Metrics for glycaemic control - from HbA1c to continuous glucose monitoring

被引:190
作者
Kovatchev, Boris P. [1 ,2 ,3 ]
机构
[1] Univ Virginia, Sch Med, 1215 Lee St, Charlottesville, VA 22908 USA
[2] Univ Virginia, Sch Engn & Appl Sci, Thornton Hall,POB 400259, Charlottesville, VA 22904 USA
[3] Univ Virginia, Sch Med, Ctr Diabet Technol, Ivy Translat Res Bldg,560 Ray C Hunt Dr, Charlottesville, VA 22903 USA
关键词
CLOSED-LOOP CONTROL; MEAN BLOOD-GLUCOSE; HYPOGLYCEMIA BEGETS HYPOGLYCEMIA; HEMOGLOBIN GLYCATION INDEX; ESTIMATED AVERAGE GLUCOSE; ARTIFICIAL PANCREAS; PLASMA-GLUCOSE; DIABETES COMPLICATIONS; CLINICAL-IMPLICATIONS; RACIAL-DIFFERENCES;
D O I
10.1038/nrendo.2017.3
中图分类号
R5 [内科学];
学科分类号
100201 [内科学];
摘要
As intensive treatment to lower levels of HbA(1c) 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 HbA(1c) 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 HbA(1c) and the various available metrics of glucose variability reflect the management of diabetes mellitus on different timescales, ranging from months (for HbA(1c)) 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.
引用
收藏
页码:425 / 436
页数:12
相关论文
共 120 条
[11]
Breton MD, 2016, DIABETES, V65, pA228
[12]
Multinight "Bedside" Closed-Loop Control for Patients with Type 1 Diabetes [J].
Brown, Sue A. ;
Kovatchev, Boris P. ;
Breton, Marc D. ;
Anderson, Stacey M. ;
Keith-Hynes, Patrick ;
Patek, Stephen D. ;
Jiang, Boyi ;
Ben Brahim, Najib ;
Vereshchetin, Paul ;
Bruttomesso, Daniela ;
Avogaro, Angelo ;
Del Favero, Simone ;
Boscari, Federico ;
Galasso, Silvia ;
Visentin, Roberto ;
Monaro, Marco ;
Cobelli, Claudio .
DIABETES TECHNOLOGY & THERAPEUTICS, 2015, 17 (03) :203-209
[13]
Glycemic variability:: A hemoglobin A1c-independent risk factor for diabetic complications [J].
Brownlee, M ;
Hirsch, IB .
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION, 2006, 295 (14) :1707-1708
[14]
The Artificial Pancreas: Are We There Yet? [J].
Cefalu, William T. ;
Tamborlane, William V. .
DIABETES CARE, 2014, 37 (05) :1182-1183
[15]
Decreased complexity of glucose dynamics in diabetes: evidence from multiscale entropy analysis of continuous glucose monitoring system data [J].
Chen, Jin-Long ;
Chen, Pin-Fan ;
Wang, Hung-Ming .
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY, 2014, 307 (02) :R179-R183
[16]
Childs BP, 2005, DIABETES CARE, V28, P1245
[17]
Statistical Tools to Analyze Continuous Glucose Monitor Data [J].
Clarke, William ;
Kovatchev, Boris .
DIABETES TECHNOLOGY & THERAPEUTICS, 2009, 11 :S45-S54
[18]
MEDICINE A Pancreas in a Box [J].
Clery, Daniel .
SCIENCE, 2014, 343 (6167) :133-135
[19]
Cobelli Claudio, 2009, IEEE Rev Biomed Eng, V2, P54, DOI 10.1109/RBME.2009.2036073
[20]
Dynamical glucometry: Use of multiscale entropy analysis in diabetes [J].
Costa, Madalena D. ;
Henriques, Teresa ;
Munshi, Medha N. ;
Segal, Alissa R. ;
Goldberger, Ary L. .
CHAOS, 2014, 24 (03)