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

The Prescription of Allopurinol in a Tertiary Care Centre: Appropriate Indications and Dose Adjustment

Objective To determine the appropriateness (both indications and adequate dosage regimen via creatinine clearance estimation) of allopurinol by physicians of different specialties in a tertiary care centre. Patients and Methods In this cross sectional study computerized clinical records of 156 adult patients who were prescribed allopurinol from 12th November to 11th December, 2011 were retrieved from Al Hada Hospital Taif Saudi Arabia. Main outcome variables were approprsiate indications of allopurinol, prescribing physician's specialty, and dosage of allopurinol. The prescribed dosages were categorized into correct and incorrect dose adjustments based on creatinine clearance estimation. The SPSS version 16 was utilized for data analyses. Results The mean (±SD) age was 58.15 (±14.99) years. There were 105 (67.3%) males and 51 (32.7%) females with male to female ratio being 2:1. Allopurinol was frequently prescribed by nephrologists and family physicians in this study. Out of 156 patients, 46 (29.5%) patients received allopurinol with appropriate indications. Eighty-five (54.5%) patients were received allopurinol without dose adjustment based on their creatinine clearance estimation; among them, 21 (13.5%) received allopurinol with appropriate indications. Conclusion The inappropriate use of allopurinol (both the indication and prescribed dosage) is still a major problem in a large tertiary care centre. Furthermore, the specialty of physicians is also a contributory factor in this inappropriateness

The Relationship of Lean Body Mass With Aging to the Development of Diabetes

Abstract Context Older adults have the greatest burden of diabetes; however, the contribution of age-related muscle loss to its development remains unclear. Objective We assessed the relationship of lean body mass with aging to incident diabetes in community-dwelling adults. Design and Setting We studied participants in the Baltimore Longitudinal Study of Aging with median follow-up of 7 years (range 1-16). Cox proportional hazard models with age as the time scale were used. Time-dependent lean body mass measures were updated at each follow-up visit available. Participants Participants included 871 men and 984 women without diabetes who had ≥ 1 assessment of body composition using dual x-ray absorptiometry. Main Outcomes Incident diabetes, defined as self-reported history and use of glucose-lowering medications; or fasting plasma glucose ≥ 126 mg/dL and 2-hour oral glucose tolerance test glucose ≥ 200 mg/dL either at the same visit or 2 consecutive visits. Results The baseline mean [standard deviation] age was 58.9 [17.3] years. Men and women with a higher percentage of total lean body mass had lower fasting and 2-hour glucose levels, and less prediabetes (all P < 0.01). Among men, comparing highest versus lowest quartiles, percentage of total lean body mass (hazard ratio [HR], 0.46; 95% confidence interval, 0.22-0.97), percentage leg lean mass (HR, 0.38; 0.15-0.96), and lean-to-fat mass ratio (HR, 0.39; 0.17-0.89) were inversely associated with incident diabetes after accounting for race and attenuated after adjustment for height and weight. Conversely, absolute total lean body mass was positively associated with incident diabetes among women, with similar trends in men. No associations were observed with muscle strength or quality. Conclusions Relatively lower lean body mass with aging is associated with incident diabetes in men and partially related to anthropometrics, but not so in women