A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA 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.MethodsWe 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.ResultsThe 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.ConclusionThe 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

Diabetic Myonecrosis: A Diagnostic and Treatment Challenge in Longstanding Diabetes

Objective. Diabetes mellitus is associated with microvascular and macrovascular complications; the most commonly recognized ones include diabetic nephropathy, retinopathy, and neuropathy. Less well-known complications are equally important, as timely recognition and treatment are essential to decrease short- and long-term morbidity. Methods. Herein, we describe a case of a 41-year-old female with longstanding, uncontrolled type 2 diabetes, who presented with classical findings of diabetic myonecrosis. Results. Our patient underwent extensive laboratory and imaging studies prior to diagnosis due to its rarity and similarity in presentation with other commonly noted musculoskeletal conditions. We emphasize the clinical presentation, laboratory and imaging findings, treatment regimen, and prognosis associated with diabetic myonecrosis. Conclusion. Diabetic myonecrosis is a rare complication of longstanding, poorly controlled diabetes mellitus. The diagnosis requires a high index of suspicion in the right clinical setting: acute onset nontraumatic muscular pain with associated findings on clinical exam, laboratory studies, and imaging. While the short-term prognosis is good, the recurrence rate remains high and long-term prognosis is poor given underlying uncontrolled diabetes and associated sequelae

Attitudes and Behaviors with Diabetes Technology Use in the Hospital: Multicenter Survey Study in the United States

Objective: To assess the attitudes, behaviors, and barriers with diabetes technology use in the general medicine hospital wards. Research Design and Methods: The authors developed a nonincentivized web-based anonymous survey that captured demographic and practice data regarding continuous subcutaneous insulin infusion (CSII) and continuous glucose monitor (CGM) use in the hospital. Setting: Four large hospital systems in the United States. Results: Among 128 survey respondents, 76%, 10%, and 6% were hospitalists, advanced practice providers, and primary care physicians, respectively. The majority of respondents rated the treatment of inpatient hyperglycemia (96%) and the continuation of CSII during the hospital stay (93%) "important." While most respondents (64%) acknowledged knowing the existence of their institution's policies for CSII use, only 84% of those respondents felt somewhat to very familiar with the policy. The most common barrier to CSII use in the inpatient setting was lack of practitioner (70%) and nursing (67%) knowledge of using the device. With regard to CGM use in the hospital, a minority (28%) of respondents were aware of their institution's CGM policies. Less than half of the providers, 43.8%, stated that, when admitting a patient, they reviewed CGM data to guide insulin dosing. Conclusions: In this US multicenter survey, we found that most inpatient practitioners valued glycemic control, but many were not familiar with institutional policies, had lack of knowledge with CSII, and were not reviewing CGM data