Retrospective Analysis of Continuous Glucose Monitoring Data With the Surveillance Error Grid Supports Nonadjunctive Dosing Decisions

利用监测误差网格对连续血糖监测数据进行回顾性分析,有助于制定非辅助给药决策

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Abstract

OBJECTIVE: The objective was to assess clinical risks of inaccurate continuous glucose monitoring (CGM) system readings as estimated by the surveillance error grid (SEG). METHODS: Values from Dexcom G4 Platinum system with an advanced algorithm (Software 505) were plotted on the SEG with temporally matched reference venous (YSI) values collected during clinic visits on days 1, 4, and 7 of sensor wear. Data from a pediatric study (N = 79, age [mean ± SD] 12.2 ± 4.6 years, all with type 1 diabetes) and an adult study (N = 51, age 46.7 ± 15.8 years, 44 with type 1 diabetes and 7 with type 2 diabetes) were used. RESULTS: Pediatric data included 2262 paired points, of which 1990 (88.0%) were in the "no risk" zone. Adult data included 2263 paired points, of which 2056 (90.9%) were in the "no risk" zone. Performance was best on Day 4, when 92.7% and 93.3% of points from the pediatric and adult studies, respectively, were in the "no risk" zone. Nine of the 4525 points (<0.2%) from 5 different sensors were in zones representing moderate risk, and none were in zones representing great or extreme risk. CONCLUSIONS: SEG analysis suggests that in pediatric and adult subjects with diabetes, using CGM values for diabetes management poses minimal risk to the user. CGM users also benefit from glucose trends and alerts.

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