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Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data., Methods: We assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation., Results: The analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals., Conclusion: The GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments.

Objectives: The metabolic abnormalities that lead to diabetes mellitus (DM) after an episode of acute pancreatitis (AP) have not been extensively studied. This article describes the objectives, hypotheses, and methods of mechanistic studies of glucose metabolism that comprise secondary outcomes of the DREAM (Diabetes RElated to Acute pancreatitis and its Mechanisms) Study., Methods: Three months after an index episode of AP, participants without preexisting DM will undergo baseline testing with an oral glucose tolerance test. Participants will be followed longitudinally in three subcohorts with distinct metabolic tests. In the first and largest subcohort, oral glucose tolerance tests will be repeated 12 months after AP and annually to assess changes in β-cell function, insulin secretion, and insulin sensitivity. In the second, mixed meal tolerance tests will be performed at 3 and 12 months, then annually, and following incident DM to assess incretin and pancreatic polypeptide responses. In the third, frequently sampled intravenous glucose tolerance tests will be performed at 3 months and 12 months to assess the first-phase insulin response and more precisely measure β-cell function and insulin sensitivity., Conclusions: The DREAM study will comprehensively assess the metabolic and endocrine changes that precede and lead to the development of DM after AP., Competing Interests: K.M.D. has declared research support from Sanofi, Viacyte, Abbott, and Dexcom; consulting activities with Eli Lilly, Boehringer Ingelheim, Elsevier, and Dexcom; and honoraria from UptoDate, Medscape, Academy for Continued Healthcare Learning, and Cardiometabolic Health Congress. M.D.B. has declared research support from Viacyte and Dexcom and consulting activities with Insulet (advisory board). C.E.-M. has received research support from Lilly, Astellas Pharma, Bristol Myers Squibb, and Nimbus Therapeutics and consulting/advisory fees from Avotres, Inc, DiogenX, Isla Technologies, Provention Bio, Inc, MaiCell Therapeutics, and Dompe. R.E.P. has received grants (directed to his institution) from Hanmi Pharmaceutical Co, Ltd, Janssen, Metavention, Novo Nordisk, Poxel SA, and Sanofi; has received consulting fees (directed to his institution) from AstraZeneca, Corcept Therapeutics Incorporated, Glytec LLC, Hanmi Pharmaceutical Co, Ltd, Janssen, Merck & Co, Inc., Mundipharma, Novo Nordisk, Pfizer, Inc, Sanofi, Scohia Pharma, Inc, and Sun Pharmaceutical Industries; and has received support for attending meetings/travel (directed to his institution or to the travel provider) from AstraZeneca, Glytec LLC, Merck & Co, Inc, Mundipharma, Novo Nordisk, and Pfizer, Inc. E.K.S. has received honoraria from Medscape. C.S. has participated on an advisory board for Vertex Pharmaceuticals. F.G.S.T. has declared research support from Dompé Pharmaceuticals and previous consulting activities with Sanofi, Eli Lilly, and AstraZeneca. The other authors declare no conflict of interest., (Copyright © 2022 Written work prepared by employees of the Federal Government as part of their official duties is, under the U.S. Copyright Act, a “work of the United States Government” for which copyright protection under Title 17 of the United States Code is not available. As such, copyright does not extend to the contributions of employees of the Federal Government.)

Hyperglycemia is a common phenomenon in critically ill patients, even in those without diabetes. Two landmark studies established the benefits of tight glucose control (blood glucose target 80-110 mg/dL) in surgical and medical patients. Since then, literature has consistently demonstrated that both hyperglycemia and hypoglycemia are independently associated with increased morbidity and mortality in a variety of critically ill patients. However, tight glycemic control has subsequently come into question due to risks of hypoglycemia and increased mortality. More recently, strategies targeting euglycemia (blood glucose ≤180 mg/dL) have been associated with improved outcomes, although the risk of hypoglycemia remains. More complex targets (ie, glycemic variability and time within target glucose range) and the impact of individual patient characteristics (ie, diabetic status and prehospital glucose control) have more recently been shown to influence the relationship between glycemic control and outcomes in critically ill patients. Although our understanding has increased, the optimal glycemic target is still unclear and glucose management strategies may require adjustment for individual patient characteristics. As glucose management increases in complexity, we realize that traditional means of using meters and strips and paper insulin titration algorithms are potential limitations to our success. To achieve these complex goals for glycemic control, the use of continuous or near-continuous glucose monitoring combined with computerized insulin titration algorithms may be required. The purpose of this review is to discuss the evidence surrounding the various domains of glycemic control and the emerging data supporting the need for individualized glucose targets in critically ill patients.

Purpose: To determine prevalence, predictors, and outcomes of steroid-induced hyperglycemia in hospitalized patients with hematologic malignancies METHODS: We performed retrospective analysis of patients who were hospitalized on any of the four hematology services or bone marrow transplant service and who received systemic steroids during a 2-month period. Mean glucoses for days 1-4 and maximum glucose were calculated and the total daily steroid dose was converted to equivalent dose of dexamethasone. Hyperglycemia was defined as any glucose >9.917 mmol/l during days 1-4. We examined associations between variables using Spearman's correlations and multivariable linear regression RESULTS: 168 patients were included in the analysis. Mean age was 57.1 ± 14.4 years with 59% males and 90% Caucasians. The prevalence of hyperglycemia was 39%. Eight patients received intravenous insulin. In patients without diabetes, steroid dose equivalent to >12 mg dexamethasone and longer acting steroids caused greater degree of hyperglycemia compared to a dose <12 mg. Maximum glucose was a predictor of hospital length of stay among patients without diabetes (but not those with diabetes), and with acute leukemia or stem cell transplant (but not other hematologic malignancies). There were no significant differences in in mortality or other outcomes between the groups with and without hyperglycemia CONCLUSIONS: Hyperglycemia is common in patients with hematologic malignancies, which require frequent corticosteroids. Higher steroid dose and long-acting steroids caused a greater degree of hyperglycemia. Maximum glucose was a predictor of length of stay but this was only significant for patients without diabetes, those with acute hematologic malignancy or stem cell transplant.

Aims: To evaluate the safety and efficacy of once-weekly dulaglutide 1.5 mg, a long-acting glucagon-like peptide-1 receptor agonist, compared with placebo in patients with type 2 diabetes (T2D) on glimepiride monotherapy., Methods: This phase III, randomized (4 : 1; dulaglutide:placebo), double-blind, placebo-controlled, 24-week study compared the safety and efficacy of once-weekly dulaglutide 1.5 mg with placebo in sulphonylurea-treated (≥half-maximal dose, stable ≥3 months) patients (N = 300) with T2D and inadequate glycaemic control [glycated haemoglobin (HbA1c) ≥7.5 and ≤9.5% (≥58 mmol/mol and ≤80 mmol/mol)]. Analysis was carried out according to intention-to-treat., Results: At baseline, the mean participant age was 58 years; mean HbA1c was 8.4% (68 mmol/mol) and mean weight was 85.5 kg. Dulaglutide 1.5 mg was superior to placebo at 24 weeks for HbA1c reduction from baseline with a between-group HbA1c difference of -1.3% [95% confidence interval (CI) -1.6, -1.0] or -14 mmol/mol (95% CI -17, -11); p < 0.001. A greater proportion of participants in the dulaglutide group reached an HbA1c level of <7.0% (53 mmol/mol) compared with placebo (55.3% vs 18.9%; p < 0.001). Dulaglutide significantly decreased fasting serum glucose from baseline compared with placebo (between-group difference -1.86 mmol/l (95% CI -2.58, -1.14) or -33.54 mg/dl (95% CI -46.55, -20.53); p < 0.001. Weight was decreased significantly from baseline in the dulaglutide group (p < 0.001); the between-group difference was not significant. The most common treatment-emergent adverse events for dulaglutide 1.5 mg were gastrointestinal: nausea (10.5%), diarrhoea (8.4%) and eructation (5.9%). Total hypoglycaemia was higher with dulaglutide 1.5 mg vs placebo (2.37 and 0.07 events/participant/year, respectively; p = 0.025). No severe hypoglycaemia was reported., Conclusions: Once-weekly dulaglutide 1.5 mg had a favourable benefit/risk profile when added to glimepiride monotherapy., (© 2016 The Authors. Diabetes, Obesity and Metabolism published by John Wiley & Sons Ltd.)

Patients with hematologic malignancies are at high risk for hyperglycemia due to factors such as frequent exposure to glucocorticoids, immunosuppressants, total parenteral nutrition, and medical stress. Hyperglycemia in these patients has been associated with poor outcomes including increased risk of infection, organ dysfunction, durability of remission, graft-versus-host disease, and mortality. However, the appropriate glucose targets are not well established, and there are few prospective data assessing whether glucose control improves outcomes. HbA1c should be interpreted with caution in patients with hematologic malignancies, due to inaccuracies imposed by disordered hematopoiesis and frequent transfusions, and short-term perturbations imposed by acute illness or medications. Management of diabetes or glucocorticoid-induced hyperglycemia in the hospital generally requires insulin therapy, which is tailored based upon nutritional needs, baseline glucose control, and concomitant factors such as type and dose of glucocorticoid administration. Close follow-up and adjustment of therapy, ideally with the assistance of patient self-titration algorithms, is required after discharge. Patients are at increased long-term risk for developing diabetes and therefore should undergo regular screening.

Currently patients with diabetes comprise up to 25-30% of the census of adult wards and critical care units in our hospitals. Although evidence suggests that avoidance of hyperglycemia (>180 mg/dL) and hypoglycemia (<70 mg/dL) is beneficial for positive outcomes in the hospitalized patient, much of this evidence remains controversial and at times somewhat contradictory. We have recently formed a consortium for Planning Research in Inpatient Diabetes (PRIDE) with the goal of promoting clinical research in the area of management of hyperglycemia and diabetes in the hospital. In this article, we outline eight aspects of inpatient glucose management in which randomized clinical trials are needed. We refer to four as system-based issues and four as patient-based issues. We urge further progress in the science of inpatient diabetes management. We hope this call to action is supported by the American Diabetes Association, The Endocrine Society, the American Association of Clinical Endocrinologists, the American Heart Association, the European Association for the Study of Diabetes, the International Diabetes Federation, and the Society of Hospital Medicine. Appropriate federal research funding in this area will help ensure high-quality investigations, the results of which will advance the field. Future clinical trials will allow practitioners to develop optimal approaches for the management of hyperglycemia in the hospitalized patient and lessen the economic and human burden of poor glycemic control and its associated complications and comorbidities in the inpatient setting.

Background: The accuracy of continuous glucose monitoring (CGM) in non-critically ill hospitalized patients with heart failure or severe hyperglycemia (SH) is unknown., Methods: Hospitalized patients with congestive heart failure (CHF) exacerbation (receiving IV or subcutaneous insulin) or SH requiring insulin infusion were compared to outpatients referred for retrospective CGM., Results: Forty-three patients with CHF, 15 patients with SH, and 88 outpatients yielded 470, 164, and 2150 meter-sensor pairs, respectively. Admission glucose differed (188 versus 509 mg/dl in CHF and SH, p < .001) but not the first sensor glucose (p = .35). In continuous glucose error grid analysis, 67-78% of pairs during hypoglycemia were in zones A+B (p = .63), compared with 98-100% in euglycemia (p < .001) and 98%, 92%, and 99% (p = .001) during hyperglycemia for the CHF, SH, and outpatient groups, respectively. Mean absolute relative difference (MARD) was lower in the CHF versus the SH group in glucose strata above 100 mg/dl, but there was no difference between the CHF and outpatient groups. Linear regression models showed that CHF versus outpatient, SH versus CHF, and coefficient of variation were significant predictors of higher MARD. Among subjects with CHF, MARD was not associated with brain natriuretic peptide or change in plasma volume, but it was significantly higher in subjects randomized to IV insulin (p = .04)., Conclusions: The results suggest that SH and glycemic variability are more important determinants of CGM accuracy than known CHF status alone in hospitalized patients., (© 2012 Diabetes Technology Society.)

Results of randomised controlled trials of tight glycaemic control in hospital inpatients might vary with population and disease state. Individualised therapy for different hospital inpatient populations and identification of patients at risk of hyperglycaemia might be needed. One risk factor that has received much attention is the presence of pre-existing diabetes. So-called stress hyperglycaemia is usually defined as hyperglycaemia resolving spontaneously after dissipation of acute illness. The term generally refers to patients without known diabetes, although patients with diabetes might also develop stress hyperglycaemia-a fact overlooked in many studies comparing hospital inpatients with or without diabetes. Investigators of several studies have suggested that patients with stress hyperglycaemia are at higher risk of adverse consequences than are those with pre-existing diabetes. We describe classification of stress hyperglycaemia, mechanisms of harm, and management strategies.

Objective: Postprandial hyperglycemia is often inadequately assessed in diabetes management. Serum 1,5-anhydroglucitol (1,5-AG) drops as serum glucose rises above the renal threshold for glucose and has been proposed as a marker for postprandial hyperglycemia. The objective of this study is to demonstrate the relationship between 1,5-AG and postprandial hyperglycemia, as assessed by the continuous glucose monitoring system (CGMS) in suboptimally controlled patients with diabetes., Research Design and Methods: Patients with type 1 or type 2 diabetes and an HbA(1c) (A1C) between 6.5 and 8% with stable glycemic control were recruited from two sites. A CGMS monitor was worn for two consecutive 72-h periods. Mean glucose, mean postmeal maximum glucose (MPMG), and area under the curve for glucose above 180 mg/dl (AUC-180), were compared with 1,5-AG, fructosamine (FA), and A1C at baseline, day 4, and day 7., Results: 1,5-AG varied considerably between patients (6.5 +/- 3.2 mug/ml [means +/- SD]) despite similar A1C (7.3 +/- 0.5%). Mean 1,5-AG (r = -0.45, P = 0.006) correlated with AUC-180 more robustly than A1C (r = 0.33, P = 0.057) or FA (r = 0.38, P = 0.88). MPMG correlated more strongly with 1,5-AG (r = -0.54, P = 0.004) than with A1C (r = 0.40, P = 0.03) or FA (r = 0.32, P = 0.07)., Conclusions: 1,5-AG reflects glycemic excursions, often in the postprandial state, more robustly than A1C or FA. 1,5-AG may be useful as a complementary marker to A1C to assess glycemic control in moderately controlled patients with diabetes.