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Published on: June 11, 2012
Metrics for glycaemic control - from HbA1c to continuous glucose monitoring
Boris P Kovatchev1,2,3
1University of Virginia School of Medicine, 1215 Lee Street, Charlottesvile, Virginia 22908, USA.
Insights
Managing diabetes involves balancing blood sugar levels to avoid hypoglycemia. Lowering glucose variability is key, using metrics from HbA1c to continuous glucose monitoring (CGM) for better patient outcomes.
Area of Science:
- Endocrinology
- Metabolic Diseases
- Diabetes Mellitus Management
Background:
- Intensive treatment to lower HbA1c increases hypoglycemia risk.
- Diabetes management requires lifelong optimization of glycemia and avoidance of hypoglycemia.
- Lowering glucose variability is essential for effective diabetes control.
Purpose of the Study:
- To review the assessment, quantification, and control of glucose fluctuations in diabetes mellitus.
- To discuss the utility and limitations of HbA1c as a gold-standard metric.
- To explore glucose variability metrics and control strategies.
Main Methods:
- Review of literature on glycemic control and variability in diabetes.
- Analysis of HbA1c as a measure of average glycemia.
- Examination of glucose variability metrics from self-monitoring of blood glucose and continuous glucose monitoring (CGM).
- Discussion of pharmacological agents and artificial pancreas systems for glycemic control.
Main Results:
- HbA1c reflects glycemic control over months, while CGM metrics capture variability over minutes.
- Glucose variability has two principal dimensions: amplitude and time.
- Both average glycemia and glucose variability require comprehensive assessment.
Conclusions:
- HbA1c and glucose variability metrics provide complementary information on different timescales.
- Accurate assessment of glycemic fluctuation dynamics is crucial for effective diabetes management.
- Comprehensive data is vital for patients, physicians, decision-support systems, and artificial pancreas technology.
Abstract:
As intensive treatment to lower levels of HbA1c characteristically results in an increased risk of hypoglycaemia, patients with diabetes mellitus face a life-long optimization problem to reduce average levels of glycaemia and postprandial hyperglycaemia while simultaneously avoiding hypoglycaemia. This optimization can only be achieved in the context of lowering glucose variability. In this Review, I discuss topics that are related to the assessment, quantification and optimal control of glucose fluctuations in diabetes mellitus. I focus on markers of average glycaemia and the utility and/or shortcomings of HbA1c as a 'gold-standard' metric of glycaemic control; the notion that glucose variability is characterized by two principal dimensions, amplitude and time; measures of glucose variability that are based on either self-monitoring of blood glucose data or continuous glucose monitoring (CGM); and the control of average glycaemia and glucose variability through the use of pharmacological agents or closed-loop control systems commonly referred to as the 'artificial pancreas'. I conclude that HbA1c and the various available metrics of glucose variability reflect the management of diabetes mellitus on different timescales, ranging from months (for HbA1c) to minutes (for CGM). Comprehensive assessment of the dynamics of glycaemic fluctuations is therefore crucial for providing accurate and complete information to the patient, physician, automated decision-support or artificial-pancreas system.
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