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Frequency of flash glucose monitoring and glucose metrics: real-world observational data from Saudi Arabia

Mohammad Y. Al-Harbi, Abdulhameed Albunyan, Ahmed Nahari, Kalvin Kao, Laura Brandner, Manal El Jammal, Timothy C. Dunn

2022Diabetology & Metabolic Syndrome16 citationsDOIOpen Access PDF

Abstract

BACKGROUND: flash glucose monitoring in relation to scanning frequency, time in range (TIR) and estimated A1c (eA1c) in Saudi Arabia. METHODS: Anonymized reader data were analyzed according to scanning frequency quartiles, eA1c categories (<7%,≥7%‒≤9% or>9%) and TIR categories (<50%,≥50%‒≤70% or>70%). Sensors, grouped by reader, were required to have≥120 h of operation. Differences in scanning frequency, eA1c, TIR, time in hypoglycemia and hyperglycemia, and glucose variability (standard deviation [SD] and coefficient of variation [CV]) were analyzed between groups. RESULTS: 6097 readers, 35,747 sensors, and 40 million automatic glucose measurements were analyzed. Patients in the highest scanning frequency quartile (Q4, mean 32.0 scans/day) had lower eA1c (8.47%), greater TIR (46.4%) and lower glucose variation (SD 75.0 mg/dL, CV 38.2%) compared to the lowest quartile (Q1, mean 5.2 scans/day; eA1c 9.77%, TIR 32.8%, SD 94.9 mg/dL, CV 41.3%). Lower eA1c and higher TIR were associated with greater scanning frequency, lower glucose variability and less time in hyperglycemia. CONCLUSIONS: Higher scanning frequency in flash glucose users from Saudi Arabia is associated with lower eA1c, higher TIR, lower glucose variability and less time in hypoglycemia or hyperglycemia.

Topics & Concepts

QuartileMedicineHypoglycemiaCoefficient of variationStandard deviationDiabetes mellitusInternal medicineAnimal scienceEndocrinologyStatisticsMathematicsBiologyConfidence intervalDiabetes Management and ResearchHyperglycemia and glycemic control in critically ill and hospitalized patientsDiabetes, Cardiovascular Risks, and Lipoproteins
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