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Yoo JH, Yang SH, Jin SM, Kim JH. Optimal Coefficient of Variance Threshold to Minimize Hypoglycemia Risk in Individuals with Well-Controlled Type 1 Diabetes Mellitus. Diabetes Metab J 2024; 48:429-439. [PMID: 38476023 PMCID: PMC11140403 DOI: 10.4093/dmj.2023.0083] [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: 03/14/2023] [Accepted: 08/12/2023] [Indexed: 03/14/2024] Open
Abstract
BACKGRUOUND This study investigated the optimal coefficient of variance (%CV) for preventing hypoglycemia based on real-time continuous glucose monitoring (rt-CGM) data in people with type 1 diabetes mellitus (T1DM) already achieving their mean glucose (MG) target. METHODS Data from 172 subjects who underwent rt-CGM for at least 90 days and for whom 439 90-day glycemic profiles were available were analyzed. Receiver operator characteristic analysis was conducted to determine the cut-off value of %CV to achieve time below range (%TBR)<54 mg/dL <1 and =0. RESULTS Overall mean glycosylated hemoglobin was 6.8% and median %TBR<54 mg/dL was 0.2%. MG was significantly higher and %CV significantly lower in profiles achieving %TBR<54 mg/dL <1 compared to %TBR<54 mg/dL ≥1 (all P<0.001). The cut-off value of %CV for achieving %TBR<54 mg/dL <1 was 37.5%, 37.3%, and 31.0%, in the whole population, MG >135 mg/dL, and ≤135 mg/dL, respectively. The cut-off value for %TBR<54 mg/dL=0% was 29.2% in MG ≤135 mg/dL. In profiles with MG ≤135 mg/dL, 94.2% of profiles with a %CV <31 achieved the target of %TBR<54 mg/dL <1, and 97.3% with a %CV <29.2 achieved the target of %TBR<54 mg/ dL=0%. When MG was >135 mg/dL, 99.4% of profiles with a %CV <37.3 achieved %TBR<54 mg/dL <1. CONCLUSION In well-controlled T1DM with MG ≤135 mg/dL, we suggest a %CV <31% to achieve the %TBR<54 mg/dL <1 target. Furthermore, we suggest a %CV <29.2% to achieve the target of %TBR<54 mg/dL =0 for people at high risk of hypoglycemia.
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Affiliation(s)
- Jee Hee Yoo
- Division of Endocrinology and Metabolism, Department of Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea
- Division of Endocrinology and Metabolism, Department of Medicine, Chung-Ang University Gwangmyeong Hospital, Chung-Ang University College of Medicine, Gwangmyeong, Korea
| | - Seung Hee Yang
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Sang-Man Jin
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jae Hyeon Kim
- Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences & Technology, Sungkyunkwan University, Seoul, Korea
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2
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Kennedy EC, Hawkes CP. Approaches to Measuring Beta Cell Reserve and Defining Partial Clinical Remission in Paediatric Type 1 Diabetes. CHILDREN (BASEL, SWITZERLAND) 2024; 11:186. [PMID: 38397298 PMCID: PMC10887271 DOI: 10.3390/children11020186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 01/26/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024]
Abstract
CONTEXT Type 1 diabetes (T1D) results from the autoimmune T-cell mediated destruction of pancreatic beta cells leading to insufficient insulin secretion. At the time of diagnosis of T1D, there is residual beta cell function that declines over the subsequent months to years. Recent interventions have been approved to preserve beta cell function in evolving T1D. OBJECTIVE The aim of this review is to summarise the approaches used to assess residual beta cell function in evolving T1D, and to highlight potential future directions. METHODS Studies including subjects aged 0 to 18 years were included in this review. The following search terms were used; "(type 1 diabetes) and (partial remission)" and "(type 1 diabetes) and (honeymoon)". References of included studies were reviewed to determine if additional relevant studies were eligible. RESULTS There are numerous approaches to quantifying beta cell reserve in evolving T1D. These include c-peptide measurement after a mixed meal or glucagon stimuli, fasting c-peptide, the urinary c-peptide/creatinine ratio, insulin dose-adjusted haemoglobin A1c, and other clinical models to estimate beta cell function. Other biomarkers may have a role, including the proinsulin/c-peptide ratio, cytokines, and microRNA. Studies using thresholds to determine if residual beta cell function is present often differ in values used to define remission. CONCLUSIONS As interventions are approved to preserve beta cell function, it will become increasingly necessary to quantify residual beta cell function in research and clinical contexts. In this report, we have highlighted the strengths and limitations of the current approaches.
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Affiliation(s)
- Elaine C Kennedy
- Department of Paediatrics and Child Health, University College Cork, T12 DC4A Cork, Ireland
- INFANT Research Centre, University College Cork, T12 DC4A Cork, Ireland
| | - Colin P Hawkes
- Department of Paediatrics and Child Health, University College Cork, T12 DC4A Cork, Ireland
- INFANT Research Centre, University College Cork, T12 DC4A Cork, Ireland
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
- Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA
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Prahalad P, Maahs DM. Roadmap to Continuous Glucose Monitoring Adoption and Improved Outcomes in Endocrinology: The 4T (Teamwork, Targets, Technology, and Tight Control) Program. Diabetes Spectr 2023; 36:299-305. [PMID: 37982062 PMCID: PMC10654131 DOI: 10.2337/dsi23-0003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Glucose monitoring is essential for the management of type 1 diabetes and has evolved from urine glucose monitoring in the early 1900s to home blood glucose monitoring in the 1980s to continuous glucose monitoring (CGM) today. Youth with type 1 diabetes struggle to meet A1C goals; however, CGM is associated with improved A1C in these youth and is recommended as a standard of care by diabetes professional organizations. Despite their utility, expanding uptake of CGM systems has been challenging, especially in minoritized communities. The 4T (Teamwork, Targets, Technology, and Tight Control) program was developed using a team-based approach to set consistent glycemic targets and equitably initiate CGM and remote patient monitoring in all youth with new-onset type 1 diabetes. In the pilot 4T study, youth in the 4T cohort had a 0.5% improvement in A1C 12 months after diabetes diagnosis compared with those in the historical cohort. The 4T program can serve as a roadmap for other multidisciplinary pediatric type 1 diabetes clinics to increase CGM adoption and improve glycemic outcomes.
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Affiliation(s)
- Priya Prahalad
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
| | - David M. Maahs
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, CA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA
- Department of Health Research and Policy (Epidemiology), Stanford University, Stanford, CA
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4
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Gavin JR, Abaniel RM, Virdi NS. Therapeutic Inertia and Delays in Insulin Intensification in Type 2 Diabetes: A Literature Review. Diabetes Spectr 2023; 36:379-384. [PMID: 38024219 PMCID: PMC10654128 DOI: 10.2337/ds22-0084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/01/2023]
Abstract
Background Therapeutic inertia leading to delays in insulin initiation or intensification is a major contributor to lack of optimal diabetes care. This report reviews the literature summarizing data on therapeutic inertia and delays in insulin intensification in the management of type 2 diabetes. Methods A literature search was conducted of the Allied & Complementary Medicine, BIOSIS Previews, Embase, EMCare, International Pharmaceutical Abstracts, MEDLINE, and ToxFile databases for clinical studies, observational research, and meta-analyses from 2012 to 2022 using search terms for type 2 diabetes and delay in initiating/intensifying insulin. Twenty-two studies met inclusion criteria. Results Time until insulin initiation among patients on two to three antihyperglycemic agents was at least 5 years, and mean A1C ranged from 8.7 to 9.8%. Early insulin intensification was linked with reduced A1C by 1.4%, reduction of severe hypoglycemic events from 4 to <1 per 100 person-years, and diminution in risk of heart failure (HF) by 18%, myocardial infarction (MI) by 23%, and stroke by 28%. In contrast, delayed insulin intensification was associated with increased risk of HF (64%), MI (67%), and stroke (51%) and a higher incidence of diabetic retinopathy. In the views of both patients and providers, hypoglycemia was identified as a primary driver of therapeutic inertia; 75.5% of physicians reported that they would treat more aggressively if not for concerns about hypoglycemia. Conclusion Long delays before insulin initiation and intensification in clinically eligible patients are largely driven by concerns over hypoglycemia. New diabetes technology that provides continuous glucose monitoring may reduce occurrences of hypoglycemia and help overcome therapeutic inertia associated with insulin initiation and intensification.
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Addala A, Ding V, Zaharieva DP, Bishop FK, Adams AS, King AC, Johari R, Scheinker D, Hood KK, Desai M, Maahs DM, Prahalad P. Disparities in Hemoglobin A1c Levels in the First Year After Diagnosis Among Youths With Type 1 Diabetes Offered Continuous Glucose Monitoring. JAMA Netw Open 2023; 6:e238881. [PMID: 37074715 PMCID: PMC10116368 DOI: 10.1001/jamanetworkopen.2023.8881] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 03/05/2023] [Indexed: 04/20/2023] Open
Abstract
Importance Continuous glucose monitoring (CGM) is associated with improvements in hemoglobin A1c (HbA1c) in youths with type 1 diabetes (T1D); however, youths from minoritized racial and ethnic groups and those with public insurance face greater barriers to CGM access. Early initiation of and access to CGM may reduce disparities in CGM uptake and improve diabetes outcomes. Objective To determine whether HbA1c decreases differed by ethnicity and insurance status among a cohort of youths newly diagnosed with T1D and provided CGM. Design, Setting, and Participants This cohort study used data from the Teamwork, Targets, Technology, and Tight Control (4T) study, a clinical research program that aims to initiate CGM within 1 month of T1D diagnosis. All youths with new-onset T1D diagnosed between July 25, 2018, and June 15, 2020, at Stanford Children's Hospital, a single-site, freestanding children's hospital in California, were approached to enroll in the Pilot-4T study and were followed for 12 months. Data analysis was performed and completed on June 3, 2022. Exposures All eligible participants were offered CGM within 1 month of diabetes diagnosis. Main Outcomes and Measures To assess HbA1c change over the study period, analyses were stratified by ethnicity (Hispanic vs non-Hispanic) or insurance status (public vs private) to compare the Pilot-4T cohort with a historical cohort of 272 youths diagnosed with T1D between June 1, 2014, and December 28, 2016. Results The Pilot-4T cohort comprised 135 youths, with a median age of 9.7 years (IQR, 6.8-12.7 years) at diagnosis. There were 71 boys (52.6%) and 64 girls (47.4%). Based on self-report, participants' race was categorized as Asian or Pacific Islander (19 [14.1%]), White (62 [45.9%]), or other race (39 [28.9%]); race was missing or not reported for 15 participants (11.1%). Participants also self-reported their ethnicity as Hispanic (29 [21.5%]) or non-Hispanic (92 [68.1%]). A total of 104 participants (77.0%) had private insurance and 31 (23.0%) had public insurance. Compared with the historical cohort, similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were observed for Hispanic individuals (estimated difference, -0.26% [95% CI, -1.05% to 0.43%], -0.60% [-1.46% to 0.21%], and -0.15% [-1.48% to 0.80%]) and non-Hispanic individuals (estimated difference, -0.27% [95% CI, -0.62% to 0.10%], -0.50% [-0.81% to -0.11%], and -0.47% [-0.91% to 0.06%]) in the Pilot-4T cohort. Similar reductions in HbA1c at 6, 9, and 12 months postdiagnosis were also observed for publicly insured individuals (estimated difference, -0.52% [95% CI, -1.22% to 0.15%], -0.38% [-1.26% to 0.33%], and -0.57% [-2.08% to 0.74%]) and privately insured individuals (estimated difference, -0.34% [95% CI, -0.67% to 0.03%], -0.57% [-0.85% to -0.26%], and -0.43% [-0.85% to 0.01%]) in the Pilot-4T cohort. Hispanic youths in the Pilot-4T cohort had higher HbA1c at 6, 9, and 12 months postdiagnosis than non-Hispanic youths (estimated difference, 0.28% [95% CI, -0.46% to 0.86%], 0.63% [0.02% to 1.20%], and 1.39% [0.37% to 1.96%]), as did publicly insured youths compared with privately insured youths (estimated difference, 0.39% [95% CI, -0.23% to 0.99%], 0.95% [0.28% to 1.45%], and 1.16% [-0.09% to 2.13%]). Conclusions and Relevance The findings of this cohort study suggest that CGM initiation soon after diagnosis is associated with similar improvements in HbA1c for Hispanic and non-Hispanic youths as well as for publicly and privately insured youths. These results further suggest that equitable access to CGM soon after T1D diagnosis may be a first step to improve HbA1c for all youths but is unlikely to eliminate disparities entirely. Trial Registration ClinicalTrials.gov Identifier: NCT04336969.
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Affiliation(s)
- Ananta Addala
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
| | - Victoria Ding
- Division of Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California
| | - Dessi P. Zaharieva
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
| | - Franziska K. Bishop
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
| | - Alyce S. Adams
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Department of Health Policy, Stanford University School of Medicine, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
| | - Abby C. King
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Stanford Prevention Research Center Division, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Ramesh Johari
- Clinical Excellence Research Center, Stanford University, Stanford, California
| | - David Scheinker
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
- Clinical Excellence Research Center, Stanford University, Stanford, California
- Department of Management Science and Engineering, Stanford University, Stanford, California
| | - Korey K. Hood
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
| | - Manisha Desai
- Division of Biomedical Informatics Research, Department of Medicine, Stanford University, Stanford, California
| | - David M. Maahs
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
| | - Priya Prahalad
- Division of Pediatric Endocrinology, Department of Pediatrics, Stanford University, Stanford, California
- Stanford Diabetes Research Center, Stanford University, Stanford, California
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Dovc K, Lanzinger S, Cardona-Hernandez R, Tauschmann M, Marigliano M, Cherubini V, Preikša R, Schierloh U, Clapin H, AlJaser F, Pelicand J, Shukla R, Biester T. Association of Achieving Time in Range Clinical Targets With Treatment Modality Among Youths With Type 1 Diabetes. JAMA Netw Open 2023; 6:e230077. [PMID: 36808243 PMCID: PMC9941889 DOI: 10.1001/jamanetworkopen.2023.0077] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/22/2023] Open
Abstract
IMPORTANCE Continuous glucose monitoring (CGM) devices have demonstrated efficacy in adults and more recently in youths and older adults with type 1 diabetes. In adults with type 1 diabetes, the use of real-time CGM compared with intermittently scanned CGM was associated with improved glycemic control, but there are limited data available for youths. OBJECTIVE To assess real-world data on achievement of time in range clinical targets associated with different treatment modalities in youths with type 1 diabetes. DESIGN, SETTING, AND PARTICIPANTS This multinational cohort study included children, adolescents, and young adults younger than 21 years (hereinafter referred to collectively as youths) with type 1 diabetes for a duration of at least 6 months who provided CGM data between January 1, 2016, and December 31, 2021. Participants were enrolled from the international Better Control in Pediatric and Adolescent Diabetes: Working to Create Centers of Reference (SWEET) registry. Data from 21 countries were included. Participants were divided into 4 treatment modalities: intermittently scanned CGM with or without insulin pump use and real-time CGM with or without insulin pump use. EXPOSURES Type 1 diabetes and the use of CGM with or without an insulin pump. MAIN OUTCOMES AND MEASURES Proportion of individuals in each treatment modality group achieving recommended CGM clinical targets. RESULTS Among the 5219 participants (2714 [52.0%] male; median age, 14.4 [IQR, 11.2-17.1] years), median duration of diabetes was 5.2 (IQR, 2.7-8.7) years and median hemoglobin A1c level was 7.4% (IQR, 6.8%-8.0%). Treatment modality was associated with the proportion of individuals achieving recommended clinical targets. Adjusted for sex, age, diabetes duration, and body mass index standard deviation score, the proportion achieving the recommended greater than 70% time in range target was highest with real-time CGM plus insulin pump use (36.2% [95% CI, 33.9%-38.4%]), followed by real-time CGM plus injection use (20.9% [95% CI, 18.0%-24.1%]), intermittently scanned CGM plus injection use (12.5% [95% CI, 10.7%-14.4%]), and intermittently scanned CGM plus insulin pump use (11.3% [95% CI, 9.2%-13.8%]) (P < .001). Similar trends were observed for less than 25% time above (real-time CGM plus insulin pump, 32.5% [95% CI, 30.4%-34.7%]; intermittently scanned CGM plus insulin pump, 12.8% [95% CI, 10.6%-15.4%]; P < .001) and less than 4% time below range target (real-time CGM plus insulin pump, 73.1% [95% CI, 71.1%-75.0%]; intermittently scanned CGM plus insulin pump, 47.6% [95% CI, 44.1%-51.1%]; P < .001). Adjusted time in range was highest among real-time CGM plus insulin pump users (64.7% [95% CI, 62.6%-66.7%]). Treatment modality was associated with the proportion of participants experiencing severe hypoglycemia and diabetic ketoacidosis events. CONCLUSIONS AND RELEVANCE In this multinational cohort study of youths with type 1 diabetes, concurrent use of real-time CGM and an insulin pump was associated with increased probability of achieving recommended clinical targets and time in range target as well as lower probability of severe adverse events compared with other treatment modalities.
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Affiliation(s)
- Klemen Dovc
- Department of Pediatric Endocrinology, Diabetes and Metabolic Diseases, University Children’s Hospital, Ljubljana, Slovenia
- Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Stefanie Lanzinger
- Institute of Epidemiology and Medical Biometry, ZIBMT, Ulm University, Ulm, Germany
- German Center for Diabetes Research (DZD), Munich–Neuherberg, Germany
| | | | - Martin Tauschmann
- Department of Pediatrics and Adolescent Medicine, Medical University of Vienna, Vienna, Austria
| | - Marco Marigliano
- Pediatric Diabetes and Metabolic Disorders Unit, Regional Center for Pediatric Diabetes, University City Hospital of Verona, Verona, Italy
- Department of Surgery, Dentistry, Paediatrics and Gynaecology, University of Verona, Verona, Italy
| | - Valentino Cherubini
- Division of Pediatric Diabetology, Department of Women’s and Children’s Health, Salesi Hospital, Ancona, Italy
| | - Romualdas Preikša
- Institute and Clinic of Endocrinology, Lithuanian University of Health Sciences, Kaunas
| | - Ulrike Schierloh
- Department of Pediatric Diabetes and Endocrinology, Centre Hospitalier Luxembourg, Luxembourg, Luxembourg
| | - Helen Clapin
- Department of Diabetes and Endocrinology, Perth Children’s Hospital, Perth, Australia
| | - Fahed AlJaser
- Department of Pediatrics, Amiri Hospital, Ministry of Health, Dasman, Kuwait
| | - Julie Pelicand
- Pediatric and Adolescent Diabetes Program, Department of Pediatrics, San Camilo Hospital, San Felipe, Chile
- Medicine School, Universidad de Valparaiso, San Felipe, Chile
| | - Rishi Shukla
- Department of Diabetes and Endocrinology, Center for Diabetes & Endocrine Diseases, Kanpur, India
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Pollé OG, Delfosse A, Martin M, Louis J, Gies I, den Brinker M, Seret N, Lebrethon MC, Mouraux T, Gatto L, Lysy PA, Lysy PA, Pollé OG, Delfosse A, Gallo P, Barrea T, De Valensart G, Brunelle C, Docquir J, Louis J, Oberweis N, Gies I, Staels W, Vanbesien J, Van den Brande C, den Brinker M, Van Eyde M, Seret N, Chivu O, Lambert S, Lebrethon MC, Parent AS, Sondag C, Beckers D, Mouraux T, Boutsen L. Glycemic Variability Patterns Strongly Correlate With Partial Remission Status in Children With Newly Diagnosed Type 1 Diabetes. Diabetes Care 2022; 45:2360-2368. [PMID: 35994729 PMCID: PMC9862313 DOI: 10.2337/dc21-2543] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 06/18/2022] [Indexed: 02/05/2023]
Abstract
OBJECTIVE To evaluate whether indexes of glycemic variability may overcome residual β-cell secretion estimates in the longitudinal evaluation of partial remission in a cohort of pediatric patients with new-onset type 1 diabetes. RESEARCH DESIGN AND METHODS Values of residual β-cell secretion estimates, clinical parameters (e.g., HbA1c or insulin daily dose), and continuous glucose monitoring (CGM) from 78 pediatric patients with new-onset type 1 diabetes were longitudinally collected during 1 year and cross-sectionally compared. Circadian patterns of CGM metrics were characterized and correlated to remission status using an adjusted mixed-effects model. Patients were clustered based on 46 CGM metrics and clinical parameters and compared using nonparametric ANOVA. RESULTS Study participants had a mean (± SD) age of 10.4 (± 3.6) years at diabetes onset, and 65% underwent partial remission at 3 months. β-Cell residual secretion estimates demonstrated weak-to-moderate correlations with clinical parameters and CGM metrics (r2 = 0.05-0.25; P < 0.05). However, CGM metrics strongly correlated with clinical parameters (r2 >0.52; P < 0.05) and were sufficient to distinguish remitters from nonremitters. Also, CGM metrics from remitters displayed specific early morning circadian patterns characterized by increased glycemic stability across days (within 63-140 mg/dL range) and decreased rate of grade II hypoglycemia (P < 0.0001) compared with nonremitters. Thorough CGM analysis allowed the identification of four novel glucotypes (P < 0.001) that segregate patients into subgroups and mirror the evolution of remission after diabetes onset. CONCLUSIONS In our pediatric cohort, combination of CGM metrics and clinical parameters unraveled key clinical milestones of glucose homeostasis and remission status during the first year of type 1 diabetes.
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Affiliation(s)
- Olivier G Pollé
- Pôle de PEDI, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.,Specialized Pediatrics Service, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Antoine Delfosse
- Pôle de PEDI, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.,Specialized Pediatrics Service, Cliniques Universitaires Saint-Luc, Brussels, Belgium
| | - Manon Martin
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Jacques Louis
- Division of Pediatric Endocrinology, Department of Pediatrics, Grand Hôpital de Charleroi, Charleroi, Belgium
| | - Inge Gies
- Division of Pediatric Endocrinology, Department of Pediatrics, Universitair Ziekenhuis Brussel, Vrije Universiteit Brussel, Brussels, Belgium.,Research Group GRON, Vrije Universiteit Brussel, Brussels, Belgium
| | - Marieke den Brinker
- Laboratory of Experimental Medicine and Pediatrics and member of the Infla-Med Centre of Excellence, University of Antwerp, Faculty of Medicine and Health Sciences, Antwerp, Belgium.,Division of Pediatric Endocrinology, Department of Pediatrics, Antwerp University Hospital, Antwerp, Belgium
| | - Nicole Seret
- Division of Pediatric Endocrinology, Department of Pediatrics, Centre Hospitalier Chrétien MontLégia, Liège, Belgium
| | | | - Thierry Mouraux
- Division of Pediatric Endocrinology, Department of Pediatrics, CHU Namur, Namur, Belgium
| | - Laurent Gatto
- Computational Biology and Bioinformatics Unit, de Duve Institute, UCLouvain, Brussels, Belgium
| | - Philippe A Lysy
- Pôle de PEDI, Institut de Recherche Expérimentale et Clinique, UCLouvain, Brussels, Belgium.,Specialized Pediatrics Service, Cliniques Universitaires Saint-Luc, Brussels, Belgium
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8
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Zaharieva DP, Addala A, Prahalad P, Leverenz B, Arrizon-Ruiz N, Ding VY, Desai M, Karger AB, Maahs DM. An Evaluation of Point-of-Care HbA1c, HbA1c Home Kits, and Glucose Management Indicator: Potential Solutions for Telehealth Glycemic Assessments. DIABETOLOGY 2022; 3:494-501. [PMID: 37163187 PMCID: PMC10166120 DOI: 10.3390/diabetology3030037] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/11/2023]
Abstract
During the COVID-19 pandemic, fewer in-person clinic visits resulted in fewer point-of-care (POC) HbA1c measurements. In this sub-study, we assessed the performance of alternative glycemic measures that can be obtained remotely, such as HbA1c home kits and Glucose Management Indicator (GMI) values from Dexcom Clarity. Home kit HbA1c (n = 99), GMI, (n = 88), and POC HbA1c (n = 32) were collected from youth with T1D (age 9.7 ± 4.6 years). Bland-Altman analyses and Lin's concordance correlation coefficient (ρc) were used to characterize the agreement between paired HbA1c measures. Both the HbA1c home kit and GMI showed a slight positive bias (mean difference 0.18% and 0.34%, respectively) and strong concordance with POC HbA1c (ρc = 0.982 [0.965, 0.991] and 0.823 [0.686, 0.904], respectively). GMI showed a slight positive bias (mean difference 0.28%) and fair concordance (ρc = 0.750 [0.658, 0.820]) to the HbA1c home kit. In conclusion, the strong concordance of GMI and home kits to POC A1c measures suggest their utility in telehealth visits assessments. Although these are not candidates for replacement, these measures can facilitate telehealth visits, particularly in the context of other POC HbA1c measurements from an individual.
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Affiliation(s)
- Dessi P. Zaharieva
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
- Correspondence: ; Tel.: +1-(628)-238-9420; Fax: +1-(650)-475-8375
| | - Ananta Addala
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
| | - Priya Prahalad
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
- Stanford Diabetes Research Center, Stanford, CA 94304, USA
| | - Brianna Leverenz
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
| | - Nora Arrizon-Ruiz
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
| | - Victoria Y. Ding
- Quantitative Sciences Unit, Division of Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA
| | - Manisha Desai
- Quantitative Sciences Unit, Division of Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA
| | - Amy B. Karger
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, MN 55455, USA
| | - David M. Maahs
- Division of Endocrinology, Department of Pediatrics, School of Medicine, Stanford University, Stanford, CA 94304, USA
- Stanford Diabetes Research Center, Stanford, CA 94304, USA
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9
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Advancements and future directions in the teamwork, targets, technology, and tight control-the 4T study: improving clinical outcomes in newly diagnosed pediatric type 1 diabetes. Curr Opin Pediatr 2022; 34:423-429. [PMID: 35836400 PMCID: PMC9298953 DOI: 10.1097/mop.0000000000001140] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
PURPOSE OF REVIEW The benefits of intensive diabetes management have been established by the Diabetes Control and Complications Trial. However, challenges with optimizing glycemic management in youth with type 1 diabetes (T1D) remain across pediatric clinics in the United States. This article will review our Teamwork, Targets, Technology, and Tight Control (4T) study that implements emerging diabetes technology into clinical practice with a team approach to sustain tight glycemic control from the onset of T1D and beyond to optimize clinical outcomes. RECENT FINDINGS During the 4T Pilot study and study 1, our team-based approach to intensive target setting, education, and remote data review has led to significant improvements in hemoglobin A1c throughout the first year of T1D diagnosis in youth, as well as family and provider satisfaction. SUMMARY The next steps include refinement of the current 4T study 1, developing a business case, and broader implementation of the 4T study. In study 2, we are including a more pragmatic cadence of remote data review and disseminating exercise education and activity tracking to both English- and Spanish-speaking families. The overall goal is to create and implement a translatable program that can facilitate better outcomes for pediatric clinics across the USA.
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10
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Scheinker D, Prahalad P, Johari R, Maahs DM, Majzun R. A New Technology-Enabled Care Model for Pediatric Type 1 Diabetes. NEJM CATALYST INNOVATIONS IN CARE DELIVERY 2022; 3:10.1056/CAT.21.0438. [PMID: 36544715 PMCID: PMC9767424 DOI: 10.1056/cat.21.0438] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
In July 2018, pediatric type 1 diabetes (T1D) care at Stanford suffered many of the problems that plague U.S. health care. Patient outcomes lagged behind those of peer European nations, care was delivered primarily on a fixed cadence rather than as needed, continuous glucose monitors (CGMs) were largely unavailable for individuals with public insurance, and providers' primary access to CGM data was through long printouts. Stanford developed a new technology-enabled, telemedicine-based care model for patients with newly diagnosed T1D. They developed and deployed Timely Interventions for Diabetes Excellence (TIDE) to facilitate as-needed patient contact with the partially automated analysis of CGM data and used philanthropic funding to facilitate full access to CGM technology for publicly insured patients, for whom CGM is not readily available in California. A study of the use of CGM for patients with new-onset T1D (pilot Teamwork, Targets, and Technology for Tight Control [4T] study), which incorporated the use of TIDE, was associated with a 0.5%-point reduction in hemoglobin A1c compared with historical controls and an 86% reduction in screen time for providers reviewing patient data. Based on this initial success, Stanford expanded the use of TIDE to a total of 300 patients, including many outside the pilot 4T study, and made TIDE freely available as open-source software. Next steps include expanding the use of TIDE to support the care of approximately 1,000 patients, improving TIDE and the associated workflows to scale their use to more patients, incorporating data from additional sensors, and partnering with other institutions to facilitate their deployment of this care model.
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Affiliation(s)
- David Scheinker
- Associate Professor, Pediatrics, Stanford University, Stanford, California, USA,Executive Director, Lucile Packard Children’s Hospital Stanford, Palo Alto, California, USA,Faculty, Clinical Excellence Research Center, Stanford University, California, USA
| | - Priya Prahalad
- Associate Professor, Pediatrics, Stanford University, Stanford, California, USA
| | - Ramesh Johari
- Professor, Management Science and Engineering, Stanford University, Stanford, California, USA
| | - David M. Maahs
- Professor, Pediatrics, Stanford University, Stanford, California, USA
| | - Rick Majzun
- Chief Operating Officer, Lucile Packard Children’s Hospital Stanford, Palo Alto, California, USA
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11
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Prahalad P, Ding VY, Zaharieva DP, Addala A, Johari R, Scheinker D, Desai M, Hood K, Maahs DM. Teamwork, Targets, Technology, and Tight Control in Newly Diagnosed Type 1 Diabetes: the Pilot 4T Study. J Clin Endocrinol Metab 2022; 107:998-1008. [PMID: 34850024 PMCID: PMC8947228 DOI: 10.1210/clinem/dgab859] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Indexed: 11/19/2022]
Abstract
CONTEXT Youth with type 1 diabetes (T1D) do not meet glycated hemoglobin A1c (HbA1c) targets. OBJECTIVE This work aimed to assess HbA1c outcomes in children with new-onset T1D enrolled in the Teamwork, Targets, Technology and Tight Control (4T) Study. METHODS HbA1c levels were compared between the 4T and historical cohorts. HbA1c differences between cohorts were estimated using locally estimated scatter plot smoothing (LOESS). The change from nadir HbA1c (month 4) to 12 months post diagnosis was estimated by cohort using a piecewise mixed-effects regression model accounting for age at diagnosis, sex, ethnicity, and insurance type. We recruited 135 youth with newly diagnosed T1D at Stanford Children's Health. Starting July 2018, all youth within the first month of T1D diagnosis were offered continuous glucose monitoring (CGM) initiation and remote CGM data review was added in March 2019. The main outcomes measure was HbA1c. RESULTS HbA1c at 6, 9, and 12 months post diagnosis was lower in the 4T cohort than in the historic cohort (-0.54% to -0.52%, and -0.58%, respectively). Within the 4T cohort, HbA1c at 6, 9, and 12 months post diagnosis was lower in those patients with remote monitoring than those without (-0.14%, -0.18% to -0.14%, respectively). Multivariable regression analysis showed that the 4T cohort experienced a significantly lower increase in HbA1c between months 4 and 12 (P < .001). CONCLUSION A technology-enabled, team-based approach to intensified new-onset education involving target setting, CGM initiation, and remote data review statistically significantly decreased HbA1c in youth with T1D 12 months post diagnosis.
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Affiliation(s)
- Priya Prahalad
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California 94304, USA
- Correspondence: Priya Prahalad, MD, PhD, Department of Pediatrics, Division of Pediatric Endocrinology, Center for Academic Medicine, 453 Quarry Rd, Palo Alto, CA 94304, USA.
| | - Victoria Y Ding
- Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, California 94304, USA
| | - Dessi P Zaharieva
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
| | - Ananta Addala
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
| | - Ramesh Johari
- Stanford Diabetes Research Center, Stanford University, Stanford, California 94304, USA
- Department of Management Science and Engineering, Stanford University, Stanford, California 94304, USA
| | - David Scheinker
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California 94304, USA
- Department of Management Science and Engineering, Stanford University, Stanford, California 94304, USA
- Clinical Excellence Research Center, Stanford University, Stanford, California 94304, USA
| | - Manisha Desai
- Department of Medicine, Division of Biomedical Informatics Research, Stanford University, Stanford, California 94304, USA
| | - Korey Hood
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California 94304, USA
| | - David M Maahs
- Department of Pediatrics, Division of Pediatric Endocrinology, Stanford University, Stanford, California 94304, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, California 94304, USA
- Department of Health Research and Policy (Epidemiology) Stanford University, Stanford, California 94304, USA
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12
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Franceschi R, Cauvin V, Stefani L, Berchielli F, Soffiati M, Maines E. Early Initiation of Intermittently Scanned Continuous Glucose Monitoring in a Pediatric Population With Type 1 Diabetes: A Real World Study. Front Endocrinol (Lausanne) 2022; 13:907517. [PMID: 35784525 PMCID: PMC9247237 DOI: 10.3389/fendo.2022.907517] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 05/18/2022] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Use of Continuous Glucose Monitoring (CGM) systems early in the course of diabetes has the potential to help glycemic management and to improve quality of life (QoL). No previous research has examined these outcomes in children-adolescents with type 1 diabetes (T1D) who use intermittently scanned CGM (isCGM) starting within the first month after diagnosis. AIM To evaluate the impact of isCGM early after T1D diagnosis, on metabolic control and QoL, comparing a group who started the use of the device within one month from the onset with another one who started at least one year later. SUBJECTS AND METHODS Patients who used isCGM within 1 month from T1D diagnosis were enrolled in group A; those who didn't have the device during the first year were considered as control group (group B). HbA1c and total daily insulin were evaluated at 3 (T1), 6 (T2) and 12 (T3) months post-baseline (T0, diabetes onset), QoL after 1 year. In group A, isCGM glucose metrics were also recorded. RESULTS 85 patients were enrolled in group A and 67 patients in group B. In group A isCGM was well accepted during follow up: no patient dropped out; percentage of time with active sensor was in mean > 87%; number of scans/day remained stable. QoL was higher in group A than in group B both in children-adolescents (p<0.0001) and in parents (p 0.003). Group A presented lower HbA1c during the first year after diagnosis (p<0.001), and this data correlated with glucose management indicator (GMI), time in range (TIR) and mean glucose. The honeymoon period lasted more in group A than in B (p 0.028). Furthermore, the mean hypoglycemia duration decreased during follow-up (p 0.001) in group A. CONCLUSIONS Early use of isCGM, starting within the first month after diagnosis, improves metabolic control and QoL in pediatric patients with T1D.
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Affiliation(s)
- Roberto Franceschi
- Pediatric Diabetology Unit, Pediatric Department, S. Chiara General Hospital, Trento, Italy
- *Correspondence: Roberto Franceschi,
| | - Vittoria Cauvin
- Pediatric Diabetology Unit, Pediatric Department, S. Chiara General Hospital, Trento, Italy
| | - Lorenza Stefani
- Pediatric Diabetology Unit, Pediatric Department, S. Chiara General Hospital, Trento, Italy
| | | | - Massimo Soffiati
- Pediatric Diabetology Unit, Pediatric Department, S. Chiara General Hospital, Trento, Italy
| | - Evelina Maines
- Pediatric Diabetology Unit, Pediatric Department, S. Chiara General Hospital, Trento, Italy
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13
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Zaharieva DP, Senanayake R, Brown C, Watkins B, Loving G, Prahalad P, Ferstad JO, Guestrin C, Fox EB, Maahs DM, Scheinker D. Adding glycemic and physical activity metrics to a multimodal algorithm-enabled decision-support tool for type 1 diabetes care: Keys to implementation and opportunities. Front Endocrinol (Lausanne) 2022; 13:1096325. [PMID: 36714600 PMCID: PMC9877334 DOI: 10.3389/fendo.2022.1096325] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 12/15/2022] [Indexed: 01/15/2023] Open
Abstract
Algorithm-enabled patient prioritization and remote patient monitoring (RPM) have been used to improve clinical workflows at Stanford and have been associated with improved glucose time-in-range in newly diagnosed youth with type 1 diabetes (T1D). This novel algorithm-enabled care model currently integrates continuous glucose monitoring (CGM) data to prioritize patients for weekly reviews by the clinical diabetes team. The use of additional data may help clinical teams make more informed decisions around T1D management. Regular exercise and physical activity are essential to increasing cardiovascular fitness, increasing insulin sensitivity, and improving overall well-being of youth and adults with T1D. However, exercise can lead to fluctuations in glycemia during and after the activity. Future iterations of the care model will integrate physical activity metrics (e.g., heart rate and step count) and physical activity flags to help identify patients whose needs are not fully captured by CGM data. Our aim is to help healthcare professionals improve patient care with a better integration of CGM and physical activity data. We hypothesize that incorporating exercise data into the current CGM-based care model will produce specific, clinically relevant information such as identifying whether patients are meeting exercise guidelines. This work provides an overview of the essential steps of integrating exercise data into an RPM program and the most promising opportunities for the use of these data.
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Affiliation(s)
- Dessi P. Zaharieva
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA, United States
- *Correspondence: Dessi P. Zaharieva,
| | - Ransalu Senanayake
- Department of Computer Science, Stanford University, Stanford, CA, United States
| | - Conner Brown
- Stanford Children’s Health, Lucile Packard Children’s Hospital, Stanford, CA, United States
| | - Brendan Watkins
- Stanford Children’s Health, Lucile Packard Children’s Hospital, Stanford, CA, United States
| | - Glenn Loving
- Stanford Children’s Health, Lucile Packard Children’s Hospital, Stanford, CA, United States
| | - Priya Prahalad
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA, United States
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, United States
| | - Johannes O. Ferstad
- Department of Management Science and Engineering, Stanford University School of Engineering, Stanford, CA, United States
| | - Carlos Guestrin
- Department of Computer Science, Stanford University, Stanford, CA, United States
| | - Emily B. Fox
- Department of Computer Science, Stanford University, Stanford, CA, United States
- Chan Zuckerberg Biohub, San Francisco, CA, United States
- Department of Statistics, Stanford University, Stanford, CA, United States
| | - David M. Maahs
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA, United States
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, United States
- Department of Health Research and Policy, Stanford University School of Medicine, Stanford, CA, United States
| | - David Scheinker
- Division of Endocrinology, Department of Pediatrics, Stanford University, School of Medicine, Stanford, CA, United States
- Stanford Children’s Health, Lucile Packard Children’s Hospital, Stanford, CA, United States
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, United States
- Department of Management Science and Engineering, Stanford University School of Engineering, Stanford, CA, United States
- Clinical Excellence Research Center, Stanford University School of Medicine, Stanford, CA, United States
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14
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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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