Evaluating quality of glycemic control: Graphical displays of hypo-And hyperglycemia, time in target range, and mean glucose

Journal of Diabetes Science and Technology

Volumn 9, Issue 1, 2015, Pages 56-62

  Rodbard, David ^a  

^a Biomedical Informatics Consultants LLC   (United States)

Author keywords

continuous glucose monitoring; diabetes mellitus; glycemic control; hyperglycemia; hypoglycemia; self monitoring of blood glucose

Indexed keywords

GLUCOSE; HEMOGLOBIN A1C; GLUCOSE BLOOD LEVEL;

ARTICLE; ARTIFICIAL PANCREAS; BLOOD GLUCOSE METER; BLOOD GLUCOSE MONITORING; COMPUTER PROGRAM; GLUCOSE BLOOD LEVEL; GLYCEMIC CONTROL; HUMAN; HYPERGLYCEMIA; HYPOGLYCEMIA; RISK ASSESSMENT; ANALYSIS; BLOOD; COMPARATIVE STUDY; COMPLICATION; COMPUTER GRAPHICS; DIABETES MELLITUS, TYPE 1; EVALUATION STUDY; INFORMATION PROCESSING; MEASUREMENT ACCURACY; PREDICTIVE VALUE; QUALITY CONTROL; STANDARDS; STATISTICAL ANALYSIS; STATISTICS AND NUMERICAL DATA; TIME FACTOR;

BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; COMPUTER GRAPHICS; DATA ACCURACY; DATA DISPLAY; DATA INTERPRETATION, STATISTICAL; DIABETES MELLITUS, TYPE 1; HUMANS; HYPERGLYCEMIA; HYPOGLYCEMIA; PREDICTIVE VALUE OF TESTS; QUALITY CONTROL; TIME FACTORS;

EID: 84947945770     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/1932296814551046     Document Type: Article

References (30)

1. Mazze RS, Lucido D, Langer O, Hartmann K, Rodbard D. Ambulatory glucose profile: representation of verified selfmonitored blood glucose data. Diabetes Care. 1987;10(1): 111-117
2. Rodbard D. Potential role of computers in the clinical investigation and management of diabetes mellitus: an overview. Diabetes Care. 1988;11(1):54-61
3. Rodbard D. Optimizing display, analysis, interpretation and utility of self-monitoring of blood glucose (SMBG) data for management of patients with diabetes. J Diabetes Sci Technol. 2007;1(1):62-71
4. Mazze RS, Strock E, Wesley D, et al. Characterizing glucose exposure for individuals with normal glucose tolerance using continuous glucose monitoring and ambulatory glucose profile analysis. Diabetes Technol Ther. 2008;10(3):149-159
5. 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(2):562-578
6. Rodbard D. Standardization versus customization of glucose reporting. Diabetes Technol Ther. 2013;15(5):439-443
7. Levetan C, Want LL, Weyer C, et al. Impact of pramlintide on glucose fluctuations and postprandial glucose, glucagon, and triglyceride excursions among patients with type 1 diabetes intensively treated with insulin pumps. Diabetes Care. 2003;26(1):1-8
8. Rodbard D. Display of glucose distributions by date, time of day, and day of week: new and improved methods. J Diabetes Sci Technol. 2009;3(6):1388-1394
9. Patton SR, Williams LB, Eder SJ, Crawford MJ, Dolan L, Powers SW. Use of continuous glucose monitoring in young children with type 1 diabetes: implications for behavioral research. Pediatr Diabetes. 2011;12(1):18-24
10. McCall AL, Cox DJ, Brodows R, Crean J, Johns D, Kovatchev B. Reduced daily risk of glycemic variability: comparison of exenatide with insulin glargine. Diabetes Technol Ther. 2009;11(6):339-344
11. Garg S, Zisser H, Schwartz S, et al. Improvement in glycemic excursions with a transcutaneous, real-time continuous glucose sensor: a randomized controlled trial. Diabetes Care. 2006;29:44-50
12. Rodbard D, Bailey T, Jovanovic L, Zisser H, Kaplan R, Garg SK. Improved quality of glycemic control and reduced glycemic variability with use of continuous glucose monitoring. Diabetes Technol Ther. 2009;11(11):717-723
13. Rodbard D, Jovanovic L, Garg SK. Responses to continuous glucose monitoring in subjects with type 1 diabetes using continuous subcutaneous insulin infusion or multiple daily injections. Diabetes Technol Ther. 2009;11(12):757-765
14. Russell SJ, El-Khatib FH, Sinha M, et al. Outpatient glycemic control with a bionic pancreas in type 1 diabetes. N Engl J Med. 2014;371(4):313-325
15. Wikipedia. Ternary plot. Available at: http://en.wikipedia.org/wiki/Ternary-plot. Accessed February 11, 2014
16. WaterproofPaper.com. Free ternary diagram-triangular graph paper. Available at: http://www.waterproofpaper.com/graphpaper/ternary-diagram-triangular-graph-paper.shtml. Accessed February 11, 2014
17. Anonymous. Working with triangular graph paper. Available at: http://lorien.ncl.ac.uk/ming/Webnotes/sp3/triang/triplt.htm. Accessed February 11, 2014
18. Cinquegrani F. Excel spreadsheet to generate triangular graphs. Available at: http://www.prodomosua.it/zips/triangolare.xls Accessed February 11, 2014
19. Kovatchev BP, Otto E, Cox D, Gonder-Frederick L, Clarke W. Evaluation of a new measure of blood glucose variability in diabetes. Diabetes Care. 2006;29(11):2433-2438
20. Clarke W, Kovatchev B. Statistical tools to analyze continuous glucose monitor data. Diabetes Technol Ther. 2009;11(suppl 1):S45-S54
21. Hill NR, Hindmarsh PC, Stevens RJ, Stratton IM, Levy JC, Matthews DR. A method for assessing quality of control from glucose profiles. Diabet Med. 2007;24(7):753-758
22. Hill NR, Oliver NS, Choudhary P, Levy JC, Hindmarsh P, Matthews DR. Normal reference range for mean tissue glucose and glycemic variability derived from continuous glucose monitoring for subjects without diabetes in different ethnic groups. Diabetes Technol Ther. 2011;13(9):921-928
23. Rodbard D. Interpretation of continuous glucose monitoring data: glycemic variability and quality of glycemic control. Diabetes Technol Ther. 2009;11(suppl 1):S55-S67
24. Rodbard D. New and improved methods to characterize glycemic variability using continuous glucose monitoring. Diabetes Technol Ther. 2009;11(9):551-565
25. Bross IDJ. How to use RIDIT analysis. Biometrics. 1958;14(1):18-38
26. Rodbard D, Berger M, Pernick N. Computer, networking, and information systems to facilitate delivery of health care to patients with diabetes. In: Baba S, Kaneko T, eds., Diabetes 1994, Proceedings of the 15th International Diabetes Federation Congress, Kobe, 6-11 November 1994. Amsterdam, Netherlands: Elsevier; 1995:800-803
27. Little S, Shaw J, Home P. Hypoglycemia rates with basal insulin analogs. Diabetes Technol Ther. 2011;13(suppl 1):S53-S64
28. Cameron FJ, Baghurst PA, Rodbard D. Assessing glycemic variation: why, when and how? Pediatr Endocrinol Rev. 2010;7(suppl 3):432-444
29. Siegelaar SE, Holleman F, Hoekstra JB, DeVries JH. Glucose variability; does it matter? Endocr Rev. 2010;31(2):171-182
30. Thomas A, Schnauer M, Achermann F, et al. 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.