Larry A Distiller1, Iain Cranston2, Roger Mazze2. 1. Centre for Diabetes and Endocrinology, Johannesburg, SA larryd@cdediabetes.co.za. 2. AGP Clinical Academy, Portsmouth Hospitals, NHST, Portsmouth, UK.
Abstract
BACKGROUND: In 2014, an innovative blinded continuous glucose monitoring system was introduced with automated ambulatory glucose profile (AGP) reporting. The clinical use and interpretation of this new technology has not previously been described. Therefore we wanted to understand its use in characterizing key factors related to glycemic control: glucose exposure, variability, and stability, and risk of hypoglycemia in clinical practice. METHODS: Clinicians representing affiliated diabetes centers throughout South Africa were trained and subsequently were given flash glucose monitoring readers and 2-week glucose sensors to use at their discretion. After patient use, sensor data were collected and uploaded for AGP reporting. RESULTS: Complete data (sensor AGP with corresponding clinical information) were obtained for 50 patients with type 1 (70%) and type 2 diabetes (30%), irrespective of therapy. Aggregated analysis of AGP data comparing patients with type 1 versus type 2 diabetes, revealed that despite similar HbA1c values between both groups (8.4 ± 2 vs 8.6 ± 1.7%, respectively), those with type 2 diabetes had lower mean glucose levels (9.2 ± 3 vs 10.3 mmol/l [166 ± 54 vs 185 mg/dl]) and lower indices of glucose variability (3.0 ± 1.5 vs 5.0 ± 1.9 mmol/l [54 ± 27 vs 90 ± 34.2 mg/dl]). This highlights key areas for future focus. CONCLUSIONS: Using AGP, the characteristics of glucose exposure, variability, stability, and hypoglycemia risk and occurrence were obtained within a short time and with minimal provider and patient input. In a survey at the time of the follow-up visit, clinicians indicated that aggregated AGP data analysis provided important new clinical information and insights.
BACKGROUND: In 2014, an innovative blinded continuous glucose monitoring system was introduced with automated ambulatory glucose profile (AGP) reporting. The clinical use and interpretation of this new technology has not previously been described. Therefore we wanted to understand its use in characterizing key factors related to glycemic control: glucose exposure, variability, and stability, and risk of hypoglycemia in clinical practice. METHODS: Clinicians representing affiliated diabetes centers throughout South Africa were trained and subsequently were given flash glucose monitoring readers and 2-week glucose sensors to use at their discretion. After patient use, sensor data were collected and uploaded for AGP reporting. RESULTS: Complete data (sensor AGP with corresponding clinical information) were obtained for 50 patients with type 1 (70%) and type 2 diabetes (30%), irrespective of therapy. Aggregated analysis of AGP data comparing patients with type 1 versus type 2 diabetes, revealed that despite similar HbA1c values between both groups (8.4 ± 2 vs 8.6 ± 1.7%, respectively), those with type 2 diabetes had lower mean glucose levels (9.2 ± 3 vs 10.3 mmol/l [166 ± 54 vs 185 mg/dl]) and lower indices of glucose variability (3.0 ± 1.5 vs 5.0 ± 1.9 mmol/l [54 ± 27 vs 90 ± 34.2 mg/dl]). This highlights key areas for future focus. CONCLUSIONS: Using AGP, the characteristics of glucose exposure, variability, stability, and hypoglycemia risk and occurrence were obtained within a short time and with minimal provider and patient input. In a survey at the time of the follow-up visit, clinicians indicated that aggregated AGP data analysis provided important new clinical information and insights.
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