Professional continuous glucose monitoring in subjects with type 1 diabetes: Retrospective hypoglycemia detection

Journal of Diabetes Science and Technology

Volumn 7, Issue 1, 2013, Pages 135-143

  Jensen, Morten Hasselstrmø ^a   Christensen, Toke Folke ^a   Tarnow, Lise ^b   Mahmoudi, Zeinab ^a   Johansen, Mette Dencker ^a   Hejlesen, Ole Kristian ^a,c,d  

^a AALBORG UNIVERSITY   (Denmark)

^b STENO DIABETES CENTER   (Denmark)

^c UNIVERSITY OF AGDER   (Norway)

^d UNIVERSITY OF TROMSØ   (Norway)

Author keywords

Continuous glucose monitoring; Diabetes; Hypoglycemia; Machine learning; Retrospective

Indexed keywords

GLUCOSE; INSULIN ASPART;

ADULT; AREA UNDER THE CURVE; ARTICLE; AUTOMATED PATTERN RECOGNITION; BLOOD GLUCOSE MONITORING; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; CONTINUOUS GLUCOSE MONITORING; CONTINUOUS GLUCOSE MONITORING SYSTEM; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; GLUCOSE BLOOD LEVEL; GLUCOSE SENSOR; HUMAN; INSULIN DEPENDENT DIABETES MELLITUS; INSULIN HYPOGLYCEMIA; MALE; MONITOR; RECEIVER OPERATING CHARACTERISTIC; RETROSPECTIVE STUDY; SENSITIVITY AND SPECIFICITY; SUPPORT VECTOR MACHINE; ALGORITHM; AUTOMATION; BLOOD; HYPOGLYCEMIA; MIDDLE AGED; PHYSIOLOGIC MONITORING;

ADULT; ALGORITHMS; AUTOMATION; BLOOD GLUCOSE; BLOOD GLUCOSE SELF-MONITORING; DIABETES MELLITUS, TYPE 1; HUMANS; HYPOGLYCEMIA; MALE; MIDDLE AGED; MONITORING, PHYSIOLOGIC; RETROSPECTIVE STUDIES; SENSITIVITY AND SPECIFICITY;

EID: 84880287850     PISSN: None     EISSN: 19322968     Source Type: Journal    
DOI: 10.1177/193229681300700116     Document Type: Article

References (42)

1. The Diabetes Control and Complications Trial Research Group. 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):977-86.
2. UK Prospective Diabetes Study (UKPDS) Group. Intensive blood-glucose control with sulphonylureas or insulin compared with conventional treatment and risk of complications in patients with type 2 diabetes (UKPDS 33). Lancet. 1998;352(9131):837-53.
3. Sanders K, Mills J, Martin FI, Del Horne DJ. Emotional attitudes in adult insulin-dependent diabetics. J Psychosom Res. 1975;19(4):241-6.
4. Nardacci EA, Bode BW, Hirsch IB. Individualizing care for the many: the evolving role of professional continuous glucose monitoring systems in clinical practice. Diabetes Educ. 2010;36 Suppl 1:4S-21S.
5. Murphy HR, Rayman G, Lewis K, Kelly S, Johal B, Dufield K, Fowler D, Campbell PJ, Temple RC. Effectiveness of continuous glucose monitoring in pregnant women with diabetes: randomised clinical trial. BMJ. 2008;337:a1680.
6. Kaufman FR, Gibson LC, Halvorson M, Carpenter S, Fisher LK, Pitukcheewanont P. A pilot study of the continuous glucose monitoring system: clinical decisions and glycemic control after its use in pediatric type 1 diabetic subjects. Diabetes Care. 2001;24(12):2030-4. (Pubitemid 33716516)
7. Chico A, Vidal-Ríos P, Subirà M, Novials A. The continuous glucose monitoring system is useful for detecting unrecognized hypoglycemias in patients with type 1 and type 2 diabetes but is not better than frequent capillary glucose measurements for improving metabolic control. Diabetes Care. 2003;26(4):1153-7. (Pubitemid 36929264)
8. Weber KK, Lohmann T, Busch K, Donati-Hirsch I, Riel R. High frequency of unrecognized hypoglycaemias in patients with type 2 diabetes is discovered by continuous glucose monitoring. Exp Clin Endocrinol Diabetes. 2007;115(8):491-4. (Pubitemid 350056760)
9. Wojciechowski P, Ryœ P, Lipowska A, Gawêska M, Małecki M. Efficacy and safety comparison of continuous glucose monitoring and self-monitoring of blood glucose in type 1 diabetes: systematic review and meta-analysis. Pol Arch Med Wewn. 2011;121(10):333-43.
10. Jungheim K, Wientjes KJ, Heinemann L, Lodwig V, Koschinsky T, Schoonen AJ; Glucose Monitoring Study Group. Subcutaneous continuous glucose monitoring: feasibility of a new microdialysis-based glucose sensor system. Diabetes Care. 2001;24(9):1696-7.
11. Gilliam LK, Hirsch IB. Practical aspects of real-time continuous glucose monitoring. Diabetes Technol Ther. 2009;11 Suppl 1:S75-82.
12. Blevins TC, Bode BW, Garg SK, Grunberger G, Hirsch IB, Jovanoviè L, Nardacci E, Orzeck EA, Roberts VL, Tamborlane WV; AACE Continuous Glucose Monitoring Task Force, Rothermel C. Statement by the American Association of Clinical Endocrinologists Consensus Panel on continuous glucose monitoring. Endocr Pract. 2010;16(5):730-45.
13. Rebrin K, Sheppard NF Jr, Steil GM. Use of subcutaneous interstitial fluid glucose to estimate blood glucose: revisiting delay and sensor ofset. J Diabetes Sci Technol. 2010;4(5):1087-98.
14. Kovatchev B, Anderson S, Heinemann L, Clarke W. Comparison of the numerical and clinical accuracy of four continuous glucose monitors. Diabetes Care. 2008;31(6):1160-4.
15. Bode B, Gross K, Rikalo N, Schwartz S, Wahl T, Page C, Gross T, Mastrototaro J. Alarms based on real-time sensor glucose values alert patients to hypo- and hyperglycemia: the guardian continuous monitoring system. Diabetes Technol Ther. 2004;6(2):105-13. (Pubitemid 38445735)
16. Choleau C, Klein JC, Reach G, Aussedat B, Demaria-Pesce V, Wilson GS, Giford R, Ward WK. Calibration of a subcutaneous amperometric glucose sensor implanted for 7 days in diabetic patients. Part 2. Superiority of the one-point calibration method. Biosens Bioelectron. 2002;17(8):647-54. (Pubitemid 34607448)
17. Facchinetti A, Sparacino G, Cobelli C. Enhanced accuracy of continuous glucose monitoring by online extended Kalman filtering. Diabetes Technol Ther. 2010;12(5):353-63.
18. Aussedat B, Dupire-Angel M, Gifford R, Klein JC, Wilson GS, Reach G. Interstitial glucose concentration and glycemia: implications for continuous subcutaneous glucose monitoring. Am J Physiol Endocrinol Metab. 2000;278(4):E716-28. (Pubitemid 30215184)
19. Boyne MS, Silver DM, Kaplan J, Saudek CD. Timing of changes in interstitial and venous blood glucose measured with a continuous subcutaneous glucose sensor. Diabetes. 2003;52(11):2790-4. (Pubitemid 37339709)
20. Keenan DB, Mastrototaro JJ, Weinzimer SA, Steil GM. Interstitial fluid glucose time-lag correction for real-time continuous glucose monitoring. Biomed Signal Process Control. 2012. Epub ahead of print.
21. King C, Anderson SM, Breton M, Clarke WL, Kovatchev BP. Modeling of calibration efectiveness and blood-to-interstitial glucose dynamics as potential confounders of the accuracy of continuous glucose sensors during hyperinsulinemic clamp. J Diabetes Sci Technol. 2007;1(3):317-22.
22. Jensen MH, Cichosz SL, Dinesen B, Hejlesen OK. Moving prediction of exacerbation in chronic obstructive pulmonary disease for patients in telecare. J Telemed Telecare. 2012;18(2):99-103.
23. Nuryani N, Ling SS, Nguyen HT. Electrocardiographic signals and swarm-based support vector machine for hypoglycemia detection. Ann Biomed Eng. 2012;40(4):934-45.
24. Workgroup on Hypoglycemia, American Diabetes Association. Defining and reporting hypoglycemia in diabetes: a report from the American Diabetes Association Workgroup on Hypoglycemia. Diabetes Care. 2005;28(5):1245-9.
25. Cameron F, Niemeyer G, Gundy-Burlet K, Buckingham B. Statistical hypoglycemia prediction. J Diabetes Sci Technol. 2008;2(4):612-21.
26. Dassau E, Cameron F, Lee H, Bequette BW, Zisser H, Jovanovic L, Chase HP, Wilson DM, Buckingham BA, Doyle FJ 3rd. Real-time hypoglycemia prediction suite using continuous glucose monitoring: a safety net for the artificial pancreas. Diabetes Care. 2010;33(6):1249-54.
27. Palerm CC, Bequette BW. Hypoglycemia detection and prediction using continuous glucose monitoring-a study on hypoglycemic clamp data. J Diabetes Sci Technol. 2007;1(5):624-9.
28. Pappada SM, Cameron BD, Rosman PM, Bourey RE, Papadimos TJ, Olorunto W, Borst MJ. Neural network-based real-time prediction of glucose in patients with insulin-dependent diabetes. Diabetes Technol Ther. 2011;13(2):135-41.
29. Pedersen-Bjergaard U, Pramming S, Thorsteinsson B. Recall of severe hypoglycaemia and self-estimated state of awareness in type 1 diabetes. Diabetes Metab Res Rev. 2003;19(3):232-40. (Pubitemid 36675964)
30. Birk H, Moeslund TB. Recognizing gestures from the hand alphabet using principal component analysis. Master's thesis. Aalborg University; 1996.
31. Koller D, Sahami M. Toward optimal feature selection. International Conference on Machine Learning. 1996, 284-92.
32. Meyer D, Leisch F, Hornik K. The support vector machine under test. Neurocomput. 2003;55(1-2):169-86. (Pubitemid 37336675)
33. Duda R, Hart P, Stork D. Pattern classification. New York: John Wiley & Sons; 2001.
34. Department for Transport Road Safety Research Group. Report no. 61: stratifying hypoglycemic event risk in insulin-treated diabetes. Department for Transport Road Safety Research; 2006, 68-9.
35. Pérez-Gandía C, Facchinetti A, Sparacino G, Cobelli C, Gómez EJ, Rigla M, de Leiva A, Hernando ME. Artificial neural network algorithm for online glucose prediction from continuous glucose monitoring. Diabetes Technol Ther. 2010;12(1):81-8.
36. Diabetes Research In Children Network (Direcnet) Study Group, Buckingham BA, Kollman C, Beck R, Kalajian A, Fiallo-Scharer R, Tansey MJ, Fox LA, Wilson DM, Weinzimer SA, Ruedy KJ, Tamborlane WV. Evaluation of factors afecting CGMS calibration. Diabetes Technol Ther. 2006;8(3):318-25.
37. Giménez M, Lara M, Jiménez A, Conget I. Glycaemic profile characteristics and frequency of impaired awareness of hypoglycaemia in subjects with T1D and repeated hypoglycaemic events. Acta Diabetol. 2009;46(4):291-3.
38. Keenan DB, Cartaya R, Mastrototaro JJ. Accuracy of a new real-time continuous glucose monitoring algorithm. J Diabetes Sci Technol. 2010;4(1):111-8.
39. Zijlstra E, Heise T, Nosek L, Heinemann L, Heckermann S. Continuous glucose monitoring: quality of hypoglycaemia detection. Diabetes Obes Metab. 2012. Epub ahead of print.
40. Ellis SL, Naik RG, Gemperline K, Garg SK. Use of continuous glucose monitoring in patients with type 1 diabetes. Curr Diabetes Rev. 2008;4(3):207-17.
41. Blevins TC. Professional continuous glucose monitoring in clinical practice 2010. J Diabetes Sci Technol. 2010;4(2):440-56.
42. Berger M, Rodbard D. Computer simulation of plasma insulin and glucose dynamics after subcutaneous insulin injection. Diabetes Care. 1989;12(10):725-36. (Pubitemid 19284096)