Indian journal of pediatrics · 2024
Beyond HbA1c: Identifying Gaps in Glycemic Control Among Children and Young People with Type 1 Diabetes Using Continuous Glucose Monitoring.
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Tandon Ambica, Bhowmik Eshita, Ali Zebish, Tripathi Sarita, Bk Ajitha, Dabadghao Preeti, Sudhanshu Siddhnath, Bhatia Vijayalakshmi
Аннотация
OBJECTIVES: To describe continuous glucose monitoring (CGM) derived glycemic variables, and study their association with HbA1c and socio-economic factors in young people with Type 1 diabetes mellitus (T1DM).
METHODS: Ninety-two participants [age 15.7 ± 5.0 y (mean ± SD), HbA1c 8.0 ± 1.5% (mean ± SD)] wore a professional CGM sensor for 14 d.
RESULTS: Median (IQR) time in range (TIR) was 41 (18)%. Participants spent 41 ± 20% of their day in hyperglycemia (>180 mg/dl), and 14 (13)% in hypoglycemia (<70 mg/dl). High glycemic variability (percent CV >36%) was seen in 92% participants. Older age at diagnosis was associated with higher TIR (β = 0.267, p = 0.01), lower time above range (TAR) (β = -0.352, p <0.001), but higher time below range (TBR) (β = 0.274, p = 0.006). The use of NPH vs. glargine basal insulin was associated with higher TBR (β = -0.262, p = 0.009) but lower TAR (β = 0.202, p = 0.041). HbA1c showed negative correlation with TIR (r = -0.449, p <0.001) and TBR (r = -0.466, p <0.001) and positive correlation with TAR (r = 0.580, p <0.001) and mean glucose (r = 0.589, p <0.001).
CONCLUSIONS: These data demonstrate wide gaps between the recommended vs. real world glycemic variables in patients with T1DM in this region on multiple daily insulin injections. CGM identifies glycemic variability and complements HbA1c in improving glycemic control.
METHODS: Ninety-two participants [age 15.7 ± 5.0 y (mean ± SD), HbA1c 8.0 ± 1.5% (mean ± SD)] wore a professional CGM sensor for 14 d.
RESULTS: Median (IQR) time in range (TIR) was 41 (18)%. Participants spent 41 ± 20% of their day in hyperglycemia (>180 mg/dl), and 14 (13)% in hypoglycemia (<70 mg/dl). High glycemic variability (percent CV >36%) was seen in 92% participants. Older age at diagnosis was associated with higher TIR (β = 0.267, p = 0.01), lower time above range (TAR) (β = -0.352, p <0.001), but higher time below range (TBR) (β = 0.274, p = 0.006). The use of NPH vs. glargine basal insulin was associated with higher TBR (β = -0.262, p = 0.009) but lower TAR (β = 0.202, p = 0.041). HbA1c showed negative correlation with TIR (r = -0.449, p <0.001) and TBR (r = -0.466, p <0.001) and positive correlation with TAR (r = 0.580, p <0.001) and mean glucose (r = 0.589, p <0.001).
CONCLUSIONS: These data demonstrate wide gaps between the recommended vs. real world glycemic variables in patients with T1DM in this region on multiple daily insulin injections. CGM identifies glycemic variability and complements HbA1c in improving glycemic control.