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Associations between HbA1c and continuous glucose monitoring-derived glycaemic variables
I B Hirsch1, J B Welsh2, P Calhoun2
1University of Washington School of Medicine, Seattle, WA, USA.
Insights
Continuous glucose monitoring (CGM) metrics strongly correlate with HbA1c levels, offering insights into glucose control. These CGM metrics can guide diabetes therapy intensification independently of HbA1c alone.
Area of Science:
- Endocrinology
- Metabolic Diseases
- Diabetes Technology
Background:
- Glycemic control is crucial for managing diabetes.
- HbA1c provides a long-term measure of average blood glucose.
- Continuous glucose monitoring (CGM) offers real-time glucose data and derived metrics.
Purpose of the Study:
- To identify clinically useful associations between HbA1c levels and various CGM-derived metrics.
- To explore the relationship between traditional HbA1c measurements and advanced CGM parameters.
Main Methods:
- Retrospective analysis of CGM data and HbA1c levels from 530 adults with Type 1 or insulin-requiring Type 2 diabetes.
- Data collected from four randomized trials, each lasting at least 24 weeks.
- Participants grouped by HbA1c levels or CGM-derived glucose values.
Main Results:
- HbA1c strongly correlated with mean glucose (r=0.80) and time in range (r=-0.75).
- Weak correlations were observed with time spent below 3.9 mmol/l (r=-0.39) or 3.0 mmol/l (r=-0.21).
- Specific CGM metric thresholds (e.g., time in range >80%) were associated with HbA1c levels ≤53 mmol/mol (≤7.0%).
Conclusions:
- CGM-derived metrics show strong associations with HbA1c.
- These metrics may offer a complementary approach to guide diabetes therapy intensification.
- CGM metrics may enable therapy adjustments independently of HbA1c levels.
Aims:
To identify clinically useful associations between HbA1c levels and various continuous glucose monitoring-derived metrics.
Methods:
We retrospectively analysed end-of-study HbA1c levels and >2 weeks of continuous glucose monitoring data collected from 530 adults with Type 1 diabetes or insulin-requiring Type 2 diabetes during four randomized trials. Each trial lasted ≥24 weeks and provided central laboratory end-of-study HbA1c levels and continuous glucose monitoring data from the preceding 3 months. Participants were assigned to groups based on either HbA1c levels or continuous glucose monitoring-derived glucose values.
Results:
HbA1c was strongly correlated with mean glucose value (r=0.80), time spent with glucose values in the 3.9-10.0 mmol/l range (time in range; r=-0.75) and percentage of glucose values >13.9 mmol/l (r=0.72), but was weakly correlated with the percentage of glucose values <3.9 mmol/l (r=-0.39) or <3.0 mmol/l (r=-0.21). The median percentage of glucose values <3.0 mmol/l was <1.2% (<20 min/day) for all HbA1c -based groups, but the median percentage of values >13.9 mmol/l varied from 2.5% (0.6 h/day) to 27.8% (6.7 h/day) in the lowest and highest HbA1c groups, respectively. More than 90% of participants with either <2% of glucose values >13.9 mmol/l, mean glucose <7.8 mmol/l, or time in range >80% had HbA1c levels ≤53 mmol/mol (≤7.0%). For participants with HbA1c ≥64 mmol/mol (≥8.0%), the median time in range was 44%, with 90% of participants having a time in range of <59%.
Conclusions:
The associations shown in the present study suggest that continuous glucose monitoring-derived metrics may help guide diabetes therapy intensification efforts in an HbA1c -independent manner.
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