Diabetes Technology & TherapeuticsVol. 26, No. S1 Original ArticlesFree AccessContinuous and Intermittent Glucose Monitoring in 2023Klemen Dovc, Bruce W. Bode, and Tadej BattelinoKlemen DovcUniversity Medical Center Ljubljana, Ljubljana, Slovenia.Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.Search for more papers by this author, Bruce W. BodeAtlanta Diabetes Associates and Emory University School of Medicine, Atlanta, GA, USA.Search for more papers by this author, and Tadej BattelinoUniversity Medical Center Ljubljana, Ljubljana, Slovenia.Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia.Search for more papers by this authorPublished Online:1 Mar 2024https://doi.org/10.1089/dia.2024.2502AboutSectionsPDF/EPUB Permissions & CitationsPermissionsDownload CitationsTrack CitationsAdd to favorites Back To Publication ShareShare onFacebookXLinked InRedditEmail IntroductionIn the last few years, continuous glucose monitoring (CGM) has established its pivotal role in individuals with diabetes treated with insulin. Recently, studies have evaluated a broadening role of CGM beyond insulin dosing titration guidance: CGM has been considered as a diagnostic tool for staging of (pre)type 1 diabetes (T1D), for therapy modification guidance for non-insulin-treated individuals with type 2 diabetes (T2D), or as an outcome measure for clinical trials.In the present article, we highlight key publications that provide further evidence for routine CGM use; novel data from large, well-established registries; and data from a broader spectrum of diabetes care, including non-insulin-treated T2D, staging of (pre)T1D, and within clinical trials evaluating the effects of therapeutic interventions; and possibly uncover novel aspects of diabetes care where the use of CGM could further facilitate and advance the excellence of our routine clinical care.Key Articles ReviewedContinuous Glucose Monitoring versus Blood Glucose Monitoring for Risk of Severe Hypoglycaemia and Diabetic Ketoacidosis in Children, Adolescents, and Young Adults with Type 1 Diabetes: A Population-based StudyKarges B, Tittel SR, Bey A, Freiberg C, Klinkert C, Kordonouri O, Thiele-Schmitz S, Schröder C, Steigleder-Schweiger C, and Holl RWLancet Diabetes Endocrinol2023; 11:314–323CGM Metrics Identify Dysglycemic States in Participants from the TrialNet Pathway to Prevention StudyWilson DM, Pietropaolo SL, Acevedo-Calado M, Huang S, Anyaiwe D, Scheinker D, Steck AK, Vasudevan MM, McKay SV, Sherr JL, Herold KC, Dunne JL, Greenbaum CJ, Lord SM, Haller MJ, Schatz DA, Atkinson MA, Nelson PW, Pietropaolo M and the Type 1 Diabetes TrialNet Study GroupDiabetes Care2023; 46:526–534Intermittently Scanned Continuous Glucose Monitoring for Type 1 DiabetesLeelarathna L, Evans ML, Neupane S, Rayman G, Lumley S, Cranston I, Narendran P, Barnard-Kelly K, Sutton CJ, Elliott RA, Taxiarchi VP, Gkountouras G, Burns M, Mubita W, Kanumilli N, Camm M, Thabit H, Wilmot EG, for the FLASH-UK Trial Study GroupN Engl J Med2022; 387:1477–1487Multicenter Randomized Trial of Intermittently Scanned Continuous Glucose Monitoring versus Self-monitoring of Blood Glucose in Individuals with Type 2 Diabetes and Recent-onset Acute Myocardial Infarction: Results of the LIBERATES TrialAjjan RA, Heller SR, Everett CC, Vargas-Palacios A, Higham R, Sharples L, Gorog DA, Rogers A, Reynolds C, Fernandez C, Rodrigues P, Sathyapalan T, Storey RF, Stocken DDDiabetes Care2023; 46:441–449Association of Achieving Time in Range Clinical Targets with Treatment Modality among Youths with Type 1 DiabetesDovc 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 TJAMA Netw Open2023; 6:e230077Initiation of Continuous Glucose Monitoring Is Linked to Improved Glycemic Control and Fewer Clinical Events in Type 1 and Type 2 Diabetes in the Veterans Health AdministrationReaven PD, Newell M, Rivas S, Zhou X, Norman GJ, Zhou JJDiabetes Care2023; 46:854–863Real-world Study of Flash Glucose Monitoring among Adults with Type 2 Diabetes within the Swedish National Diabetes RegisterEeg-Olofsson K, Svensson AM, Franzén S, Ahmed Ismail H, Törnblom M, Levrat-Guillen FDiab Vasc Dis Res 2023; 20: 14791641211067418Increased Derived Time in Range Is Associated with Reduced Risk of Major Adverse Cardiovascular Events, Severe Hypoglycemia, and Microvascular Events in Type 2 Diabetes: A Post Hoc Analysis of DEVOTEBergenstal RM, Hachmann-Nielsen E, Kvist K, Peters AL, Tarp JM, Buse JBDiabetes Technol Ther2023; 25:378–383Continuous Glucose Monitoring-based Time-in-Range Using Insulin Glargine 300 Units/mL versus Insulin Degludec 100 Units/mL in Type 1 Diabetes: The Head-to-Head Randomized Controlled InRange TrialBattelino T, Danne T, Edelman SV, Choudhary P, Renard E, Westerbacka J, Mukherjee B, Pilorget V, Coudert M, Bergenstal RMDiabetes Obes Metab 2023; 25:545–555Effect of CGM Access Expansion on Uptake among Patients on Medicaid with DiabetesNi K, Tampe CA, Sol K, Richardson DB, Pereira RIDiabetes Care2023; 46:391–398Association between Diabetes Technology Use and Glycemic Outcomes in Adults with Type 1 Diabetes over a DecadeKarakus KE, Akturk HK, Alonso GT, Snell-Bergeon JK, Shah VNDiabetes Care2023; 46:1646–1651Impact of Flash Glucose Monitoring in People with Type 2 Diabetes Inadequately Controlled with Non-insulin Antihyperglycaemic Therapy (IMMEDIATE): A Randomized Controlled TrialAronson R, Brown RE, Chu L, Bajaj HS, Khandwala H, Abitbol A, Malakieh N, Goldenberg RDiabetes Obes Metab2023; 25:1024–1031Examining the Acute Glycemic Effects of Different Types of Structured Exercise Sessions in Type 1 Diabetes in a Real-World Setting: The Type 1 Diabetes and Exercise Initiative (T1DEXI)Riddell MC, Li Z, Gal RL, Calhoun P, Jacobs PG, Clements MA, Martin CK, Doyle Iii FJ, Patton SR, Castle JR, Gillingham MB, Beck RW, Rickels MR, for the T1DEXI Study GroupDiabetes Care2023; 46:704–713Disparities in Hemoglobin A1c Levels in the First Year after Diagnosis among Youths with Type 1 Diabetes Offered Continuous Glucose MonitoringAddala A, Ding V, Zaharieva DP, Bishop FK, Adams AS, King AC, Johari R, Scheinker D, Hood KK, Desai M, Maahs DM, Prahalad P, for the Teamwork, Targets, Technology, and Tight Control (4T) Study GroupJAMA Netw Open2023; 6:e238881CGMap: Characterizing Continuous Glucose Monitor Data in Thousands of Non-diabetic IndividualsKeshet A, Shilo S, Godneva A, Talmor-Barkan Y, Aviv Y, Segal E, Rossman HCell Metab2023; 35:758–769.e3Continuous Glucose Monitoring versus Blood Glucose Monitoring for Risk of Severe Hypoglycaemia and Diabetic Ketoacidosis in Children, Adolescents, and Young Adults with Type 1 Diabetes: A Population-Based StudyKarges B1, Tittel SR2, 3Bey A4, Freiberg C5, Klinkert C6, Kordonouri O7, Thiele-Schmitz S8, Schröder C9, Steigleder-Schweiger C10, and Holl RW231Division of Endocrinology and Diabetes, Medical Faculty, RWTH Aachen University, Aachen, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 2Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 3German Center for Diabetes Research, Neuherberg, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 4Department of Pediatrics, St Marien Hospital Düren, Düren, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 5Department of Pediatrics and Adolescent Medicine, University of Göttingen, Göttingen, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 6Practice of Pediatrics and Pediatric Diabetes, Herford, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 7Diabetes Center for Children and Adolescents, Children's Hospital Auf der Bult, Hannover, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 8Department of Pediatric and Adolescent Medicine, St Vincenz Hospital, Paderborn, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 9Department of Pediatrics, Division of Endocrinology and Diabetes, University of Greifswald, Greifswald, Germany; Paracelsus Medical University Salzburg, Salzburg, Austria; 10Department of Pediatrics, Paracelsus Medical University Salzburg, Salzburg, AustriaLancet Diabetes Endocrinol 2023;11:314–323This study is also discussed in DIA-2024-2508, page S-117.Blood glucose monitoring or sensor-based continuous glucose monitoring (CGM) is mandatory to optimize insulin therapy and inform other management decisions in type 1 diabetes (T1D) to achieve glycemic targets. However, the effect of CGM use on the events of severe hypoglycemia (SH) and diabetic ketoacidosis (DKA) remains unclear. This study determined whether the rates of SH and DKA are lower with use of CGM compared with blood glucose monitoring in young patients with T1D and investigated which CGM metrics are informative for these acute diabetes complications.MethodsA population-based cohort study including patients with T1D younger than 25 years with disease duration of > 1 year who were identified from diabetes centers (n = 511) between January 1, 2014, and June 30, 2021, across Austria, Germany, Luxembourg, and Switzerland participated in the Diabetes Prospective Follow-up initiative. SH and DKA rates during the most recent treatment year were examined in people using CGM and in those using blood glucose monitoring. Adjustments of the statistical models included age, sex, diabetes duration, migration background, mode of insulin therapy (pump or injections), and treatment period. The rates of SH and DKA were evaluated by several CGM metrics, including percentage of time below target glucose range (< 3.9 mmol/L), glycemic variability (measured as the coefficient of variation), and mean sensor glucose.ResultsThe cohort included 32,117 patients (53.1% males) with T1D (median age 16.8 years [IQR, 13.3–18.1]). Of these participants, 10,883 used CGM (median 289 days/year), and 21,234 used blood glucose monitoring. Compared with those using blood glucose monitoring, patients using CGM had lower rates of SH (6.74 [95% CI, 5.90–7.69] per 100 patient-years vs 8.84 [95% CI, 8.09–9.66] per 100 patient-years; incidence rate ratio [IRR] 0.76 [95% CI, 0.64–0.91]; P = 0.0017) and DKA (3.72 [95% CI, 3.32–4.18] per 100 patient-years vs 7.29 [95% CI, 6.83–7.78] per 100 patient-years; IRR, 0.51 [95% CI, 0.44–0.59]; P < 0.0001). The SH rates increased with percentage of time below target glucose range (IRR, 1.69 [95% CI, 1.18–2.43], P = 0.0024, for 4.0%–7.9% vs < 4.0%; and IRR, 2.38 [95% CI, 1.51–3.76], P < 0.0001, for ≥ 8.0% vs < 4.0%) and glycemic variability (coefficient of variation ≥ 36% vs < 36%; IRR, 1.52 [95% CI, 1.06–2.17], P = 0.022). The DKA rates increased with mean sensor glucose (IRR, 1.77 [95% CI, 0.89–3.51], P = 0.13, for 8.3–9.9 mmol/L vs < 8.3 mmol/L; IRR, 3.56 [95% CI, 1.83–6.93], P < 0.0001, for 10.0–11.6 mmol/L vs < 8.3 mmol/L; and IRR, 8.66 [95% CI, 4.48–16.75], P < 0.0001, for ≥ 11.7 mmol/L vs < 8.3 mmol/L).ConclusionsYoung patients with T1D using CGM might have lower risks of SH and DKA than those using blood glucose monitoring. The CGM metrics associated with lower rates of SH and of DKA might serve as additional tools to advance personalized treatment in young patients with T1D.CommentsIn this population-based cohort study from the large international registry covering an estimated proportion of more than 90% of all individuals with diabetes in the represented region, Beate and colleagues reported evidence of lower rates of severe hypoglycemia or hypoglycemic coma with seizures, and lower rates of diabetic ketoacidosis or severe ketoacidosis in individuals with T1D using CGM compared with those using only blood glucose monitoring (1). These results complement the observations from two previous smaller cohorts from the same registry of individuals with T1D demonstrating reduced rates of acute complications after CGM initiation (2,3).Importantly, the individuals using CGM, compared with the blood glucose monitoring users, had nearly half the incidence of the most severe acute complications of T1D—hypoglycemic coma and severe diabetic ketoacidosis. Possibly, CGM might reduce both the occurrence of acute complications and their progression to severe life-threatening forms. This observed benefit might be attributed to the real-time glucose monitoring and alerting capabilities of CGM, which enable timely intervention and the implementation of counteractive measures (4,5).A single episode of diabetic ketoacidosis can be associated with cognitive dysfunction, particularly in children with T1D, which further emphasizes the criticality of all possible preventive measures (6,7). Additionally, with the large number of available CGM profiles, a study has identified a number of CGM metrics (time below target glucose range [≥ 4%] and higher glucose variability [coefficient of variation ≥ 36%]) as risk factors for severe hypoglycemia, consistent with current recommended targets (8). These data also present an excellent opportunity for calculating the immediate cost savings related to the decrease of acute complications and the resultant decrease in emergency department visits and hospitalizations.CGM Metrics Identify Dysglycemic States in Participants from the TrialNet Pathway to Prevention StudyWilson DM1, Pietropaolo SL2, Acevedo-Calado M2, Huang S3, Anyaiwe D4, Scheinker D1, Steck AK5, Vasudevan MM2, McKay SV2,6, Sherr JL7, Herold KC8, Dunne JL9, Greenbaum CJ10, Lord SM10, Haller MJ11, Schatz DA11, Atkinson MA11, Nelson PW4, Pietropaolo M2, and the Type 1 Diabetes TrialNet Study Group1Division of Pediatric Endocrinology, Stanford University School of Medicine, Palo Alto, CA; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 2Division of Endocrinology, Diabetes, and Metabolism, Diabetes Research Center, Department of Medicine, Baylor College of Medicine, Houston, TX; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 3Department of Industrial & Systems Engineering, University of Washington, Seattle, WA; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 4Department of Mathematics & Computer Science, Lawrence Technological University, Southfield, MI; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 5Barbara Davis Center for Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 6Department of Pediatrics, Baylor College of Medicine, Houston, TX; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 7Division of Pediatric Endocrinology, Yale University School of Medicine, New Haven, CT; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 8Departments of Immunobiology and Internal Medicine, Yale University, New Haven, CT; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 9JDRF, New York, NY; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 10Center for Interventional Immunology and Diabetes Program, Benaroya Research Institute, Seattle, WA; University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FL; 11Department of Pediatrics, University of Florida Diabetes Institute, College of Medicine, University of Florida, Gainesville, FLDiabetes Care 2023;46:526–534This study is also discussed in DIA-2024-2508, page S-117.Because continuous glucose monitoring (CGM) parameters may identify individuals at risk for progression to overt type 1 diabetes (T1D), this study examined whether CGM metrics could provide additional insight into the progression to clinical stage 3 T1D.MethodsFrom the TrialNet Pathway to Prevention study, 105 relatives of individuals in T1D probands (median age 16.8 years; 89% non-Hispanic White; 43.8% female) underwent 7-day CGM assessments and oral glucose tolerance tests (OGTTs) at 6-month intervals. The three groups evaluated were individuals with (1) stage 2 T1D (n = 42) with two or more diabetes-related autoantibodies and abnormal OGTT; (2) stage 1 T1D (n = 53) with two or more diabetes-related autoantibodies and normal OGTT; and (3) negative test for all diabetes-related autoantibodies and normal OGTT (n = 10).ResultsAfter the baseline data assessment, multiple CGM metrics were found to be associated with progression to stage 3 T1D: spending ≥ 5% time with glucose levels ≥ 140 mg/dL (P = 0.01), ≥ 8% time with glucose levels ≥ 140 mg/dL (P = 0.02), ≥ 5% time with glucose levels ≥ 160 mg/dL (P = 0.0001), and ≥ 8% time with glucose levels ≥ 160 mg/dL (P = 0.02). The stage 2 participants and those who progressed to stage 3 also exhibited higher mean daytime glucose values; they spent more time with glucose values over 120, 140, and 160 mg/dL, and they had greater variability.ConclusionsCGM could aid in the identification of individuals, including those with a normal OGTT, who are likely to rapidly progress to stage 3 T1D.CommentsThis prospective investigation derived from the TrialNet Pathway to Prevention study, involved 105 first-degree or second-degree relatives of individuals with already diagnosed T1D. Almost one-third (30.5%, n = 29) of the multiple islet autoantibody-positive participants progressed to stage 3 T1D in a median of approximately 1.5 years. The analysis of CGM data worn at baseline revealed that individuals who progressed to clinical T1D spent a significantly greater proportion of their time above 140 mg/dL compared with those who did not progress (8% vs 4.7%). In addition, several other CGM metrics indicative of hyperglycemia (daytime mean glucose, time above 120 or 160 mg/dL) or glycemic variability were associated with progression to stage 3 T1D. Spending more than 5% time above 140 mg/dL emerged as a strong predictor of progression to stage 3 T1D (40% progressed to stage 3 T1D compared with 6.5% of participants with time above 140 mg/dL < 5%).These observations are consistent with findings from the ASK Study, involving autoantibody-positive children identified through general population screening (9) and reviewed in the 2022 ATTD Yearbook (10). It has been previously demonstrated that disruptions of glucose homeostasis precede by several months or even years the progression to clinical stage 3 T1D. This gap provides a crucial window of opportunity for early recognition and management of T1D, which might help avoid diabetic ketoacidosis. Furthermore, this insight could impact decision-making for ongoing and future T1D prevention trials to preserve β-cell insulin secretion (11–15).Overall, these findings suggest that CGM metrics could be useful as indicators of progression to stage 3 T1D, spanning both pediatric and adult populations, and including also individuals with a normal oral glucose tolerance test (OGTT). Moreover, CGM-derived criteria should be broadly accepted classifiers of risk when available and could be superior to the OGTT approach of detecting dysglycemia, especially as its use might be more feasible and less burdensome.Intermittently Scanned Continuous Glucose Monitoring for Type 1 DiabetesLeelarathna L1,2, Evans ML6, Neupane S7, Rayman G8, Lumley S9, Cranston I10, Narendran P11, Barnard-Kelly K12, Sutton CJ3,5, Elliott RA4, Taxiarchi VP3, Gkountouras G4, Burns M5, Mubita W1, Kanumilli N1, Camm M1, Thabit H1,2, Wilmot EG13,14 for the FLASH-UK Trial Study Group1Diabetes, Endocrinology, and Metabolism Centre, Manchester Royal Infirmary, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK; Nottingham, UK; 2Division of Diabetes, Endocrinology, and Gastroenterology, Faculty of Biology, Medicine, and Health, Manchester, UK; Nottingham, UK; 3Centre for Biostatistics, Division of Population Health, Health Service Research and Primary Care, University of Manchester, Manchester, UK; Nottingham, UK; 4Manchester Centre for Health Economics, Division of Population Health, Health Service Research and Primary Care, University of Manchester, Manchester, UK; Nottingham, UK; 5Manchester Clinical Trials Unit, Division of Population Health, Health Service Research and Primary Care, University of Manchester, Manchester, UK; Nottingham, UK; 6Wellcome Trust–Medical Research Council Institute of Metabolic Science, National Institute for Health and Care Research Cambridge Biomedical Research Centre, Cambridge University Hospitals and University of Cambridge, Cambridge, UK; Nottingham, UK; 7Elsie Bertram Diabetes Centre, Norfolk, UK; Norwich University Hospitals NHS Foundation Trust, Norwich, UK; Nottingham, UK; 8Diabetes and Endocrine Centre, Ipswich Hospital, East Suffolk and North Essex NHS Foundation Trust, Ipswich, UK; Nottingham, UK; 9Adam Practice, Upton and Poole, Dorset, UK; Nottingham, UK; 10Academic Department of Diabetes and Endocrinology, Queen Alexandra Hospital, Cosham, Portsmouth, UK; Nottingham, UK; 11Institute of Immunology and Immunotherapy, College of Medical and Dental Sciences, University of Birmingham, and University Hospitals Birmingham NHS Foundation Trust, Birmingham, UK; Nottingham, UK; 12Barnard Health, Barnard Health Research Limited, Portsmouth, UK, Nottingham, UK; 13University Hospitals of Derby and Burton NHS Foundation Trust, Royal Derby Hospital, Derby, UK; Nottingham, UK; 14University of Nottingham, Nottingham, UKN Engl J Med 2022;387:1477–1487This study examined the benefits of intermittently scanned continuous glucose monitors (isCGM) with optional alarms for high and low blood glucose levels in persons with type 1 diabetes (T1D) and high glycated hemoglobin (HbA1c) levels.MethodsThis parallel-group, multicenter, randomized, controlled trial involving participants with T1D and HbA1c levels between 7.5% and 11.0% investigated the efficacy of isCGM as compared with participant monitoring of blood glucose levels via fingerstick testing. The primary outcome was the HbA1c level at 24 weeks, analyzed according to the intention-to-treat principle. Key secondary outcomes included sensor data, participant-reported outcome measures, and safety.ResultsA total of 156 participants were randomly assigned in a 1:1 ratio to using isCGM (intervention group, n = 78) or monitoring their own blood glucose levels with fingerstick testing (usual-care group, n = 78). At baseline, the mean age of the participants was 44 (± 15 SD) years, and the mean duration of diabetes was 21 (± 13 SD) years; 44% of the participants were women. The mean baseline HbA1c levels were 8.7% ± 0.9% in the intervention group and 8.5 ± 0.8% in the usual-care group; at 24 weeks these levels decreased to 7.9% ± 0.8% and 8.3% ± 0.9%, respectively (adjusted mean between-group difference, −0.5 percentage points [95% CI, −0.7 to −0.3], P < 0.001). The time per day that the glucose level was in the target range was 9.0 percentage points (95% CI, 4.7–13.3) higher or 130 minutes (95% CI, 68–192) longer in the intervention group compared with the usual-care group; and the time spent in a hypoglycemic state (blood glucose level, < 70 mg/dL [< 3.9 mmol/L]) was 3.0 percentage points (95% CI, 1.4–4.5) lower or 43 minutes (95% CI, 20–65) shorter in the intervention group. Two participants in the usual-care group had an episode of severe hypoglycemia, and one participant in the intervention group had a skin reaction to the sensor.ConclusionsThe use of isCGM with optional alarms for high and low blood glucose levels resulted in significantly lower HbA1c levels in individuals with T1D compared with monitoring by fingerstick testing.CommentsIn the FLASH-UK trial, Leelarathna and colleagues demonstrated that a second-generation intermittently scanned continuous glucose monitor (isCGM) improved glycemic outcomes in individuals with T1D, particularly among those initially presenting with higher baseline levels of glycated hemoglobin (HbA1c). Although the absolute HbA1c and time in range levels were outside recommended clinical targets (8,16), the use of isCGM resulted in a clinically significant reduction in HbA1c levels of 0.5%. This improvement in HbA1c was paralleled by improvements in time in range (9%), along with notable reductions in both the time spent above range (6%) and below range (3%).It is pertinent to acknowledge that the first-generation isCGM devices focused mainly on hypoglycemia prevention and often did not lead to notable improvements in HbA1c (17–19); the evolution to the second generation brought forth a significant advancement. The addition of personalized optional alarms for both high and low glucose levels made important progress toward insulin therapy intensification, given the alarms can prompt action to treat glucose excursions. A direct comparison between the first- and second-generation isCGM is lacking, but it can be speculated that second-generation isCGM is closer in functionality to real-time CGM. This is supported by the 0.5% improvement in HbA1c observed in this study, which aligns reasonably well with the outcomes of clinical trials evaluating real-time CGM (20–22). To approach HbA1c and time-in-range clinical targets even closer and enable broader availability of glucose-responsive insulin delivery, a third generation of (is)CGM may also be necessary.Multicenter Randomized Trial of Intermittently Scanned Continuous Glucose Monitoring versus Self-monitoring of Blood Glucose in Individuals with Type 2 Diabetes and Recent-onset Acute Myocardial Infarction: Results of the LIBERATES TrialAjjan RA1, Heller SR2, Everett CC3, Vargas-Palacios A4, Higham R2, Sharples L5, Gorog DA6,7, Rogers A8, Reynolds C1, Fernandez C2, Rodrigues P4, Sathyapalan T9, Storey RF10, Stocken DD31Clinical Population and Sciences Department, Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 2Department of Oncology and Metabolism, Medical School, University of Sheffield, Sheffield, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 3Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 4Academic Unit of Health Economics, University of Leeds, Leeds, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 5Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 6School of Life and Medical Science, University of Hertfordshire, Hertfordshire, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 7National Heart and Lung Institute, Imperial College London, London, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 8Patient representative; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 9Academic Diabetes, Endocrinology and Metabolism, Allam Diabetes Centre, Hull York Medical School, University of Hull, Hull, UK; Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UK; 10Department of Infection, Immunity and Cardiovascular Disease, Medical School, University of Sheffield, Sheffield, UKDiabetes Care 2023;46:441–449This study analyzed glycemic and patient-related outcomes in individuals with type 2 diabetes (T2D) and recent myocardial infarction (MI) using modern glucose-monitoring strategies and assessed their cost effectiveness.MethodsLIBERATES was a phase 2, multicenter, two-arm, randomized trial to compare self-monitoring of blood glucose (SMBG) with intermittently scanned continuous glucose monitoring (isCGM), also known as flash CGM, in individuals with T2D and recent MI who had been treated with insulin and/or a sulphonylurea before hospital admission. The primary outcome measure was time in range (TIR) (glucose 3.9–10.0 mmol/L/day) on days 76–90 after randomization. The secondary and exploratory outcomes included time in hypoglycemia, hemoglobin A1c (HbA1c), clinical outcome, quality of life (QOL), and cost effectiveness.ResultsThe study randomly assigned 141 participants (median age 63 years [IQR, 53–70]; 73% men) to treatment with isCGm (n = 69) or SMBG (n = 72). The isCGM group had increased TIR by 17 min/day (95% credible interval, −105 to + 153 min/day), with 59% probability of benefit. Users of isCGM also showed lower hypoglycemic exposure (< 3.9 mmol/L) at days 76–90 (−80 min/day; 95% CI, −118 to −43) and days 16–30 (−28 min/day; 95% CI, −92 to 2). Compared with baseline, HbA1c levels showed similar reductions of 7 mmol/mol at 3 months in both study arms. Combined glycemic emergencies and mortality occurred in 4 isCGM and 7 SMBG study participants. QOL measures marginally favored isCGM, and the intervention proved to be cost effective.ConclusionsCompared with SMBG, isCGM in individuals with T2D and MI marginally increased TIR and significantly reduced hypoglycemic exposure while equally improving HbA1c levels, explaining its cost effectiveness.CommentsEight years ago, a retrospective cohort analysis using the U.K. Clinical Practice Research Datalink of more than 100,000 individuals with newly diagnosed T2D concluded that a 1-year delay in treatment intensification for people with HbA1c above 7.5% was associated with an estimated 67% increased risk of myocardial infarction, a 51% increase in risk of stroke, and a 64% increased risk of heart f

Continuous and Intermittent Glucose Monitoring in 2023.