Understanding the clinical implications of differences between glucose management indicator and glycated haemoglobin.
HbA1c
average glucose
continuous glucose monitoring
diabetes
glucose management indicator
Journal
Diabetes, obesity & metabolism
ISSN: 1463-1326
Titre abrégé: Diabetes Obes Metab
Pays: England
ID NLM: 100883645
Informations de publication
Date de publication:
04 2022
04 2022
Historique:
revised:
20
12
2021
received:
29
09
2021
accepted:
01
01
2022
pubmed:
6
1
2022
medline:
1
4
2022
entrez:
5
1
2022
Statut:
ppublish
Résumé
Laboratory measured glycated haemoglobin (HbA1c) is the gold standard for assessing glycaemic control in people with diabetes and correlates with their risk of long-term complications. The emergence of continuous glucose monitoring (CGM) has highlighted limitations of HbA1c testing. HbA1c can only be reviewed infrequently and can mask the risk of hypoglycaemia or extreme glucose fluctuations. While CGM provides insights in to the risk of hypoglycaemia as well as daily fluctuations of glucose, it can also be used to calculate an estimated HbA1c that has been used as a substitute for laboratory HbA1c. However, it is evident that estimated HbA1c and HbA1c values can differ widely. The glucose management indicator (GMI), calculated exclusively from CGM data, has been proposed. It uses the same scale (% or mmol/mol) as HbA1c, but is based on short-term average glucose values, rather than long-term glucose exposure. HbA1c and GMI values differ in up to 81% of individuals by more than ±0.1% and by more than ±0.3% in 51% of cases. Here, we review the factors that define these differences, such as the time period being assessed, the variation in glycation rates and factors such as anaemia and haemoglobinopathies. Recognizing and understanding the factors that cause differences between HbA1c and GMI is an important clinical skill. In circumstances when HbA1c is elevated above GMI, further attempts at intensification of therapy based solely on the HbA1c value may increase the risk of hypoglycaemia. The observed difference between GMI and HbA1c also informs the important question about the predictive ability of GMI regarding long-term complications.
Substances chimiques
Blood Glucose
0
Glycated Hemoglobin A
0
Glucose
IY9XDZ35W2
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
599-608Informations de copyright
© 2022 John Wiley & Sons Ltd.
Références
Deckert T, Poulsen JE, Larsen M. Prognosis of diabetics with diabetes onset before the age of thirty-one. Survival, causes of death, and complications. Diabetologia. 1978;14(6):363-370. doi:10.1007/BF01228130
Diabetes Control and Complications Trial Research Group, Nathan DM. The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. N Engl J Med. 1993;329(14):977-986.
Rahbar S, Blumenfeld O, Ranney HM. Studies of an unusual hemoglobin in patients with diabetes mellitus. Biochem Biophys Res Commun. 1969;36(5):838-843.
The diabetes control and complications trial (DCCT). Design and methodologic considerations for the feasibility phase. The DCCT Research Group. Diabetes. 1986;35:530-545.
Bergenstal RM, Beck RW, Close KL, et al. Glucose Management Indicator (GMI): a new term for estimating A1C from continuous glucose monitoring. Diabetes Care. 2018;41(11):2275-2280. doi:10.2337/dc18-1581
United Kingdom Prospective Diabetes Study Group (UKPDS). Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). UKprospective Diabetes Study (UKPDS) Group. Lancet. 1998;352(9131):837-853.
Stratton IM, Adler AI, Neil HAW, et al. Association of glycaemia with macrovascular and microvascular complications of type 2 diabetes (UKPDS 35): prospective observational study. BMJ. 2000;321(7258):405-412. doi:10.1136/bmj.321.7258.405
Tahara Y, Shima K. The response of GHb to stepwise plasma glucose change over time in diabetic patients. Diabetes Care. 1993;16:1313-1314.
Hudson PR, Child DF, Jones H, Williams CP. Differences in rates of glycation (glycation index) may significantly affect individual HbA1c results in type 1 diabetes. Ann Clin Biochem. 1999;36(4):451-459.
Bergenstal RM, Gal RL, Connor CG, et al. Racial differences in the relationship of glucose concentrations and hemoglobin A1c levels. Ann Intern Med. 2017;167:95-102.
Cohen RM, Holmes YR, Chenier TC, Joiner CH. Discordance between HbA1c and Fructosamine: evidence for a glycosylation gap and its relation to diabetic nephropathy. Diabetes Care. 2003;26:163-167.
Nayak AU, Holland MR, Macdonald DR, Nevill A, Singh BM. Evidence for consistency of the glycation gap in diabetes. Diabetes Care. 2011;34:1712-1716.
Hempe JM, Gomez R, McCarter RJ, Chalew SA. High and low hemoglobin glycation phenotypes in type 1 diabetes. J Diabetes Complications. 2002;16(5):313-320.
McCarter RJ, Hempe JM, Gomez R, Chalew SA. Biological variation in HbA1c predicts risk of retinopathy and nephropathy in type 1 diabetes. Diabetes Care. 2004;27(6):1259-1264.
Nathan DM, Kuenen J, Borg R, et al. Translating the A1C assay into estimated average glucose values. Diabetes Care. 2008;31(8):1473-1478.
Beck RW, Connor CG, Mullen DM, Wesley DM, Bergenstal RM. The fallacy of average: how using HbA1c alone to assess glycemic control can be misleading. Diabetes Care. 2017;40(8):994-999.
Danne T, Nimri R, Battelino T, et al. International consensus on use of continuous glucose monitoring. Diabetes Care. 2017;40(12):1631-1640.
Riddlesworth TD, Beck RW, Gal RL, et al. Optimal sampling duration for continuous glucose monitoring to determine long-term glycemic control. Diabetes Technol Ther. 2018;20:314-316.
Xu Y, Dunn TC, Ajjan RA. A kinetic model for glucose levels and hemoglobin A1c provides a novel tool for individualized diabetes management. J Diabetes Sci Technol. 2021;15(2):294-302. doi:10.1177/1932296819897613
Aleppo G, Ruedy KJ, Riddlesworth TD, et al. REPLACE-BG: a randomized trial comparing continuous glucose monitoring with and without routine blood glucose monitoring in adults with well-controlled type 1 diabetes. Diabetes Care. 2017;40(4):538-545.
Beck RW, Riddlesworth T, Ruedy K, et al. Effect of continuous glucose monitoring on glycemic control in adults with type 1 diabetes using insulin injections: the DIAMOND randomized clinical trial. JAMA. 2017;317(4):371-378.
Beck RW, Riddlesworth TD, Ruedy K, et al. Continuous glucose monitoring versus usual care in patients with type 2 diabetes receiving multiple daily insulin injections. Ann Intern Med. 2017;167(6):365-374.
Heinemann L, Freckmann G, Ehrmann D, et al. Real-time continuous glucose monitoring in adults with type 1 diabetes and impaired hypoglycaemia awareness or severe hypoglycaemia treated with multiple daily insulin injections (HypoDE): a multicentre, randomised controlled trial. Lancet. 2018;391(10128):1367-1377.
Leelarathna L, Beck RW, Bergenstal RM, et al. Glucose management indicator (GMI): insights and validation using Guardian 3 and navigator 2 sensor data. Diabetes Care. 2019;42(4):e60-e61.
Grimsmann JM, von Sengbusch S, Freff M, et al. Glucose management indicator based on sensor data and laboratory HbA1c in people with type 1 diabetes from the DPV database: differences by sensor type. Diabetes Care. 2020;43(9):e111-e112. doi:10.2337/dc20-0259
Leelarathna L, Thabit H, Hovorka R, Evans M. Estimated HbA1c and glucose management indicator (GMI): are they the same? Diabet Med. 2020;15:e14423. doi:10.1111/dme.14423
Service FJ, O'Brien PC. The relation of glycaemia to the risk of development and progression of retinopathy in the diabetic control and complications trial. Diabetologia. 2001;44:1215-1220.
Kilpatrick ES, Rigby AS, Atkin SL. The effect of glucose variability on the risk of microvascular complications in type 1 diabetes. Diabetes Care. 2006;29:1486-1490.
Beck RW, Bergenstal RM, Riddlesworth TD, et al. Validation of time in range as an outcome measure for diabetes clinical trials. Diabetes Care. 2019;42(3):400-405. doi:10.2337/dc18-1444
Hu Y, Shen Y, Yan R, et al. Relationship between estimated glycosylated hemoglobin using flash glucose monitoring and actual measured glycosylated hemoglobin in a Chinese population. Diabetes Ther. 2020;11(9):2019-2027.
Liu H, Yang D, Deng H, et al. Impacts of glycemic variability on the relationship between glucose management indicator from iPro™2 and laboratory hemoglobin A1c in adult patients with type 1 diabetes mellitus. Ther Adv Endocrinol Metab. 2020;11:1-9. doi:10.1177/2042018820931664
Oriot P, Hermans MP. “Mind the gap please…”: estimated vs. measured A1c from continuous measurement of interstitial glucose over a 3-month period in patients with type 1 diabetes. Acta Clin Belg. 2018;75(2):109-115.
Zafon C, Ciudin A, Valladares S, Mesa J, Simó R. Variables involved in the discordance between HbA1c and Fructosamine: the glycation gap revisited. Plos One. 2013;8(6):e66696. doi:10.1371/journal.pone.0066696
Cosson E, Banu I, Cussac-Pillegand C, et al. Glycation gap is associated with macroproteinuria but not with other complications in patients with type 2 diabetes. Diabetes Care. 2013;36:2070-2076.
Nayak AU, Nevill AM, Bassett P, Singh BM. Association of glycation gap with mortality and vascular complications in diabetes. Diabetes Care. 2013;36(10):3247-3253.
Nayak AU, Singh BM, Dunmore SJ. Potential clinical error arising from use of HbA1c in diabetes: effects of the glycation gap. Endocr Rev. 2019;40:988-999.
American Diabetes Association. Standards of Medical Care in Diabetes - 2009. Diabetes Care. 2009;32(suppl 1):S13-S61.
Perlman JE, Gooley TA, McNulty B, Meyers J, Hirsch IB. HbA1c and glucose management indicator discordance: a real-world analysis. Diabetes Technol Ther. 2021;23:253-258. doi:10.1089/dia.2020.0501
Battelino T, Danne T, Bergenstal RM, et al. Clinical targets for continuous glucose monitoring data interpretation: recommendations from the international consensus on time in range. Diabetes Care. 2019;42(8):1593-1603. doi:10.2337/dci19-0028
Bergenstal RM, Ahmann AJ, Bailey T, et al. Recommendations for standardizing glucose reporting and analysis to optimize clinical decision making in diabetes: the ambulatory glucose profile. J Diabetes Sci Technol. 2013;7:562-578.