This commentary reviews several of the challenges encountered when attempting to quantify glycemic variability and correlate it with risk of diabetes complications. These challenges include (1) immaturity of the field, including problems of data accuracy, precision, reliability, cost, and availability; (2) larger relative error in the estimates of glycemic variability than in the estimates of the mean glucose; (3) high correlation between glycemic variability and mean glucose level; (4) multiplicity of measures; (5) correlation of the multiple measures; (6) duplication or reinvention of methods; (7) confusion of measures of glycemic variability with measures of quality of glycemic control; (8) the problem of multiple comparisons when assessing relationships among multiple measures of variability and multiple clinical end points; and (9) differing needs for routine clinical practice and clinical research applications.
ServiceFJMolnarGDRosevearJWAckermanEGatewoodLCTaylorWF. Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes.1970;19 (9): 644–55.
2.
ServiceFJNelsonRL. Characteristics of glycemic stability. Diabetes Care.1980;3 (1): 58–62.
3.
ServiceFJO'BrienPCRizzaRA. Measurements of glucose control. Diabetes Care.1987;10 (2): 225–37.
4.
CameronFJBaghurstPARodbardD. Assessing glycemic variation: Why, when and how?Pediatr Endocrinol Rev.2010;7Suppl 3: 432–44.
5.
SiegelaarSEHollemanFHoekstraJBDeVriesJH. Glucose variability; does it matter?Endocr Rev.2010;31 (2): 171–82.
6.
WeberCSchnellO. The assessment of glycemic variability and its impact on diabetes-related complications: An overview. Diabetes Technol Ther.2009;11 (10): 623–33.
7.
KeenanDBGrosmanBClarkHWRoyAWeinzimerSAShahRVMastrototaroJJ. Continuous glucose monitoring considerations for the development of a closed-loop artificial pancreas system. J Diabetes Sci Technol.2011;5 (6): 1327–36.
8.
McGarraughGVClarkeWLKovatchevBP. Comparison of the clinical information provided by the FreeStyle Navigator continuous interstitial glucose monitor versus traditional blood glucose readings. Diabetes Technol Ther.2010;12 (5): 365–71.
9.
BequetteBW. Continuous glucose monitoring: Real-time algorithms for calibration, filtering, and alarms. J Diabetes Sci Technol.2010;4 (2): 404–18.
RodbardD. Clinical interpretation of indices of quality of glycemic control and glycemic variability. Postgrad Med.2011;123 (4): 107–18.
12.
KilpatrickES. Arguments for and against the role of glucose variability in the development of diabetes complications. J Diabetes Sci Technol.2009;3 (4): 649–55.
13.
RodbardDBaileyTJovanovicLZisserHKaplanRGargSK. Improved quality of glycemic control and reduced glycemic variability with use of continuous glucose monitoring. Diabetes Technol Ther.2009;11 (11): 717–23.
14.
Snell-BergeonJKRomanRRodbardDGargSMaahsDMSchauerIEBergmanBCKinneyGLRewersM. Glycaemic variability is associated with coronary artery calcium in men with type 1 diabetes: The coronary artery calcification in type 1 diabetes study. Diabet Med.2010;27 (12): 1436–42.
15.
SchisanoBTripathiGMcGeeKMcTernanPGCerielloA. Glucose oscillations, more than constant high glucose, induce p53 activation and a metabolic memory in human endothelial cells. Diabetologia.2011;54 (5): 1219–26.
16.
SiegelaarSEKerrLJacoberSJDevriesJH. A decrease in glucose variability does not reduce cardiovascular event rates in type 2 diabetic patients after acute myocardial infarction: A reanalysis of the HEART2D study. Diabetes Care.2011;34 (4): 855–7.
17.
RodbardD. Interpretation of continuous glucose monitoring data: Glycemic variability and quality of glycemic control. Diabetes Technol Ther.2009;11Suppl 1: S55–67.
18.
RodbardD. New and improved methods to characterize glycemic variability using continuous glucose monitoring. Diabetes Technol Ther.2009;11 (9): 551–65.
19.
RodbardD. Glycemic variability: Measurement and utility in clinical medicine and research–one viewpoint. Diabetes Technol Ther.2011;13 (11): 1077–80.
20.
MarlingCRShubrookJHVernierSJWileyMTSchwartzFL. Characterizing blood glucose variability using new metrics with continuous glucose monitoring data. J Diabetes Sci Technol.2011;5 (4): 871–8.
21.
HermanidesJVriesendorpTMBosmanRJZandstraDFHoekstraJBDevriesJH. Glucose variability is associated with intensive care unit mortality. Crit Care Med.2010;38 (3): 838–42.
22.
MoriYTaniguchiYSezakiKYokoyamaJUtsunomiyaK. Liraglutide narrows the range of circadian glycemic variations in Japanese type 2 diabetes patients and nearly fattens these variations in drug-naive type 2 diabetes patients: A continuous glucose monitoring-based study. Diabetes Technol Ther.2011;13 (11): 1139–44.
23.
ThomasASchönauerMAchermannFSchnellOHanefeldMZiegelaschHJMastrototaroJHeinemannL. The “glucose pentagon”: Assessing glycemic control of patients with diabetes mellitus by a model integrating different parameters from glucose Profiles. Diabetes Technol Ther.2009;11 (6): 399–409.
24.
BaghurstPARodbardDCameronFJ. The minimum frequency of glucose measurements from which glycemic variation can be consistently assessed. J Diabetes Sci Technol.2010;4 (6): 1382–5.
25.
BaghurstPA. Calculating the mean amplitude of glycemic excursion from continuous glucose monitoring data: An automated algorithm. Diabetes Technol Ther.2011;13 (3): 296–302.
HillNRThompsonBBruceJMatthewsDRHindmarshP. Glycaemic risk assessment in children and young people with Type 1 diabetes mellitus. Diabet Med.2009;26 (7): 740–3.
