Roger S. Mazze

Recommendations for Standardizing Glucose Reporting and Analysis to Optimize Clinical Decision Making in Diabetes: The Ambulatory Glucose Profile (AGP)

Abstract Underutilization of glucose data and lack of easy and standardized glucose data collection, analysis, visualization, and guided clinical decision making are key contributors to poor glycemic control among individuals with type 1 diabetes. An expert panel of diabetes specialists, facilitated by the International Diabetes Center and sponsored by the Helmsley Charitable Trust, met in 2012 to discuss recommendations for standardization of analysis and presentation of glucose monitoring data, with the initial focus on data derived from CGM systems. The panel members were introduced to a universal software report, the Ambulatory Glucose Profile (AGP), and asked to provide feedback on its content and functionality, both as a research tool and in clinical settings. This paper provides a summary of the topics and issues discussed during the meeting and presents recommendations from the expert panel regarding the need to standardize glucose profile summary metrics and the value of a uniform glucose report to aid clinicians, researchers, and patients.

Evaluating the Accuracy, Reliability, and Clinical Applicability of Continuous Glucose Monitoring (CGM): Is CGM Ready for Real Time?

BACKGROUND This study was designed to assess the accuracy, reliability, and contribution to clinical decision-making of two commercially available continuous glucose monitoring (CGM) devices using a novel analytical approach. STUDY DESIGN Eleven individuals with type 1 diabetes and five with type 2 diabetes wore a Guardian RT (GRT) (Medtronic Minimed, Northridge, CA) or DexCom STS Continuous Monitoring System (DEX) (San Diego, CA) device for 200 h followed by an 8-h laboratory study. A subset of these subjects wore both devices simultaneously. RESULTS Subjects produced 1,902 +/- 269 readings during the ambulatory phase. During the laboratory study we found: lag time of 21 +/- 5 min for GRT and 7 +/- 7 min for DEX (P < 0.005); mean absolute relative difference of 19.9% and 16.7%, respectively, for GRT and DEX; and glucose exposure (the ratio of study device/laboratory reference device [YSI Instruments, Inc., Yellow Springs, OH] area under the curve) of 95 +/- 6% for GRT and 101 +/- 13% for DEX. Reliability measured during laboratory study showed 82% for DEX and 99% for GRT. Clarke Error Grid analysis (YSI reference) showed for GRT 59% of values in zone A, 34% in zone B, and 7% in zone D and for DEX 70% in zone A, 28% in zone B, 1% in zone C, and 1% in zone D. Bland-Altman plots (YSI standard) yielded for DEX 3 mg/dL (95% confidence interval, -78 to 84 mg/dL) and for GRT -21 mg/dL (95% confidence interval, -124 to 82 mg/dL). Six of eight subjects completed both home and laboratory simultaneous use of DEX and GRT. Lag times were inconsistent between devices, ranging from 0 to 32 min; area under the curve revealed a tendency for DEX to report higher total glucose exposure than GRT for the same patient. CONCLUSIONS CGM detects abnormalities in glycemic control in a manner heretofore impossible to obtain. However, our studies revealed sufficient incongruence between simultaneous laboratory blood glucose levels and interstitial fluid glucose (after calibrations) to question the fundamental assumption that interstitial fluid glucose and blood glucose could be made identical by resorting to algorithms based on concurrent blood glucose levels alone.

Cost-effectiveness of medical nutrition therapy provided by dietitians for persons with non-insulin-dependent diabetes mellitus

OBJECTIVE To conduct a cost analysis and cost-effectiveness study based on a randomized clinical trial of basic nutrition care (BC) and practice guidelines nutrition care (PGC) provided by dietitians in outpatient clinics. DESIGN Subjects with non-insulin-dependent diabetes mellitus (NIDDM) from three states (Minnesota, Florida, Colorado) were randomly assigned to a group receiving BC or a group receiving PGC for a 6-month clinical trial. Along with data about medical and clinical outcomes, data about cost resources were collected. The cost-effectiveness of PGC compared with BC was calculated using per-patient costs and glycemic outcomes for the 6 months of the study. A net cost-effectiveness ratio comparing BC and PGC, including the cost savings resulting from changes in medical therapy, was also calculated. SUBJECTS The study reports on a sample of 179 subjects with NIDDM between the ages of 38 and 76 years who completed the clinical trial. RESULTS Patients in the PGC group experienced a mean 1.1 +/- 2.8 mmol/L decrease in fasting plasma glucose level 6 months after entry to the study, for a total per-patient cost of

Ambulatory Glucose Profile: Representation of Verified Self-Monitored Blood Glucose Data

112. PGC costs included one glycated hemoglobin assay used by the dietitian to evaluate nutrition outcomes. Patients in the BC group experienced a mean 0.4 +/- 2.7 mmol/L decrease, for a total per-patient cost of

Rationale for Insulin Management in Gestational Diabetes Mellitus

42. In the PGC group, 17 persons had changes in therapy, which yielded an average 12-month cost savings prorated for all patients of

Driving Mishaps Among Individuals With Type 1 Diabetes A prospective study

31.49. In contrast, in the BC group, 9 persons had changes in therapy, for an average 12-month prorated cost savings of

An Epidemiologic Model for Diabetes Mellitus: Incidence, Prevalence, and Mortality

3.13. Each unit of change in fasting plasma glucose level from entry to the 6-month follow-up can be achieved with an investment of

Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the ambulatory glucose profile.

5.75 by implementing BC or of

Diurnal glucose patterns of exenatide once weekly: a 1-year study using continuous glucose monitoring with ambulatory glucose profile analysis.

5.84 by implementing PGC. If net costs are considered (per-patient costs--cost savings due to therapy changes), the cost-effectiveness ratios become

Characterizing blood pressure control in individuals with Type 2 diabetes: the relationship between clinic and self-monitored blood pressure.

5.32 for BC and