Impact of factory‐calibrated Freestyle Libre System with new glucose algorithm measurement accuracy and clinical performance in children with type 1 diabetes during summer camp

• Published in: Pediatric diabetes Vol. 22; no. 2; pp. 261 - 270
• Main Authors: Szadkowska, Agnieszka, Michalak, Arkadiusz, Łosiewicz, Aleksandra, Kuśmierczyk, Hanna, Krawczyk‐Rusiecka, Kinga, Chrzanowski, Jędrzej, Gawrecki, Andrzej, Zozulińska‐Ziółkiewicz, Dorota, Fendler, Wojciech
• Format: Journal Article
• Language: English
• Published: Former Munksgaard John Wiley & Sons A/S 01.03.2021; John Wiley & Sons, Inc
• Subjects: Accuracy; Adolescent; Algorithms; Blood glucose; Blood Glucose - metabolism; Blood Glucose Self-Monitoring - instrumentation; Calibration; Camping; Child; Children; Diabetes; Diabetes mellitus (insulin dependent); Diabetes Mellitus, Type 1 - blood; Female; flash glucose monitoring; freestyle libre; Glucose; Glucose monitoring; Glycated Hemoglobin A - metabolism; Humans; intermittently‐scanned continuous glucose monitoring; Male; real‐life; Reproducibility of Results; Summer; summer camp; type 1 diabetes; type 1 diabetes; children; intermittently-scanned continuous glucose monitoring; accuracy; flash glucose monitoring; freestyle libre; summer camp; real-life
• ISSN: 1399-543X; 1399-5448; 1399-5448
• DOI: 10.1111/pedi.13135

Background Factory‐calibrated intermittently‐scanned Continuous Glucose Monitoring (isCGM) device FreeStyle Libre (FSL) has recently received improvements in its glucose tracking algorithm and calibration procedures, which are claimed to have improved its accuracy. Objective To compare the accuracy of two generations of 14‐days FSL devices (A in 2016, B in 2019) to self‐monitored blood glucose measurements (SMBG) in children with type 1 diabetes in real‐life conditions during a summer camp. Materials and Methods Two largely independent groups of youth with type 1 diabetes took part in summer camps. In 2016 they used FSL‐A, in 2019 FSL‐B. On scheduled days, participants performed supervised 8‐point glucose profiles with FSL and SMBG. The accuracy vs SMBG was assessed with mean absolute relative difference (MARD) and clinical surveillance error grid (SEG). Results We collected 1655 FSL‐SMBG measurement pairs from 78 FSL‐A patients (age 13 ± 2.3 years old; HbA1c: 7.6 ± 0.8%) and 1796 from 58 in FSL‐B group (age 13.8 ± 2.3 years old, HbA1c: 7.5 ± 1.1%)—in total 3451 measurements. FSL‐B displayed lower MARD than FSL‐A (11.3 ± 3.1% vs 13.7 ± 4.6%, P = .0003), lower SD of errors (20.2 ± 6.7 mg/dL vs 24.1 ± 9.6 mg/dL, P = .0090) but similar bias (−7.6 ± 11.8 mg/dL vs −6.5 ± 8 mg/dL, P = .5240). Both FSL‐A and FSL‐B showed significantly higher MARD when glycaemia was decreasing >2 mg/dL/min (FSL‐A:22.3 ± 18.5%; FSL‐B:17.9 ± 15.8%, P < .0001) compared with stable conditions (FSL‐A: 11.4 ± 10.4%, FSL‐B:10.1 ± 9.1%) and when the system could not define the glycaemic trend (FSL‐A:16.5 ± 16.3%; FSL‐B:15.2 ± 14.9%, P < .0001). Both generations demonstrated high percentage of A‐class and B‐class results in SEG (FSL‐A: 96.4%, FSL‐B: 97.6%) with a significant shift from B (decrease by 3.7%) to A category (increase by 3.9%) between generations (FSL‐A: 16/80.4%; FSL‐B:12.3/85.3%, P = .0012). Conclusion FSL‐B demonstrated higher accuracy when compared to FSL‐A However, when glycemia is decreasing or its trend is uncertain, the verification with a glucose meter is still advisable.