, USA
| | - David C Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA 94010, USA
| | - Olga Kordonouri
- AUF DER BULT, Diabetes-Center for Children and Adolescents, Endocrinology and General Paediatrics, Hannover, Germany
| | | | - Lori Laffel
- Joslin Diabetes Center, Harvard Medical School, Boston, MA 02215, USA
| | - Julia Lawton
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Rayhan A Lal
- Division of Endocrinology, Department of Pediatrics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Lalantha Leelarathna
- Manchester University Hospitals NHS Foundation Trust/University of Manchester, Manchester, UK
| | - David M Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA 94304, USA
| | - Helen R Murphy
- Norwich Medical School, University of East Anglia, Norwich, UK
| | - Kirsten Nørgaard
- Steno Diabetes Center Copenhagen and Department of Clinical Medicine, University of Copenhagen, Gentofte, Denmark
| | - David O’Neal
- Department of Medicine and Department of Endocrinology, St Vincent’s Hospital Melbourne, University of Melbourne, Melbourne, Australia
| | - Sean Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Tamara Oser
- Department of Family Medicine, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Eric Renard
- Department of Endocrinology, Diabetes, Nutrition, Montpellier University Hospital, and Institute of Functional Genomics, University of Montpellier, CNRS, INSERM, Montpellier, France
| | - Michael C Riddell
- School of Kinesiology & Health Science, Muscle Health Research Centre, York University, Toronto, Canada
| | - David Rodbard
- Biomedical Informatics Consultants LLC, Potomac, MD, USA
| | - Steven J Russell
- Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Desmond A Schatz
- Department of Pediatrics, College of Medicine, Diabetes Institute, University of Florida, Gainesville, FL 02114, USA
| | - Viral N Shah
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Jennifer L Sherr
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Gregg D Simonson
- International Diabetes Center, HealthPartners Institute, Minneapolis, MN 55416, USA
| | - R Paul Wadwa
- Barbara Davis Center for Diabetes, University of Colorado Denver—Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Candice Ward
- Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Stuart A Weinzimer
- Department of Pediatrics, Yale University School of Medicine, Pediatric Endocrinology, New Haven, CT 06511, USA
| | - Emma G Wilmot
- Department of Diabetes & Endocrinology, University Hospitals of Derby and Burton NHS Trust, Derby, UK
- Division of Medical Sciences and Graduate Entry Medicine, University of Nottingham, Nottingham, England, UK
| | - Tadej Battelino
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children’s Hospital, Ljubljana, Slovenia, and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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13
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Karol AB, O'Malley G, Fallurin R, Levy CJ. Automated Insulin Delivery Systems as a Treatment for Type 2 Diabetes Mellitus: A Review. Endocr Pract 2023; 29:214-220. [PMID: 36241017 DOI: 10.1016/j.eprac.2022.10.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/29/2022] [Accepted: 10/03/2022] [Indexed: 12/13/2022]
Abstract
OBJECTIVE Approximately 6.3% of the worldwide population has type 2 diabetes mellitus (T2DM), and the number of people requiring insulin is increasing. Automated insulin delivery (AID) systems integrate continuous subcutaneous insulin infusion and continuous glucose monitoring with a predictive control algorithm to provide more physiologic glycemic control. Personalized glycemic targets are recommended in T2DM owing to the heterogeneity of the disease. Based on the success of hybrid closed-loop systems in improving glycemic control and safety in type 1 diabetes mellitus, there has been further interest in the use of these systems in people with T2DM. METHODS We performed a review of AID systems with a focus on the T2DM population. RESULTS In 5 randomized controlled trials, AID systems improve time in range and reduce glycemic variability, without increasing insulin requirements or the risk of hypoglycemia. CONCLUSION AID systems in T2DM are safe and effective in hospitalized and closely monitored settings. Home studies of longer duration are required to assess for long-term benefit and identify target populations of benefit.
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Affiliation(s)
- Alexander B Karol
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Grenye O'Malley
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Reshmitha Fallurin
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Carol J Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York, New York.
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14
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Mader JK, Brix JM, Aberer F, Vonbank A, Resl M, Hochfellner DA, Ress C, Pieber TR, Stechemesser L, Sourij H. [Hospital diabetes management (Update 2023)]. Wien Klin Wochenschr 2023; 135:242-255. [PMID: 37101046 PMCID: PMC10133359 DOI: 10.1007/s00508-023-02177-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/22/2023] [Indexed: 04/28/2023]
Abstract
This position statement presents the recommendations of the Austrian Diabetes Association for diabetes management of adult patients during inpatient stay. It is based on the current evidence with respect to blood glucose targets, insulin therapy and treatment with oral/injectable antidiabetic drugs during inpatient hospitalization. Additionally, special circumstances such as intravenous insulin therapy, concomitant therapy with glucocorticoids and use of diabetes technology during hospitalization are discussed.
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Affiliation(s)
- Julia K Mader
- Klinische Abteilung für Endokrinologie und Diabetologie, Universitätsklinik für Innere Medizin, Medizinische Universität Graz, Auenbruggerplatz 15, 8036, Graz, Österreich.
| | - Johanna M Brix
- Medizinische Abteilung mit Diabetologie, Endokrinologie und Nephrologie, Klinik Landstraße, Wien, Österreich
| | - Felix Aberer
- Klinische Abteilung für Endokrinologie und Diabetologie, Universitätsklinik für Innere Medizin, Medizinische Universität Graz, Auenbruggerplatz 15, 8036, Graz, Österreich
| | - Alexander Vonbank
- Innere Medizin I mit Kardiologie, Angiologie, Endokrinologie, Diabetologie und Intensivmedizin, Akademisches Lehrkrankenhaus Feldkirch, Feldkirch, Österreich
| | - Michael Resl
- Abteilung für Innere Medizin, Konventhospital der Barmherzigen Brüder Linz, Linz, Österreich
| | - Daniel A Hochfellner
- Klinische Abteilung für Endokrinologie und Diabetologie, Universitätsklinik für Innere Medizin, Medizinische Universität Graz, Auenbruggerplatz 15, 8036, Graz, Österreich
| | - Claudia Ress
- Innere Medizin, Department I, Medizinische Universität Innsbruck, Innsbruck, Österreich
| | - Thomas R Pieber
- Klinische Abteilung für Endokrinologie und Diabetologie, Universitätsklinik für Innere Medizin, Medizinische Universität Graz, Auenbruggerplatz 15, 8036, Graz, Österreich
| | - Lars Stechemesser
- Universitätsklinik für Innere Medizin I, Paracelsus Medizinische Privatuniversität - Landeskrankenhaus, Salzburg, Österreich
| | - Harald Sourij
- Klinische Abteilung für Endokrinologie und Diabetologie, Universitätsklinik für Innere Medizin, Medizinische Universität Graz, Auenbruggerplatz 15, 8036, Graz, Österreich
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15
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Daly AB, Boughton CK, Nwokolo M, Hartnell S, Wilinska ME, Cezar A, Evans ML, Hovorka R. Fully automated closed-loop insulin delivery in adults with type 2 diabetes: an open-label, single-center, randomized crossover trial. Nat Med 2023; 29:203-208. [PMID: 36631592 PMCID: PMC9873557 DOI: 10.1038/s41591-022-02144-z] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Accepted: 11/23/2022] [Indexed: 01/13/2023]
Abstract
In adults with type 2 diabetes, the benefits of fully closed-loop insulin delivery, which does not require meal bolusing, are unclear. In an open-label, single-center, randomized crossover study, 26 adults with type 2 diabetes (7 women and 19 men; (mean ± s.d.) age, 59 ± 11 years; baseline glycated hemoglobin (HbA1c), 75 ± 15 mmol mol-1 (9.0% ± 1.4%)) underwent two 8-week periods to compare the CamAPS HX fully closed-loop app with standard insulin therapy and a masked glucose sensor (control) in random order, with a 2-week to 4-week washout between periods. The primary endpoint was proportion of time in target glucose range (3.9-10.0 mmol l-1). Analysis was by intention to treat. Thirty participants were recruited between 16 December 2020 and 24 November 2021, of whom 28 were randomized to two groups (14 to closed-loop therapy first and 14 to control therapy first). Proportion of time in target glucose range (mean ± s.d.) was 66.3% ± 14.9% with closed-loop therapy versus 32.3% ± 24.7% with control therapy (mean difference, 35.3 percentage points; 95% confidence interval (CI), 28.0-42.6 percentage points; P < 0.001). Time > 10.0 mmol l-1 was 33.2% ± 14.8% with closed-loop therapy versus 67.0% ± 25.2% with control therapy (mean difference, -35.2 percentage points; 95% CI, -42.8 to -27.5 percentage points; P < 0.001). Mean glucose was lower during the closed-loop therapy period than during the control therapy period (9.2 ± 1.2 mmol l-1 versus 12.6 ± 3.0 mmol l-1, respectively; mean difference, -3.6 mmol l-1; 95% CI, -4.6 to -2.5 mmol l-1; P < 0.001). HbA1c was lower following closed-loop therapy (57 ± 9 mmol mol-1 (7.3% ± 0.8%)) than following control therapy (72 ± 13 mmol mol-1 (8.7% ± 1.2%); mean difference, -15 mmol mol-1; 95% CI, -11 to -20 mmol l-1 (mean difference, -1.4%; 95% CI, -1.0 to -1.8%); P < 0.001). Time < 3.9 mmol l-1 was similar between treatments (a median of 0.44% (interquartile range, 0.19-0.81%) during the closed-loop therapy period versus a median of 0.08% (interquartile range, 0.00-1.05%) during the control therapy period; P = 0.43). No severe hypoglycemia events occurred in either period. One treatment-related serious adverse event occurred during the closed-loop therapy period. Fully closed-loop insulin delivery improved glucose control without increasing hypoglycemia compared with standard insulin therapy and may represent a safe and efficacious method to improve outcomes in adults with type 2 diabetes. This study is registered with ClinicalTrials.gov (NCT04701424).
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Affiliation(s)
- Aideen B. Daly
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Charlotte K. Boughton
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Munachiso Nwokolo
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Sara Hartnell
- grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Malgorzata E. Wilinska
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Alina Cezar
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Mark L. Evans
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK ,grid.24029.3d0000 0004 0383 8386Cambridge University Hospitals NHS Foundation Trust, Wolfson Diabetes and Endocrine Clinic, Cambridge, UK
| | - Roman Hovorka
- grid.120073.70000 0004 0622 5016Wellcome-MRC Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
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16
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Sherr JL, Heinemann L, Fleming GA, Bergenstal RM, Bruttomesso D, Hanaire H, Holl RW, Petrie JR, Peters AL, Evans M. Automated insulin delivery: benefits, challenges, and recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association. Diabetologia 2023; 66:3-22. [PMID: 36198829 PMCID: PMC9534591 DOI: 10.1007/s00125-022-05744-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/07/2022] [Indexed: 01/15/2023]
Abstract
A technological solution for the management of diabetes in people who require intensive insulin therapy has been sought for decades. The last 10 years have seen substantial growth in devices that can be integrated into clinical care. Driven by the availability of reliable systems for continuous glucose monitoring, we have entered an era in which insulin delivery through insulin pumps can be modulated based on sensor glucose data. Over the past few years, regulatory approval of the first automated insulin delivery (AID) systems has been granted, and these systems have been adopted into clinical care. Additionally, a community of people living with type 1 diabetes has created its own systems using a do-it-yourself approach by using products commercialised for independent use. With several AID systems in development, some of which are anticipated to be granted regulatory approval in the near future, the joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association has created this consensus report. We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions. This is the fourth in a series of reports issued by this working group. The working group was jointly commissioned by the executives of both organisations to write the first statement on insulin pumps, which was published in 2015. The original authoring group was comprised by three nominated members of the American Diabetes Association and three nominated members of the European Association for the Study of Diabetes. Additional authors have been added to the group to increase diversity and range of expertise. Each organisation has provided a similar internal review process for each manuscript prior to submission for editorial review by the two journals. Harmonisation of editorial and substantial modifications has occurred at both levels. The members of the group have selected the subject of each statement and submitted the selection to both organisations for confirmation.
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Affiliation(s)
| | | | | | - Richard M Bergenstal
- International Diabetes Center and HealthPartners Institute, Minneapolis, MN, USA
| | - Daniela Bruttomesso
- Unit of Metabolic Diseases, Department of Medicine, University of Padova, Padova, Italy
| | - Hélène Hanaire
- Department of Diabetology, University Hospital of Toulouse, University of Toulouse, Toulouse, France
| | - Reinhard W Holl
- Institute of Epidemiology and Medical Biometry, Central Institute of Biomedical Engineering (ZIBMT), University of Ulm, Ulm, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - John R Petrie
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Anne L Peters
- Keck School of Medicine of the University of Southern California, Los Angeles, CA, USA
| | - Mark Evans
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
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17
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Polz M, Bergmoser K, Horn M, Schörghuber M, Lozanović J, Rienmüller T, Baumgartner C. A system theory based digital model for predicting the cumulative fluid balance course in intensive care patients. Front Physiol 2023; 14:1101966. [PMID: 37123264 PMCID: PMC10133509 DOI: 10.3389/fphys.2023.1101966] [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] [Received: 11/18/2022] [Accepted: 04/04/2023] [Indexed: 05/02/2023] Open
Abstract
Background: Surgical interventions can cause severe fluid imbalances in patients undergoing cardiac surgery, affecting length of hospital stay and survival. Therefore, appropriate management of daily fluid goals is a key element of postoperative intensive care in these patients. Because fluid balance is influenced by a complex interplay of patient-, surgery- and intensive care unit (ICU)-specific factors, fluid prediction is difficult and often inaccurate. Methods: A novel system theory based digital model for cumulative fluid balance (CFB) prediction is presented using recorded patient fluid data as the sole parameter source by applying the concept of a transfer function. Using a retrospective dataset of n = 618 cardiac intensive care patients, patient-individual models were created and evaluated. RMSE analyses and error calculations were performed for reasonable combinations of model estimation periods and clinically relevant prediction horizons for CFB. Results: Our models have shown that a clinically relevant time horizon for CFB prediction with the combination of 48 h estimation time and 8-16 h prediction time achieves high accuracy. With an 8-h prediction time, nearly 50% of CFB predictions are within ±0.5 L, and 77% are still within the clinically acceptable range of ±1.0 L. Conclusion: Our study has provided a promising proof of principle and may form the basis for further efforts in the development of computational models for fluid prediction that do not require large datasets for training and validation, as is the case with machine learning or AI-based models. The adaptive transfer function approach allows estimation of CFB course on a dynamically changing patient fluid balance system by simulating the response to the current fluid management regime, providing a useful digital tool for clinicians in daily intensive care.
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Affiliation(s)
- Mathias Polz
- Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, STM, Austria
| | - Katharina Bergmoser
- Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, STM, Austria
- CBmed Center for Biomarker Research in Medicine, Graz, STM, Austria
| | - Martin Horn
- Institute of Automation and Control, Graz University of Technology, Graz, STM, Austria
| | - Michael Schörghuber
- Department of Anesthesiology and Intensive Care Medicine, Medical University of Graz, Graz, STM, Austria
| | - Jasmina Lozanović
- Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, STM, Austria
| | - Theresa Rienmüller
- Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, STM, Austria
| | - Christian Baumgartner
- Institute of Health Care Engineering with European Testing Center of Medical Devices, Graz University of Technology, Graz, STM, Austria
- *Correspondence: Christian Baumgartner,
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18
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19
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Avari P, Lumb A, Flanagan D, Rayman G, Misra S, Choudhary P, Dhatariya K. Insulin Pumps and Hybrid Close Loop Systems Within Hospital: A Scoping Review and Practical Guidance From the Joint British Diabetes Societies for Inpatient Care. J Diabetes Sci Technol 2022; 17:625-634. [PMID: 36458697 DOI: 10.1177/19322968221137335] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
This article is the second of a two-part series providing a scoping review and summary of the Joint British Diabetes Societies for Inpatient Care (JBDS-IP) guidelines on the use of diabetes technology in people with diabetes admitted to hospital. The first part reviewed the use of continuous glucose monitoring (CGM) in hospital. In this article, we focus on the use of continuous subcutaneous insulin infusion (CSII; insulin pumps) and hybrid closed-loop systems in hospital. JBDS-IP advocates enabling people who can self-manage and are willing and capable of using CSII to continue doing so as they would do out of hospital. CSII should be discontinued if the individual is critically ill or hemodynamically unstable. For individuals on hybrid closed-loop systems, the system should be discontinued from auto-mode, and may be used individually (as CGM only or CSII only, if criteria are met). Continuing in closed-loop mode may only be done so under specialist guidance from the Diabetes Team, where the diabetes teams are comfortable and knowledgeable about the specific devices used. Health care organizations need to have clear local policies and guidance to support individuals using these wearable technologies, and ensure the relevant workforce is capable and skilled enough to ensure their safe use within the hospital setting.
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Affiliation(s)
- Parizad Avari
- Department of Diabetes and Endocrinology, Imperial College Healthcare NHS Trust, London, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Alistair Lumb
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Churchill Hospital, Oxford, UK
| | - Daniel Flanagan
- Department of Endocrinology, University Hospital Plymouth, Plymouth, UK
| | - Gerry Rayman
- Ipswich Diabetes Centre, East Suffolk and North East Essex Foundation Trust, Ipswich, UK
| | - Shivani Misra
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Pratik Choudhary
- Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Ketan Dhatariya
- Elsie Bertram Diabetes Centre, Norfolk and Norwich University Hospitals NHS Foundation Trust, Norwich, UK
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20
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Sherr JL, Heinemann L, Fleming GA, Bergenstal RM, Bruttomesso D, Hanaire H, Holl RW, Petrie JR, Peters AL, Evans M. Automated Insulin Delivery: Benefits, Challenges, and Recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association. Diabetes Care 2022; 45:3058-3074. [PMID: 36202061 DOI: 10.2337/dci22-0018] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/07/2022] [Indexed: 02/03/2023]
Abstract
A technological solution for the management of diabetes in people who require intensive insulin therapy has been sought for decades. The last 10 years have seen substantial growth in devices that can be integrated into clinical care. Driven by the availability of reliable systems for continuous glucose monitoring, we have entered an era in which insulin delivery through insulin pumps can be modulated based on sensor glucose data. Over the past few years, regulatory approval of the first automated insulin delivery (AID) systems has been granted, and these systems have been adopted into clinical care. Additionally, a community of people living with type 1 diabetes has created its own systems using a do-it-yourself approach by using products commercialized for independent use. With several AID systems in development, some of which are anticipated to be granted regulatory approval in the near future, the joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association has created this consensus report. We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions. This is the fourth in a series of reports issued by this working group. The working group was jointly commissioned by the executives of both organizations to write the first statement on insulin pumps, which was published in 2015. The original authoring group was comprised by three nominated members of the American Diabetes Association and three nominated members of the European Association for the Study of Diabetes. Additional authors have been added to the group to increase diversity and range of expertise. Each organization has provided a similar internal review process for each manuscript prior to submission for editorial review by the two journals. Harmonization of editorial and substantial modifications has occurred at both levels. The members of the group have selected the subject of each statement and submitted the selection to both organizations for confirmation.
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Affiliation(s)
| | | | | | | | - Daniela Bruttomesso
- Unit of Metabolic Diseases, Department of Medicine, University of Padova, Padova, Italy
| | - Hélène Hanaire
- Department of Diabetology, University Hospital of Toulouse, University of Toulouse, Toulouse, France
| | - Reinhard W Holl
- Institute of Epidemiology and Medical Biometry, Central Institute of Biomedical Engineering (ZIBMT), University of Ulm, Ulm, Germany.,German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - John R Petrie
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Anne L Peters
- Keck School of Medicine of the University of Southern California, Los Angeles, CA
| | - Mark Evans
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, U.K
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21
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Rodríguez-Sarmiento DL, León-Vargas F, García-Jaramillo M. Artificial pancreas systems: experiences from concept to commercialisation. Expert Rev Med Devices 2022; 19:877-894. [DOI: 10.1080/17434440.2022.2150546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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22
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Buschur EO, Faulds E, Dungan K. CGM in the Hospital: Is It Ready for Prime Time? Curr Diab Rep 2022; 22:451-460. [PMID: 35796882 PMCID: PMC9261155 DOI: 10.1007/s11892-022-01484-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 02/24/2022] [Indexed: 01/08/2023]
Abstract
PURPOSE OF REVIEW The use of continuous glucose monitoring (CGM) in the hospital setting is growing with more patients using these devices at home and when admitted to the hospital, especially during the COVID-19 pandemic. RECENT FINDINGS Historically, most evidence for CGM use in the inpatient setting was limited to small studies utilizing outdated CGM technology and analyzing accuracy of sensor measurements. Previous studies have shown reduced sensor accuracy during extreme hypo- or hyperglycemia, rapid fluctuations of glucose, compression of the sensor itself, and in those who are critically ill. Studies that are more recent have shown CGM to have adequate accuracy and may be effective in reducing hypoglycemia in hospitalized patients; some studies have also showed improvement in time in target glycemic range. Furthermore, CGM may reduce nursing workload, cost of inpatient care, and use of personal protective equipment and face-to-face patient care especially for patients during the COVID-19 pandemic. This review will describe the evidence for use of CGM in hospitalized critically ill or non-critically ill patients, address accuracy and safety considerations, and outline paths for future implementation.
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Affiliation(s)
- Elizabeth O. Buschur
- grid.261331.40000 0001 2285 7943Division of Endocrinology, Diabetes & Metabolism, The Ohio State University College of Medicine, 5th Floor McCampbell Hall, 1581 Dodd Drive, Columbus, OH 43210-1296 USA
| | - Eileen Faulds
- grid.261331.40000 0001 2285 7943Division of Endocrinology, Diabetes & Metabolism, The Ohio State University College of Medicine, 5th Floor McCampbell Hall, 1581 Dodd Drive, Columbus, OH 43210-1296 USA
- grid.261331.40000 0001 2285 7943The Ohio State University College of Nursing, Columbus, OH USA
| | - Kathleen Dungan
- grid.261331.40000 0001 2285 7943Division of Endocrinology, Diabetes & Metabolism, The Ohio State University College of Medicine, 5th Floor McCampbell Hall, 1581 Dodd Drive, Columbus, OH 43210-1296 USA
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23
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Korytkowski MT, Muniyappa R, Antinori-Lent K, Donihi AC, Drincic AT, Hirsch IB, Luger A, McDonnell ME, Murad MH, Nielsen C, Pegg C, Rushakoff RJ, Santesso N, Umpierrez GE. Management of Hyperglycemia in Hospitalized Adult Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline. J Clin Endocrinol Metab 2022; 107:2101-2128. [PMID: 35690958 PMCID: PMC9653018 DOI: 10.1210/clinem/dgac278] [Citation(s) in RCA: 83] [Impact Index Per Article: 41.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Indexed: 02/08/2023]
Abstract
BACKGROUND Adult patients with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. These patients are at increased risk for adverse clinical outcomes in the absence of defined approaches to glycemic management. OBJECTIVE To review and update the 2012 Management of Hyperglycemia in Hospitalized Patients in Non-Critical Care Settings: An Endocrine Society Clinical Practice Guideline and to address emerging areas specific to the target population of noncritically ill hospitalized patients with diabetes or newly recognized or stress-induced hyperglycemia. METHODS A multidisciplinary panel of clinician experts, together with a patient representative and experts in systematic reviews and guideline development, identified and prioritized 10 clinical questions related to inpatient management of patients with diabetes and/or hyperglycemia. The systematic reviews queried electronic databases for studies relevant to the selected questions. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess the certainty of evidence and make recommendations. RESULTS The panel agreed on 10 frequently encountered areas specific to glycemic management in the hospital for which 15 recommendations were made. The guideline includes conditional recommendations for hospital use of emerging diabetes technologies including continuous glucose monitoring and insulin pump therapy; insulin regimens for prandial insulin dosing, glucocorticoid, and enteral nutrition-associated hyperglycemia; and use of noninsulin therapies. Recommendations were also made for issues relating to preoperative glycemic measures, appropriate use of correctional insulin, and diabetes self-management education in the hospital. A conditional recommendation was made against preoperative use of caloric beverages in patients with diabetes. CONCLUSION The recommendations are based on the consideration of important outcomes, practicality, feasibility, and patient values and preferences. These recommendations can be used to inform system improvement and clinical practice for this frequently encountered inpatient population.
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Affiliation(s)
- Mary T Korytkowski
- University of Pittsburgh, Division of Endocrinology, Department of Medicine, Pittsburgh, PA, USA
| | - Ranganath Muniyappa
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, MD, USA
| | | | - Amy C Donihi
- University of Pittsburgh School of Pharmacy, Department of Pharmacy and Therapeutics, Pittsburgh, PA, USA
| | - Andjela T Drincic
- University of Nebraska Medical Center, Endocrinology & Metabolism, Omaha, NE, USA
| | - Irl B Hirsch
- University of Washington Diabetes Institute, Seattle, WA, USA
| | - Anton Luger
- Medical University and General Hospital of Vienna, Department of Medicine III, Medical University of Vienna, Vienna, Austria
| | - Marie E McDonnell
- Brigham and Women’s Hospital and Harvard Medical School, Division of Endocrinology Diabetes and Hypertension, Boston, MA, USA
| | - M Hassan Murad
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | | | - Claire Pegg
- Diabetes Patient Advocacy Coalition, Tampa, FL, USA
| | - Robert J Rushakoff
- University of California, San Francisco, Department of Medicine, Division of Endocrinology and Metabolism, San Francisco, CA, USA
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24
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Seisa MO, Saadi S, Nayfeh T, Muthusamy K, Shah SH, Firwana M, Hasan B, Jawaid T, Abd-Rabu R, Korytkowski MT, Muniyappa R, Antinori-Lent K, Donihi AC, Drincic AT, Luger A, Torres Roldan VD, Urtecho M, Wang Z, Murad MH. A Systematic Review Supporting the Endocrine Society Clinical Practice Guideline for the Management of Hyperglycemia in Adults Hospitalized for Noncritical Illness or Undergoing Elective Surgical Procedures. J Clin Endocrinol Metab 2022; 107:2139-2147. [PMID: 35690929 PMCID: PMC9653020 DOI: 10.1210/clinem/dgac277] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Indexed: 12/21/2022]
Abstract
CONTEXT Individuals with diabetes or newly recognized hyperglycemia account for over 30% of noncritically ill hospitalized patients. Management of hyperglycemia in these patients is challenging. OBJECTIVE To support development of the Endocrine Society Clinical Practice Guideline for management of hyperglycemia in adults hospitalized for noncritical illness or undergoing elective surgical procedures. METHODS We searched several databases for studies addressing 10 questions provided by a guideline panel from the Endocrine Society. Meta-analysis was conducted when feasible. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology was used to assess certainty of evidence. RESULTS We included 94 studies reporting on 135 553 patients. Compared with capillary blood glucose, continuous glucose monitoring increased the number of patients identified with hypoglycemia and decreased mean daily blood glucose (BG) (very low certainty). Data on continuation of insulin pump therapy in hospitalized adults were sparse. In hospitalized patients receiving glucocorticoids, combination neutral protamine hagedorn (NPH) and basal-bolus insulin was associated with lower mean BG compared to basal-bolus insulin alone (very low certainty). Data on NPH insulin vs basal-bolus insulin in hospitalized adults receiving enteral nutrition were inconclusive. Inpatient diabetes education was associated with lower HbA1c at 3 and 6 months after discharge (moderate certainty) and reduced hospital readmissions (very low certainty). Preoperative HbA1c level < 7% was associated with shorter length of stay, lower postoperative BG and a lower number of neurological complications and infections, but a higher number of reoperations (very low certainty). Treatment with glucagon-like peptide-1 agonists or dipeptidyl peptidase-4 inhibitors in hospitalized patients with type 2 diabetes and mild hyperglycemia was associated with lower frequency of hypoglycemic events than insulin therapy (low certainty). Caloric oral fluids before surgery in adults with diabetes undergoing surgical procedures did not affect outcomes (very low certainty). Counting carbohydrates for prandial insulin dosing did not affect outcomes (very low certainty). Compared with scheduled insulin (basal-bolus or basal insulin + correctional insulin), correctional insulin was associated with higher mean daily BG and fewer hypoglycemic events (low certainty). CONCLUSION The certainty of evidence supporting many hyperglycemia management decisions is low, emphasizing importance of shared decision-making and consideration of other decisional factors.
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Affiliation(s)
- Mohamed O Seisa
- Correspondence: Mohamed Seisa, M.D., Mayo Clinic Rochester, Rochester, MN 55902, USA.
| | - Samer Saadi
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | - Tarek Nayfeh
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | | | - Sahrish H Shah
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | | | - Bashar Hasan
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | - Tabinda Jawaid
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | - Rami Abd-Rabu
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | | | - Ranganath Muniyappa
- National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland 20892, USA
| | | | - Amy C Donihi
- University of Pittsburgh School of Pharmacy,Pittsburgh, PA 15261, USA
| | | | - Anton Luger
- Medical University and General Hospital of Vienna, Austria
| | | | | | - Zhen Wang
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
| | - M Hassan Murad
- Mayo Clinic Evidence-Based Practice Center, Rochester, MN, USA
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25
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Piya MK, Fletcher T, Myint KP, Zarora R, Yu D, Simmons D. The impact of nursing staff education on diabetes inpatient glucose management: a pilot cluster randomised controlled trial. BMC Endocr Disord 2022; 22:61. [PMID: 35272649 PMCID: PMC8911103 DOI: 10.1186/s12902-022-00975-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2021] [Accepted: 03/01/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND An increasing number of patients in hospital have diabetes, with most of them cared for by non-specialist staff. The effect of diabetes education for staff on patient outcomes, as well as the most effective method of staff education is unclear. Therefore, the aim of this study was to compare diabetes outcomes in medical wards where nursing staff were offered one face-to-face (F2F) session followed by access to online education (online), F2F education only, or standard care (control). METHODS We conducted a pilot cluster randomised controlled trial involving 16-weeks baseline/rollout followed by a 28-week post-intervention period across three medical wards (clusters) in a Sydney Teaching Hospital. The online ward provided an online competency-based diabetes education program and 1-h F2F teaching from a diabetes nurse educator (DNE), the F2F ward provided four separate 1-h teaching sessions by a DNE, with no additional sessions in the control ward. The primary outcome was length of stay (LOS); secondary outcomes included good diabetes days (GDD), hypoglycaemia and medication errors. Poisson and binary logistic regression were used to compare clusters. RESULTS Staff attendance/completion of ≥ 2 topics was greater with online than F2F education [39/48 (81%) vs 10/33 (30%); p < 0.001]. Among the 827/881 patients, there was no difference in LOS change between online [Median(IQR) 5(2-8) to 4(2-7) days], F2F [7(4-14) to 5(3-13) days] or control wards [5(3-9) to 5(3-7) days]. GDD improved only in the online ward 4.7(2.7-7.0) to 6.0(2.3-7.0) days; p = 0.038. Total patients with hypoglycaemia and appropriately treated hypoglycaemia increased in the online ward. CONCLUSIONS The inclusion of online education increased diabetes training uptake among nursing staff. GDD and appropriate hypoglycaemia management increased in the online education wards. TRIAL REGISTRATION Prospectively registered on the Australia New Zealand Clinical Trials Registry (ANZCTR) on 24/05/2017: ACTRN12617000762358 .
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Affiliation(s)
- Milan K Piya
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia.
- Macarthur Diabetes Endocrinology and Metabolism Service, Camden and Campbelltown Hospitals, Campbelltown, NSW, Australia.
| | - Therese Fletcher
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
- Macarthur Diabetes Endocrinology and Metabolism Service, Camden and Campbelltown Hospitals, Campbelltown, NSW, Australia
| | - Kyaw P Myint
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
| | - Reetu Zarora
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
| | - Dahai Yu
- Primary Care Centre Versus Arthritis, School of Medicine, Keele University, Staffordshire, UK
| | - David Simmons
- School of Medicine, Western Sydney University, Campbelltown, NSW, Australia
- Macarthur Diabetes Endocrinology and Metabolism Service, Camden and Campbelltown Hospitals, Campbelltown, NSW, Australia
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26
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Braune K, Lal RA, Petruželková L, Scheiner G, Winterdijk P, Schmidt S, Raimond L, Hood KK, Riddell MC, Skinner TC, Raile K, Hussain S. Open-source automated insulin delivery: international consensus statement and practical guidance for health-care professionals. Lancet Diabetes Endocrinol 2022; 10:58-74. [PMID: 34785000 PMCID: PMC8720075 DOI: 10.1016/s2213-8587(21)00267-9] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/01/2021] [Revised: 09/14/2021] [Accepted: 09/15/2021] [Indexed: 01/15/2023]
Abstract
Open-source automated insulin delivery systems, commonly referred to as do-it-yourself automated insulin delivery systems, are examples of user-driven innovations that were co-created and supported by an online community who were directly affected by diabetes. Their uptake continues to increase globally, with current estimates suggesting several thousand active users worldwide. Real-world user-driven evidence is growing and provides insights into safety and effectiveness of these systems. The aim of this consensus statement is two-fold. Firstly, it provides a review of the current evidence, description of the technologies, and discusses the ethics and legal considerations for these systems from an international perspective. Secondly, it provides a much-needed international health-care consensus supporting the implementation of open-source systems in clinical settings, with detailed clinical guidance. This consensus also provides important recommendations for key stakeholders that are involved in diabetes technologies, including developers, regulators, and industry, and provides medico-legal and ethical support for patient-driven, open-source innovations.
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Affiliation(s)
- Katarina Braune
- Department of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany; Institute of Medical Informatics, Charité-Universitätsmedizin Berlin, Berlin, Germany; Berlin Institute of Health, Berlin, Germany
| | - Rayhan A Lal
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford University, Stanford, CA, USA.
| | - Lenka Petruželková
- Department of Pediatrics, University Hospital Motol, Prague, Czech Republic
| | | | - Per Winterdijk
- Diabeter, Center for Pediatric and Adult Diabetes Care and Research, Rotterdam, Netherlands
| | | | | | - Korey K Hood
- Stanford Diabetes Research Center, Stanford University School of Medicine, Stanford University, Stanford, CA, USA
| | | | - Timothy C Skinner
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark; La Trobe Rural Health School, La Trobe University, Bendigo, VIC, Australia
| | - Klemens Raile
- Department of Paediatric Endocrinology and Diabetes, Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Sufyan Hussain
- Department of Diabetes and Endocrinology, Guy's and St Thomas' Hospital NHS Trust, London, UK; Department of Diabetes, King's College London, London, UK; Institute of Diabetes, Endocrinology and Obesity, King's Health Partners, London, UK.
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Biester T, Tauschmann M, Chobot A, Kordonouri O, Danne T, Kapellen T, Dovc K. The automated pancreas: A review of technologies and clinical practice. Diabetes Obes Metab 2022; 24 Suppl 1:43-57. [PMID: 34658126 DOI: 10.1111/dom.14576] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2021] [Revised: 10/07/2021] [Accepted: 10/07/2021] [Indexed: 12/12/2022]
Abstract
Insulin pumps and glucose sensors are effective in improving diabetes therapy and reducing acute complications. The combination of both devices using an algorithm-driven interoperable controller makes automated insulin delivery (AID) systems possible. Many AID systems have been tested in clinical trials and have proven safety and effectiveness. However, currently, none of these systems are available for routine use in children younger than 6 years in Europe. For continued use, both users and prescribers must have sound knowledge of the features of the individual AID systems. Presently, all systems require various user interactions (e.g. meal announcements) because fully automated systems are not yet developed. Open-source systems are non-regulated variants to circumvent existing regulatory conditions. There are risks here for both users and prescribers. To evaluate AID therapy, the metric data of the glucose sensors, 'time in target range' and 'glucose management index', are novel recognized and suitable parameters allowing a consultation based on real glucose and insulin pump download data from the daily life of people with diabetes. Read out via cloud-based software or automatic download of such individual treatment data provides the ideal technical basis for shared decision-making through telemedicine, which must be further evaluated for general use.
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Affiliation(s)
- Torben Biester
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Martin Tauschmann
- Department of Pediatric and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Agata Chobot
- Department of Pediatrics, Institute of Medical Sciences, University of Opole, Opole, Poland
| | - Olga Kordonouri
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Thomas Danne
- AUF DER BULT, Diabetes Center for Children and Adolescents, Hannover, Germany
| | - Thomas Kapellen
- Department of Pediatrics, MEDIAN Clinic for Children 'Am Nicolausholz' Bad Kösen, Naumburg, Germany
| | - Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, Ljubljana, Slovenia and Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
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Moon SJ, Jung I, Park CY. Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence. Diabetes Metab J 2021; 45:813-839. [PMID: 34847641 PMCID: PMC8640161 DOI: 10.4093/dmj.2021.0177] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 10/24/2021] [Indexed: 12/19/2022] Open
Abstract
Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.
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Affiliation(s)
- Sun Joon Moon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Inha Jung
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Cheol-Young Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
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Fully automated closed-loop glucose control compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis: an open-label, randomized crossover trial. Nat Med 2021; 27:1471-1476. [PMID: 34349267 PMCID: PMC8363503 DOI: 10.1038/s41591-021-01453-z] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/28/2021] [Indexed: 12/18/2022]
Abstract
We evaluated the safety and efficacy of fully closed-loop insulin therapy compared with standard insulin therapy in adults with type 2 diabetes requiring dialysis. In an open-label, multinational, two-center, randomized crossover trial, 26 adults with type 2 diabetes requiring dialysis (17 men, 9 women, average age 68 ± 11 years (mean ± s.d.), diabetes duration of 20 ± 10 years) underwent two 20-day periods of unrestricted living, comparing the Cambridge fully closed-loop system using faster insulin aspart (‘closed-loop’) with standard insulin therapy and a masked continuous glucose monitor (‘control’) in random order. The primary endpoint was time in target glucose range (5.6–10.0 mmol l−1). Thirteen participants received closed-loop first and thirteen received control therapy first. The proportion of time in target glucose range (5.6–10.0 mmol l−1; primary endpoint) was 52.8 ± 12.5% with closed-loop versus 37.7 ± 20.5% with control; mean difference, 15.1 percentage points (95% CI 8.0–22.2; P < 0.001). Mean glucose was lower with closed-loop than control (10.1 ± 1.3 versus 11.6 ± 2.8 mmol l−1; P = 0.003). Time in hypoglycemia (<3.9 mmol l−1) was reduced with closed-loop versus control (median (IQR) 0.1 (0.0–0.4%) versus 0.2 (0.0–0.9%); P = 0.040). No severe hypoglycemia events occurred during the control period, whereas one severe hypoglycemic event occurred during the closed-loop period, but not during closed-loop operation. Fully closed-loop improved glucose control and reduced hypoglycemia compared with standard insulin therapy in adult outpatients with type 2 diabetes requiring dialysis. The trial registration number is NCT04025775. A new randomized, crossover clinical trial testing rapid-acting insulin aspart delivered in a closed-loop system compared with standard care demonstrates increased time in range in patients with type 2 diabetes who require dialysis in the outpatient setting.
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Boughton CK, Daly A, Thabit H, Hartnell S, Herzig D, Vogt A, Ruan Y, Wilinska ME, Evans ML, Coll AP, Bally L, Hovorka R. Day-to-day variability of insulin requirements in the inpatient setting: Observations during fully closed-loop insulin delivery. Diabetes Obes Metab 2021; 23:1978-1982. [PMID: 33822461 DOI: 10.1111/dom.14396] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/03/2021] [Revised: 03/28/2021] [Accepted: 03/31/2021] [Indexed: 11/28/2022]
Abstract
The aim of this study was to characterize the variability of exogenous insulin requirements during fully closed-loop insulin delivery in hospitalized patients with type 2 diabetes or new-onset hyperglycaemia, and to determine patient-related characteristics associated with higher variability of insulin requirements. We retrospectively analysed data from two fully closed-loop inpatient studies involving adults with type 2 diabetes or new-onset hyperglycaemia requiring insulin therapy. The coefficient of variation quantified day-to-day variability of exogenous insulin requirements during up to 15 days using fully automated closed-loop insulin delivery. Data from 535 days in 67 participants were analysed. The coefficient of variation of day-to-day exogenous insulin requirements was 30% ± 16%, and was higher between nights than between any daytime period (56% ± 29% overnight [11:00 pm to 4:59 am] compared with 41% ± 21% in the morning [5:00 am to 10:59 am], 39% ± 15% in the afternoon [11:00 am to 4:59 pm] and 45% ± 19% during the evening [5:00 pm to 10:59 pm]; all P < 0.01). There is high day-to-day variability of exogenous insulin requirements in inpatients, particularly overnight, and diabetes management approaches should account for this variability.
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Affiliation(s)
- Charlotte K Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Aideen Daly
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Hood Thabit
- Division of Diabetes, Endocrinology and Gastroenterology, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Sara Hartnell
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - David Herzig
- Department of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Andreas Vogt
- Department of Anaesthesiology and Pain Medicine, Inselspital, Bern, University Hospital, University of Bern, Bern, Switzerland
| | - Yue Ruan
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | - Malgorzata E Wilinska
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Mark L Evans
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Anthony P Coll
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine, and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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Daly A, Hovorka R. Technology in the management of type 2 diabetes: Present status and future prospects. Diabetes Obes Metab 2021; 23:1722-1732. [PMID: 33950566 PMCID: PMC7611289 DOI: 10.1111/dom.14418] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 12/18/2022]
Abstract
The growing incidence of type 2 diabetes (T2D) is a significant health concern, representing 90% of diabetes cases worldwide. As the disease progresses, resultant insulin deficiency and hyperglycaemia necessitates insulin therapy in many cases. It has been recognized that a significant number of people who have a clinical requirement for insulin therapy, as well as their healthcare professionals, are reluctant to intensify treatment with insulin due to fear of hypoglycaemia, poor understanding of treatment regimens or lack of engagement, and are therefore at higher risk of developing complications from poor glycaemic control. Over the past decade, the rise of diabetes technologies, including dosing advisors, continuous glucose monitoring systems, insulin pumps and automated insulin delivery systems, has led to great improvements in the therapies available, particularly to those requiring insulin. Although the focus has largely been on delivering these therapies to the type 1 diabetes population, it is becoming increasingly recognized that people with T2D face similar challenges to achieve recommended glycaemic standards and also have the potential to benefit from these advances. In this review, we discuss diabetes technologies that are currently available for people with T2D and the evidence supporting their use, as well as future prospects. We conclude that there is a clinical need to extend the use of these technologies to the T2D population to curb the consequences of suboptimal disease management in this group.
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Affiliation(s)
- Aideen Daly
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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Freckmann G, Buck S, Waldenmaier D, Kulzer B, Schnell O, Gelchsheimer U, Ziegler R, Heinemann L. Insulin Pump Therapy for Patients With Type 2 Diabetes Mellitus: Evidence, Current Barriers, and New Technologies. J Diabetes Sci Technol 2021; 15:901-915. [PMID: 32476471 PMCID: PMC8258526 DOI: 10.1177/1932296820928100] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
An increasing number of patients with type 2 diabetes mellitus (T2DM) use insulin pumps. The first insulin pumps especially designed for patients with T2DM have recently become available. However, national guidelines do not primarily recommend the use of continuous subcutaneous insulin infusion (CSII) for this patient group. The effectiveness of CSII in T2DM has not yet been convincingly demonstrated, despite some positive evidence. An overview and an assessment of various studies to date will be given. T2DM is a heterogeneous disease with a substantial phenotypic variability; therefore, it is difficult to provide general conclusions about the effectiveness of CSII in T2DM therapy. The pump types, characteristics, and associated barriers may play a relevant role for therapy outcome. Most advanced functions like various bolus dosages offered by conventional insulin pumps are not needed for T2DM treatment and complicate the device handling for this subject group. Additionally, new technologies like increased connectivity, advanced software features, and interoperability are currently becoming available representing further barriers. The implementation of this technological progress might be a benefit for pumps for T2DM as well. However, these have not been sufficiently examined either and increased security challenges due to integrated peripheral components should not be neglected in terms of a sound cybersecurity. Pump features and handling for patients with T2DM should be as easy as possible, indicating a need for insulin pumps specially designed for patients with T2DM. However, it has to be investigated if pumps designed for T2DM are more effective than other intensified insulin regimens.
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Affiliation(s)
- Guido Freckmann
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Sina Buck
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
- Sina Buck, MSc, Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Lise-Meitner-Straße 8/2, Ulm 89081, Germany.
| | - Delia Waldenmaier
- Institut für Diabetes-Technologie, Forschungs- und Entwicklungsgesellschaft mbH an der Universität Ulm, Ulm, Germany
| | - Bernhard Kulzer
- Forschungsinstitut Diabetes Akademie Bad Mergentheim, Germany
| | - Oliver Schnell
- Forschergruppe Diabetes e.V., Helmholtz Zentrum, Munich, Germany
| | | | - Ralph Ziegler
- Diabetes Clinic for Children and Adolescents, Münster, Germany
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33
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Yeh T, Yeung M, Mendelsohn Curanaj FA. Managing Patients with Insulin Pumps and Continuous Glucose Monitors in the Hospital: to Wear or Not to Wear. Curr Diab Rep 2021; 21:7. [PMID: 33449214 PMCID: PMC7810103 DOI: 10.1007/s11892-021-01375-7] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE OF REVIEW As the prevalence of diabetes mellitus in the USA continues to rise, so does the popularity of diabetes management devices such as continuous glucose monitors (CGMs) and insulin pumps. The use of this technology has been shown to improve outpatient glycemic outcomes and quality of life and oftentimes may be continued in the hospital setting. Our aim is to review the current guidelines and available evidence on the continuation of insulin pumps and CGMs in the inpatient setting. RECENT FINDINGS Patients with diabetes are at higher risk for hospitalizations and complications due to hyper- or hypoglycemia, metabolic co-morbidities, or as seen recently, more severe illness from infections such as SARS-CoV-2. The maintenance of euglycemia is important to decrease both morbidity and mortality in the hospital setting. There is consensus among experts and medical societies that inpatient use of diabetes technology in carefully selected patients with proper institutional protocols is safe and can improve inpatient glycemic outcomes and reduce hypoglycemia. During the COVID-19 pandemic, CGMs played a vital role in managing hyperglycemia in some hospitalized patients. Insulin pumps and CGMs have the potential to transform glycemic management in hospitalized patients. In order for institutions to safely and effectively incorporate these technologies on their inpatient units, hospital-based providers will need to be able to understand how to manage and utilize these devices in their practice in conjunction with diabetes experts.
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Affiliation(s)
- Tiffany Yeh
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine / New York Presbyterian Hospital, 1305 York Avenue, 4th Floor, New York, NY, 10021, USA.
| | - Michele Yeung
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine / New York Presbyterian Hospital, 1305 York Avenue, 4th Floor, New York, NY, 10021, USA
| | - Felicia A Mendelsohn Curanaj
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, Weill Cornell Medicine / New York Presbyterian Hospital, 1305 York Avenue, 4th Floor, New York, NY, 10021, USA
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Atif Z, Halstrom A, Peragallo-Dittko V, Klek SP. Efficacy of Hybrid Closed-Loop Insulin Delivery System in a Hospital Setting: A Case Series. AACE Clin Case Rep 2021; 7:184-188. [PMID: 34095484 PMCID: PMC8165117 DOI: 10.1016/j.aace.2020.12.013] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 11/17/2020] [Accepted: 12/01/2020] [Indexed: 11/29/2022] Open
Abstract
Objective We report a case series of 4 patients with type 1 diabetes who used hybrid closed-loop insulin pumps (Medtronic MiniMed 670 G) during hospitalization. Methods Clinical data and point-of-care glucose values are presented for each patient. Glucose values are shown graphically while in manual mode as well as in auto mode. Results The first case was a 30-year-old man admitted for pancreatitis. Mean point-of-care blood glucose was 165.7 mg/dL while in auto mode, without hypoglycemia, compared with 221 mg/dL while in manual mode. The second case was a 28-year-old woman who was admitted for a laparoscopic cholecystectomy. Mean point-of-care blood glucose in auto mode was 131.3 mg/dL, without hypoglycemia, compared with 117.6 mg/dL while in manual mode. The third case was a 46-year-old man admitted to the intensive care unit for influenzal pneumonia. Mean point-of-care blood glucose in auto mode was 159.1 mg/dL without hypoglycemia, compared with 218.5 mg/dL while in manual mode. The fourth case was a 60-year-old man who remained in auto mode throughout his hospitalization except for a period when he removed his pump for an endoscopic retrograde cholangiopancreatography and endoscopic ultrasound. His mean point-of-care blood glucose while in auto mode was 156.8 mg/dL without hypoglycemia. Conclusion These case reports support the use of hybrid closed-loop insulin-pump therapy in the inpatient setting to maintain inpatient glycemic targets and avoid hypoglycemia when part of an institution-sanctioned strategy for safe use of insulin pumps that includes point-of-care blood glucose monitoring.
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Affiliation(s)
- Zulekha Atif
- Department of Endocrinology, Overlook Medical Center, Atlantic Health System, Summit, New Jersey
| | - Amanda Halstrom
- Department of Medicine, NYU Long Island School of Medicine, Mineola, New York
| | | | - Stanislaw P Klek
- Division of Endocrinology, NYU Long Island School of Medicine, Mineola, New York
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Banholzer N, Herzig D, Piazza C, Álvarez-Martínez M, Nakas CT, Kosinski C, Feuerriegel S, Hovorka R, Bally L. Effect of nutrition on postprandial glucose control in hospitalized patients with type 2 diabetes receiving fully automated closed-loop insulin therapy. Diabetes Obes Metab 2021; 23:234-239. [PMID: 32885596 DOI: 10.1111/dom.14187] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Revised: 08/06/2020] [Accepted: 08/23/2020] [Indexed: 02/05/2023]
Abstract
Fully automated closed-loop insulin delivery may offer a novel way to manage diabetes in hospital. However, postprandial glycaemic control remains challenging. We aimed to assess the effect of nutritional intake on postprandial glucose control in hospitalized patients with type 2 diabetes receiving fully closed-loop insulin therapy. The effects of different meal types and macronutrient composition on sensor glucose time-in-target (TIT, 3.9-10.0 mmol/L) and mean sensor glucose were assessed with hierarchical linear models using a Bayesian estimation approach. TIT was lower and the mean sensor glucose slightly higher, after breakfast compared with lunch and dinner, whereas the insulin dose was higher. Across meals, when carbohydrates were replaced by fat, or to a lesser extent by protein, postprandial glucose control improved. For breakfast, a 3.9% improvement in TIT was observed when 10% of the energy from carbohydrates was replaced by fat. Improvements were slightly lower during lunch and dinner (3.2% and 3.4%) or when carbohydrates were replaced by protein (2.2 and 2.7%, respectively). We suggest that reducing carbohydrate at the expense of fat or protein, could further improve glucose control during fully closed-loop insulin therapy in hospital.
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Affiliation(s)
| | - David Herzig
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Camillo Piazza
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Mario Álvarez-Martínez
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Institute of Biological Chemistry, Biophysics and Bioengineering, Heriot-Watt University, Edinburgh, UK
| | - Christos T Nakas
- Laboratory of Biometry, School of Agriculture, University of Thessaly, Nea Ionia, Greece
- University Institute of Clinical Chemistry, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Christophe Kosinski
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | | | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - Lia Bally
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Tubiana-Rufi N, Schaepelynck P, Franc S, Chaillous L, Joubert M, Renard E, Reznik Y, Abettan C, Bismuth E, Beltrand J, Bonnemaison E, Borot S, Charpentier G, Delemer B, Desserprix A, Durain D, Farret A, Filhol N, Guerci B, Guilhem I, Guillot C, Jeandidier N, Lablanche S, Leroy R, Melki V, Munch M, Penfornis A, Picard S, Place J, Riveline JP, Serusclat P, Sola-Gazagnes A, Thivolet C, Hanaire H, Benhamou PY. Practical implementation of automated closed-loop insulin delivery: A French position statement. DIABETES & METABOLISM 2020; 47:101206. [PMID: 33152550 DOI: 10.1016/j.diabet.2020.10.004] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 10/18/2020] [Indexed: 01/09/2023]
Abstract
Automated closed-loop (CL) insulin therapy has come of age. This major technological advance is expected to significantly improve the quality of care for adults, adolescents and children with type 1 diabetes. To improve access to this innovation for both patients and healthcare professionals (HCPs), and to promote adherence to its requirements in terms of safety, regulations, ethics and practice, the French Diabetes Society (SFD) brought together a French Working Group of experts to discuss the current practical consensus. The result is the present statement describing the indications for CL therapy with emphasis on the idea that treatment expectations must be clearly defined in advance. Specifications for expert care centres in charge of initiating the treatment were also proposed. Great importance was also attached to the crucial place of high-quality training for patients and healthcare professionals. Long-term follow-up should collect not only metabolic and clinical results, but also indicators related to psychosocial and human factors. Overall, this national consensus statement aims to promote the introduction of marketed CL devices into standard clinical practice.
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Affiliation(s)
- N Tubiana-Rufi
- Endocrinologie et Diabétologie Pédiatrique, Hôpital Robert Debré, APHP Nord, Université de Paris et Aide aux Jeunes Diabétiques AJD, Paris, et SFEDP, France
| | - P Schaepelynck
- Nutrition-Endocrinologie-Maladies Métaboliques, pôle ENDO, Hôpital de la Conception, APHM, Marseille, France
| | - S Franc
- Diabétologie, Centre Hospitalier Sud Francilien, Corbeil-Essonnes, CERITD, Bioparc Genopole Evry-Corbeil, LBEPS, Université Evry, IRBA, Université Paris Saclay, Evry, France
| | - L Chaillous
- Endocrinologie Diabétologie Nutrition, Institut du Thorax, CHU, Nantes, France
| | - M Joubert
- Université de Caen et Endocrinologie Diabétologie, CHU Côte de Nacre, Caen, France
| | - E Renard
- Endocrinologie, Diabète, Nutrition et CIC INSERM 1411, CHU, Montpellier, Institut de Génomique Fonctionnelle, CNRS, INSERM, Université de Montpellier, France
| | - Y Reznik
- Université de Caen et Endocrinologie Diabétologie, CHU Côte de Nacre, Caen, France
| | - C Abettan
- Endocrinologie Diabétologie Nutrition, Institut du Thorax, CHU, Nantes, France
| | - E Bismuth
- Endocrinologie et Diabétologie Pédiatrique, Hôpital Robert Debré, APHP Nord, Université de Paris et Aide aux Jeunes Diabétiques AJD, Paris, et SFEDP, France
| | - J Beltrand
- APHP Centre, Université de Paris, Hôpital Necker Enfants Malades, Paris et Aide aux Jeunes Diabétiques AJD, Paris, et SFEDP, France
| | - E Bonnemaison
- Unité de Spécialités Pédiatriques, Hôpital Clocheville, CHRU de Tours, et SFEDP, France
| | - S Borot
- Université Franche-Comté et Endocrinologie, Nutrition et Diabétologie, CHU, Besançon, France
| | | | - B Delemer
- Endocrinologie Diabétologie, CHU, Reims, et Présidente du CNP d'Endocrinologie Diabétologie et Maladies Métaboliques, France
| | - A Desserprix
- IDE I-ETP, Hotel Dieu Le Creusot (71), Groupe SOS Santé et Vice-présidente de la SFD-Paramédical, France
| | - D Durain
- Cadre de Santé Endocrinologie et Diabétologie et ETP, CHRU, Nancy et SFD-Paramédical, France
| | - A Farret
- Endocrinologie, Diabète, Nutrition, CHU, Montpellier, Institut de Génomique Fonctionnelle, CNRS, INSERM, Université de Montpellier, France
| | - N Filhol
- Endocrinologie et Diabétologie, Hôpital de la Conception, APHM, Marseille, France
| | - B Guerci
- Université de Lorraine et Endocrinologie Diabétologie Maladies Métaboliques et Nutrition, CHU, Nancy, France
| | - I Guilhem
- Endocrinologie-Diabétologie-Nutrition, CHU, Rennes, France
| | - C Guillot
- Sociologue responsable du Diabète LAB, FFD, Paris, France
| | - N Jeandidier
- Université de Strasbourg et Endocrinologie Diabétologie Nutrition, Hôpitaux Universitaires de Strasbourg, France
| | - S Lablanche
- Université Grenoble Alpes, INSERM U1055, LBFA, Endocrinologie, CHU Grenoble Alpes, France
| | - R Leroy
- Cabinet libéral d'endocrinologie diabétologie, Lille, France
| | - V Melki
- Diabétologie, Maladies Métaboliques et Nutrition, CHU Rangueil, Toulouse, France
| | - M Munch
- Service d'Endocrinologie, Diabète et Maladies Métaboliques, CHU Strasbourg, France
| | - A Penfornis
- Université Paris-Saclay et Endocrinologie, Diabétologie et Maladies Métaboliques, CHSF Corbeil-Essonnes, France
| | - S Picard
- Cabinet d'Endocrino-Diabétologie, Point Médical, Dijon et FENAREDIAM, France
| | - J Place
- Ingénieur d'Études, Institut de Génomique Fonctionnelle, CNRS, INSERM, Université de Montpellier, France
| | - J P Riveline
- Centre Universitaire du Diabète, Hôpital Lariboisière, APHP, Paris, France
| | - P Serusclat
- Groupe Hospitalier Mutualiste Les Portes du Sud, Vénissieux, France
| | - A Sola-Gazagnes
- Endocrinologie Diabétologie, Hôpital Cochin, APHP, Paris, France
| | - C Thivolet
- Centre du Diabète DIAB-eCARE, Hospices Civils de Lyon et Président de la SFD, France
| | - H Hanaire
- Université de Toulouse et Diabétologie, Maladies Métaboliques et Nutrition, CHU Rangueil, Toulouse, France
| | - P Y Benhamou
- Université Grenoble Alpes, INSERM U1055, LBFA, Endocrinologie, CHU Grenoble Alpes, Président du groupe de travail Télémédecine et Technologies Innovantes de la SFD, France.
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Galindo RJ, Umpierrez GE, Rushakoff RJ, Basu A, Lohnes S, Nichols JH, Spanakis EK, Espinoza J, Palermo NE, Awadjie DG, Bak L, Buckingham B, Cook CB, Freckmann G, Heinemann L, Hovorka R, Mathioudakis N, Newman T, O’Neal DN, Rickert M, Sacks DB, Seley JJ, Wallia A, Shang T, Zhang JY, Han J, Klonoff DC. Continuous Glucose Monitors and Automated Insulin Dosing Systems in the Hospital Consensus Guideline. J Diabetes Sci Technol 2020; 14:1035-1064. [PMID: 32985262 PMCID: PMC7645140 DOI: 10.1177/1932296820954163] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
This article is the work product of the Continuous Glucose Monitor and Automated Insulin Dosing Systems in the Hospital Consensus Guideline Panel, which was organized by Diabetes Technology Society and met virtually on April 23, 2020. The guideline panel consisted of 24 international experts in the use of continuous glucose monitors (CGMs) and automated insulin dosing (AID) systems representing adult endocrinology, pediatric endocrinology, obstetrics and gynecology, advanced practice nursing, diabetes care and education, clinical chemistry, bioengineering, and product liability law. The panelists reviewed the medical literature pertaining to five topics: (1) continuation of home CGMs after hospitalization, (2) initiation of CGMs in the hospital, (3) continuation of AID systems in the hospital, (4) logistics and hands-on care of hospitalized patients using CGMs and AID systems, and (5) data management of CGMs and AID systems in the hospital. The panelists then developed three types of recommendations for each topic, including clinical practice (to use the technology optimally), research (to improve the safety and effectiveness of the technology), and hospital policies (to build an environment for facilitating use of these devices) for each of the five topics. The panelists voted on 78 proposed recommendations. Based on the panel vote, 77 recommendations were classified as either strong or mild. One recommendation failed to reach consensus. Additional research is needed on CGMs and AID systems in the hospital setting regarding device accuracy, practices for deployment, data management, and achievable outcomes. This guideline is intended to support these technologies for the management of hospitalized patients with diabetes.
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Affiliation(s)
| | | | | | - Ananda Basu
- University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Suzanne Lohnes
- University of California San Diego Medical Center, La Jolla, CA, USA
| | | | - Elias K. Spanakis
- University of Maryland School of Medicine, Baltimore, MD, USA
- Division of Endocrinology, Baltimore Veterans Affairs Medical Center, MD, USA
| | | | - Nadine E. Palermo
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | | | | | | | | | | | | | | | - Tonya Newman
- Neal, Gerber and Eisenberg LLP, Chicago, IL, USA
| | - David N. O’Neal
- University of Melbourne Department of Medicine, St. Vincent’s Hospital, Fitzroy, Victoria, Australia
| | | | | | | | - Amisha Wallia
- Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Trisha Shang
- Diabetes Technology Society, Burlingame, CA, USA
| | | | - Julia Han
- Diabetes Technology Society, Burlingame, CA, USA
| | - David C. Klonoff
- Mills-Peninsula Medical Center, San Mateo, CA, USA
- David C. Klonoff, MD, FACP, FRCP (Edin), Fellow AIMBE, Mills-Peninsula Medical Center, 100 South San Mateo Drive Room 5147, San Mateo, CA 94401, USA.
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38
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Ruan Y, Bellot A, Moysova Z, Tan GD, Lumb A, Davies J, van der Schaar M, Rea R. Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records. Diabetes Care 2020; 43:1504-1511. [PMID: 32350021 DOI: 10.2337/dc19-1743] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2019] [Accepted: 04/04/2020] [Indexed: 02/03/2023]
Abstract
OBJECTIVE We analyzed data from inpatients with diabetes admitted to a large university hospital to predict the risk of hypoglycemia through the use of machine learning algorithms. RESEARCH DESIGN AND METHODS Four years of data were extracted from a hospital electronic health record system. This included laboratory and point-of-care blood glucose (BG) values to identify biochemical and clinically significant hypoglycemic episodes (BG ≤3.9 and ≤2.9 mmol/L, respectively). We used patient demographics, administered medications, vital signs, laboratory results, and procedures performed during the hospital stays to inform the model. Two iterations of the data set included the doses of insulin administered and the past history of inpatient hypoglycemia. Eighteen different prediction models were compared using the area under the receiver operating characteristic curve (AUROC) through a 10-fold cross validation. RESULTS We analyzed data obtained from 17,658 inpatients with diabetes who underwent 32,758 admissions between July 2014 and August 2018. The predictive factors from the logistic regression model included people undergoing procedures, weight, type of diabetes, oxygen saturation level, use of medications (insulin, sulfonylurea, and metformin), and albumin levels. The machine learning model with the best performance was the XGBoost model (AUROC 0.96). This outperformed the logistic regression model, which had an AUROC of 0.75 for the estimation of the risk of clinically significant hypoglycemia. CONCLUSIONS Advanced machine learning models are superior to logistic regression models in predicting the risk of hypoglycemia in inpatients with diabetes. Trials of such models should be conducted in real time to evaluate their utility to reduce inpatient hypoglycemia.
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Affiliation(s)
- Yue Ruan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.,Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K.,Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | - Alexis Bellot
- Department of Mathematics, University of Cambridge, Cambridge, U.K.,Alan Turing Institute, London, U.K
| | - Zuzana Moysova
- Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K
| | - Garry D Tan
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.,Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K
| | - Alistair Lumb
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K.,Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K
| | - Jim Davies
- Big Data Institute, University of Oxford Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, U.K
| | - Mihaela van der Schaar
- Department of Mathematics, University of Cambridge, Cambridge, U.K.,Alan Turing Institute, London, U.K
| | - Rustam Rea
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Oxford University Hospitals National Health Service Foundation Trust, Oxford, U.K. .,Oxford National Institute for Health Research Biomedical Research Centre, Oxford, U.K
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39
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Abstract
The prevalence of diabetes in the inpatient setting is increasing, and suboptimal glucose control in hospital is associated with increased morbidity and mortality. Attaining the recommended glucose levels is challenging with standard insulin therapy. Hypoglycaemia and hyperglycaemia are common and diabetes management in hospital can be a considerable workload burden for health-care professionals. Fully automated insulin delivery (closed-loop) has been shown to be safe, and achieves superior glucose control than standard insulin therapy in the hospital, including in those patients receiving haemodialysis and enteral or parenteral nutrition where glucose control can be particularly challenging. Evidence that the improved glucose control achieved using closed-loop systems can translate into improved clinical outcomes for patients is key to support widespread adoption of this technology. The closed-loop approach has the potential to provide a paradigm shift in the management of inpatient diabetes, particularly in the most challenging inpatient populations, and may reduce staff work burden and the health-care costs associated with inpatient diabetes.
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Affiliation(s)
- C K Boughton
- Clinical Research Fellow, University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ
| | - R Hovorka
- Professor of Metabolic Technology, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge
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40
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Abstract
Hybrid closed-loop (artificial pancreas) systems have recently been introduced into clinical practice for adults with type 1 diabetes. This reflects successful translation from research studies in highly supervised settings to evaluation of the technology in free-living home settings. We review the different closed-loop approaches and the key clinical evidence supporting adoption of hybrid closed-loop systems for adults with type 1 diabetes. We also discuss the growing evidence for automated insulin delivery in pregnant women and in hospitalized patients with hyperglycemia. We consider the psychosocial impact of closed-loop systems and the challenges and potential future advancements for automated insulin delivery.
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Affiliation(s)
- Charlotte K Boughton
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Box 289, Hills Road, Cambridge CB2 0QQ, UK
| | - Roman Hovorka
- University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Addenbrooke's Hospital, Box 289, Hills Road, Cambridge CB2 0QQ, UK.
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41
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Abstract
Technological innovations have fundamentally changed diabetes care. Insulin pump use and continuous glucose monitoring are associated with improved glycemic control along with a better quality of life; automated insulin-dosing advisors facilitate and improve decision making. Glucose-responsive automated insulin delivery enables the highest targets for time in range, lowest rate and duration of hypoglycemia, and favorable quality of life. Clear targets for time in ranges and a standard visualization of the data will help the diabetes technology to be used more efficiently. Decision support systems within and integrated cloud environment will further simplify, unify, and improve modern routine diabetes care.
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Affiliation(s)
- Klemen Dovc
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, University Medical Centre Ljubljana, Bohoriceva 20, Ljubljana SI-1000, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Tadej Battelino
- Department of Paediatric Endocrinology, Diabetes and Metabolic Diseases, UMC - University Children's Hospital, University Medical Centre Ljubljana, Bohoriceva 20, Ljubljana SI-1000, Slovenia; Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.
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42
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Davis GM, Galindo RJ, Migdal AL, Umpierrez GE. Diabetes Technology in the Inpatient Setting for Management of Hyperglycemia. Endocrinol Metab Clin North Am 2020; 49:79-93. [PMID: 31980123 PMCID: PMC7453786 DOI: 10.1016/j.ecl.2019.11.002] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
In past decades, a rapid evolution of diabetes technology led to increased popularity and use of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII) in the ambulatory setting for diabetes management, and recently, the artificial pancreas became available. Efforts to translate this technology to the hospital setting have shown accuracy and reliability of CGM, safety of CSII in appropriate populations, improvement of inpatient glycemic control with computerized glycemic management systems, and feasibility of inpatient CGM-CSII closed-loop systems. Several ongoing studies are focusing on continued translation of this technology to improve glycemic control and outcomes in hospitalized patients.
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Affiliation(s)
- Georgia M Davis
- Department of Medicine, Emory University, 69 Jesse Hill Jr Drive Southeast, Glenn Memorial Building, Suite 200, Atlanta, GA 30303, USA
| | - Rodolfo J Galindo
- Department of Medicine, Emory University, 69 Jesse Hill Jr Drive Southeast, Glenn Memorial Building, Suite 200, Atlanta, GA 30303, USA
| | - Alexandra L Migdal
- Department of Medicine, Emory University, 69 Jesse Hill Jr Drive Southeast, Glenn Memorial Building, Suite 200, Atlanta, GA 30303, USA
| | - Guillermo E Umpierrez
- Department of Medicine, Emory University, 69 Jesse Hill Jr Drive Southeast, Glenn Memorial Building, Suite 200, Atlanta, GA 30303, USA.
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43
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Dubey SK, Alexander A, Pradhyut KS, Agrawal M, Jain R, Saha RN, Singhvi G, Saraf S, Saraf S. Recent Avenues in Novel Patient-Friendly Techniques for the Treatment of Diabetes. Curr Drug Deliv 2020; 17:3-14. [DOI: 10.2174/1567201816666191106102020] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Revised: 09/14/2019] [Accepted: 10/15/2019] [Indexed: 12/26/2022]
Abstract
Background:
Diabetes is one of the most common chronic metabolic disorders which affect
the quality of human life worldwide. As per the WHO report, between 1980 to 2014, the number of
diabetes patients increases from 108 million to 422 million, with a global prevalence rate of 8.5% per
year. Diabetes is the prime reason behind various other diseases like kidney failure, stroke, heart disorders,
glaucoma, etc. It is recognized as the seventh leading cause of death throughout the world. The
available therapies are painful (insulin injections) and inconvenient due to higher dosing frequency.
Thus, to find out a promising and convenient treatment, extensive investigations are carried out globally
by combining novel carrier system (like microparticle, microneedle, nanocarrier, microbeads etc.) and
delivery devices (insulin pump, stimuli-responsive device, inhalation system, bioadhesive patch, insulin
pen etc.) for more precise diagnosis and painless or less invasive treatment of disease.
Objective:
The review article is made with an objective to compile information about various upcoming
and existing modern technologies developed to provide greater patient compliance and reduce the undesirable
side effect of the drug. These devices evade the necessity of daily insulin injection and offer a
rapid onset of action, which sustained for a prolonged duration of time to achieve a better therapeutic
effect.
Conclusion:
Despite numerous advantages, various commercialized approaches, like Afrezza (inhalation
insulin) have been a failure in recent years. Such results call for more potential work to develop a
promising system. The novel approaches range from the delivery of non-insulin blood glucose lowering
agents to insulin-based therapy with minimal invasion are highly desirable.
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Affiliation(s)
- Sunil Kumar Dubey
- Department of Pharmacy, Faculty of Pharmacy, Birla Institute of Technology and Science, Pilani (BITS-PILANI), Pilani Campus, Rajasthan, India
| | - Amit Alexander
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER GUWAHATI), Ministry of Chemicals & Fertilizers, Govt. of India, NH 37, NITS Mirza, Kamrup- 781125, Guwahati (Assam), India
| | - K. Sai Pradhyut
- Department of Pharmacy, Faculty of Pharmacy, Birla Institute of Technology and Science, Pilani (BITS-PILANI), Pilani Campus, Rajasthan, India
| | - Mukta Agrawal
- Department of Pharmaceutics, National Institute of Pharmaceutical Education and Research (NIPER GUWAHATI), Ministry of Chemicals & Fertilizers, Govt. of India, NH 37, NITS Mirza, Kamrup- 781125, Guwahati (Assam), India
| | - Rupesh Jain
- Department of Pharmacy, Faculty of Pharmacy, Birla Institute of Technology and Science, Pilani (BITS-PILANI), Pilani Campus, Rajasthan, India
| | - Ranendra Narayana Saha
- Department of Biotechnology, Faculty of Biotechnology, Birla Institute of Technology and Science, Pilani (BITS-PILANI), Dubai Campus, Dubai, United Arab Emirates
| | - Gautam Singhvi
- Department of Pharmacy, Faculty of Pharmacy, Birla Institute of Technology and Science, Pilani (BITS-PILANI), Pilani Campus, Rajasthan, India
| | - Swarnlata Saraf
- University Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur, Chhattisgarh 492 010, India
| | - Shailendra Saraf
- University Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur, Chhattisgarh 492 010, India
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Millar K, Cummings M, Cranston I. Perioperative diabetes: the challenges and strategies for glycaemic control management. PRACTICAL DIABETES 2019. [DOI: 10.1002/pdi.2247] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Kate Millar
- Portsmouth Hospitals NHS Trust Portsmouth UK
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45
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Boughton CK, Bally L, Hartnell S, Wilinska M, Coll AP, Evans M, Stettler C, Hovorka R. Closed-loop insulin delivery in end-of-life care: a case report. Diabet Med 2019; 36:1711-1714. [PMID: 31002426 PMCID: PMC6900195 DOI: 10.1111/dme.13974] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/16/2019] [Indexed: 11/29/2022]
Abstract
BACKGROUND Glucose management for people with diabetes approaching the end of life can be very challenging. The aim is to balance a minimally invasive approach with avoidance of symptomatic hypo- and hyperglycaemia. CASE REPORT We present a case of a hospitalized individual whose glucose was managed with closed-loop insulin delivery within a randomized controlled trial setting during a period of terminal illness. During the time in which closed-loop insulin delivery was used, glucose control was safe, with no glucose-related harm. The mean ± sd sensor glucose for this individual was 11.3 ± 4.3 mmol/l, percentage of time spent in target glucose range between 6 and 15 mmol/l was 70.5%, time spent in hypoglycaemia was 2.0% and time spent in significant hyperglycaemia >20 mmol/l was 2.6%. CONCLUSION Closed-loop systems can accommodate personalized glucose targets and highly variable insulin requirements. Factory-calibrated continuous glucose sensors and insulin pump therapy are less intrusive than finger-stick glucose measurements and insulin injections, respectively. Closed-loop systems may provide a safer and less burdensome approach to glucose management towards the end of life.
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Affiliation(s)
- C. K. Boughton
- Wellcome Trust‐Medical Research Council Institute of Metabolic ScienceUniversity of CambridgeCambridgeUK
- Cambridge University Hospitals NHS Foundation TrustWolfson Diabetes and Endocrine ClinicCambridgeUK
| | - L. Bally
- Bern University HospitalDepartment of Diabetes EndocrinologyClinical Nutrition and MetabolismBernSwitzerland
| | - S. Hartnell
- Cambridge University Hospitals NHS Foundation TrustWolfson Diabetes and Endocrine ClinicCambridgeUK
| | - M. Wilinska
- Wellcome Trust‐Medical Research Council Institute of Metabolic ScienceUniversity of CambridgeCambridgeUK
| | - A. P. Coll
- Wellcome Trust‐Medical Research Council Institute of Metabolic ScienceUniversity of CambridgeCambridgeUK
- Cambridge University Hospitals NHS Foundation TrustWolfson Diabetes and Endocrine ClinicCambridgeUK
| | - M. Evans
- Wellcome Trust‐Medical Research Council Institute of Metabolic ScienceUniversity of CambridgeCambridgeUK
- Cambridge University Hospitals NHS Foundation TrustWolfson Diabetes and Endocrine ClinicCambridgeUK
| | - C. Stettler
- Bern University HospitalDepartment of Diabetes EndocrinologyClinical Nutrition and MetabolismBernSwitzerland
| | - R. Hovorka
- Wellcome Trust‐Medical Research Council Institute of Metabolic ScienceUniversity of CambridgeCambridgeUK
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46
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van Noorden B, Knopp JL, Chase JG. A subcutaneous insulin pharmacokinetic model for insulin Detemir. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2019; 178:1-9. [PMID: 31416537 DOI: 10.1016/j.cmpb.2019.06.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/01/2019] [Revised: 05/16/2019] [Accepted: 06/07/2019] [Indexed: 06/10/2023]
Abstract
BACKGROUND AND OBJECTIVE Type 2 diabetes (T2D) is rapidly increasing in incidence and has significant social and economic costs. Given the increasing cost of complications, even relatively short delays in the onset of T2D can significantly reduce long-term complications and costs. Equally, recent studies have shown the onset of T2D can be delayed by use of long-acting insulin, despite the risk and concomitant low adherence. Thus, there is a strong potential motivation to develop models of long-acting insulin analogues to enable safe, effective use in model-based dosing systems. In particular, there are no current models of long-acting insulin Detemir and its unique action for model-based control. The objective of this work is to develop a first model of insulin Detemir and its unique action, and validate it against existing data in the literature. METHODS This study develops a detailed compartment model for insulin Detemir. Model specific parameters are identified using data from a range of published clinical studies on the pharmacokinetic of insulin Detemir. Model validity and robustness are assessed by identifying the model for each study and using average identified parameters over several dose sizes and study cohorts. Comparisons to peak concentration, time of peak concentration and overall error versus measured plasma concentrations are used to assess model accuracy and validity. RESULTS Almost all studies and cohorts fit literature data to within one standard deviation of error, even when using averaged identified model parameters. However, there appears to be a noticeable dose dependent dynamic not included in this first model, nor reported in the literature studies. CONCLUSIONS A first model of insulin Detemir including its unique albumin binding kinetics is derived and provisionally validated against clinical pharmacokinetic data. The pharmacokinetic curves are suitable for model-based control and general enough for use. While there are limitations in the studies used for validation that prevent a more complete understanding, the results provide an effective first model and justify the design and implementation of further, more precise human trials.
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Affiliation(s)
- Ben van Noorden
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - Jennifer L Knopp
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand
| | - J Geoffrey Chase
- Department of Mechanical Engineering, Centre for Bio-Engineering, University of Canterbury, Christchurch, New Zealand.
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47
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Boughton CK, Bally L, Hovorka R. Closed-loop management of inpatient hyperglycemia. Aging (Albany NY) 2019; 11:5292-5293. [PMID: 31395790 PMCID: PMC6710063 DOI: 10.18632/aging.102144] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 07/12/2019] [Indexed: 11/25/2022]
Affiliation(s)
- Charlotte K. Boughton
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Wolfson Diabetes and Endocrine Clinic, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Lia Bally
- Department of Diabetes, Endocrinology, Clinical Nutrition & Metabolism, Bern University Hospital, Bern, Switzerland
| | - Roman Hovorka
- Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
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48
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Taleb N, Tagougui S, Rabasa-Lhoret R. Single-Hormone Artificial Pancreas Use in Diabetes: Clinical Efficacy and Remaining Challenges. Diabetes Spectr 2019; 32:205-208. [PMID: 31462874 PMCID: PMC6695251 DOI: 10.2337/ds18-0094] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
IN BRIEF Artificial pancreas systems are rapidly developing and constitute the most promising technology for insulin-requiring diabetes management. Single-hormone systems (SH-AP) that deliver only insulin and have a hybrid design that necessitates patients' interventions around meals and exercise are the first to appear on the market. Trials with SH-AP have demonstrated improvement in time spent with blood glucose levels within target ranges, with a concomitant decrease in hypoglycemia. Longer and larger trials involving different patient populations are ongoing to further advance this important technology.
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Affiliation(s)
- Nadine Taleb
- Clinical Research Institute, Montreal, Quebec, Canada
- Department of Biomedical Sciences, Université de Montréal, Montreal, Quebec, Canada
| | - Sémah Tagougui
- Clinical Research Institute, Montreal, Quebec, Canada
- Department of Nutrition, Université de Montréal, Montreal, Quebec, Canada
| | - Rémi Rabasa-Lhoret
- Clinical Research Institute, Montreal, Quebec, Canada
- Department of Nutrition, Université de Montréal, Montreal, Quebec, Canada
- Montreal Diabetes Research Center & Endocrinology Division Montreal, Quebec, Canada
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49
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Abstract
Improvements in glycemic control using continuous glucose monitoring (CGM) systems have been demonstrated in the outpatient setting. Among hospitalized patients the use of CGM is largely investigational, particularly in the non-ICU setting. Although there is no commercially available closed-loop system, it has recently been evaluated in the non-critical care setting. Both CGMs and closed-loop systems may lead to improved glycemic control, decreased length of stay, reduced risk of adverse events related to severe hypoglycemia or hyperglycemia. Limitations of inpatient use of CGM and closed-loop systems include lack of FDA approvals, inexperience with this technology, and costs related to supplies. Significant investment may be necessary for hospital staff training and for development of infrastructure to support inpatient use. Additional limitations for CGM systems includes potential inaccuracy of interstitial glucose measurements due to medication interferences, sensor lag, or sensor drift. Limitations for closed-loop systems also includes need for routine monitoring to detect infusion site issues as well as monitoring to ensure adequate insulin supply in reservoir to avoid abrupt cessation of insulin infusion leading to severe hyperglycemia. Hospital staff must be familiar with trouble-shooting and conversion to alternative mode of insulin delivery in the event of insulin pump malfunction. Given these complexities, implementation of closed-loop systems may require involvement of an endocrinology team, limiting widespread adoption. This article reviews current state of CGM and closed-loop system use in the non-ICU setting, available literature, advantages and limitations, as well as suggestions for future CGM design, specifically for the inpatient setting.
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Affiliation(s)
- Meng Wang
- Division of Hospital Medicine, Baltimore
Veterans Affairs Medical Center, Baltimore, MD, USA
| | - Lakshmi G. Singh
- Division of Diabetes and Endocrinology,
Baltimore Veterans Affairs Medical Center, Baltimore, MD, USA
| | - Elias K. Spanakis
- Division of Diabetes and Endocrinology,
Baltimore Veterans Affairs Medical Center, Baltimore, MD, USA
- Division of Endocrinology, Diabetes and
Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Elias K. Spanakis, MD, Division of Diabetes
and Endocrinology, Baltimore Veterans Affairs Medical Center and Division of
Endocrinology, Diabetes and Nutrition, University of Maryland School of
Medicine, 10 N Greene St, 5D134, Baltimore, MD 21201, USA.
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50
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Kovatchev B. A Century of Diabetes Technology: Signals, Models, and Artificial Pancreas Control. Trends Endocrinol Metab 2019; 30:432-444. [PMID: 31151733 DOI: 10.1016/j.tem.2019.04.008] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2019] [Revised: 04/14/2019] [Accepted: 04/25/2019] [Indexed: 12/24/2022]
Abstract
Arguably, diabetes mellitus is one of the best-quantified human conditions: elaborate in silico models describe the action of the human metabolic system; real-time signals such as continuous glucose monitoring are readily available; insulin delivery is being automated; and control algorithms are capable of optimizing blood glucose fluctuation in patients' natural environments. The transition of the artificial pancreas (AP) to everyday clinical use is happening now, and is contingent upon seamless concerted work of devices encompassing the patient in a digital treatment ecosystem. This review recounts briefly the story of diabetes technology, which began a century ago with the discovery of insulin, progressed through glucose monitoring and subcutaneous insulin delivery, and is now rapidly advancing towards fully automated clinically viable AP systems.
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Affiliation(s)
- Boris Kovatchev
- University of Virginia School of Medicine, UVA Center for Diabetes Technology, Ivy Translational Research Building, 560 Ray C. Hunt Drive, Charlottesville, VA 22903-2981, USA.
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