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Blood Glucose Monitoring in Paediatric Patients


rate of BG change was observed in the treatment group, suggesting an effect of the agent on glycaemic variability.34


Others have used


CGM data to evaluate the actions of different insulin regimens on glucose levels and variability.35,36


Perhaps the most exciting research that CGM has enabled is the development of the closed-loop artificial pancreas.37–39


The


development of CGM was a critical missing piece in closing the loop, as sophisticated insulin-infusion pumps have been used routinely for years. Current research has evolved into the testing of various control algorithms which use CGM data to guide intermittent insulin infusions.29,30,40


This rapidly developing field holds great promise for children with type 1 diabetes and their parents.


CGM accuracy continues to improve with each new generation of sensors. However, its general use has been limited by reimbursement matters and by a reluctance of the diabetes community to embrace it. Currently, third party reimbursement for CGM use has been limited to patients with recurrent BG <50 mg/dl or to those with documented hypoglycaemic unawareness. Other limitations and barriers to its use in children and adolescents, alluded to in the JDRF continuous monitoring study, need to be studied further.31


Enthusiasm for


continued use of this technology appears to wane over a relatively short (<12 months) period of time.


Conclusions


When used in accordance with the manufacturer’s recommendations and a healthcare professional’s recommended treatment algorithm,


1. Silverstein J, Klingensmith G, Copeland K, et al., Care of children and adolescents with type 1 diabetes, Diabetes Care, 2005;28:186–212.


2. 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;329:977–86.


3. Lucidarme N, Alberti C, Zaccaria I, et al., Alternate-site testing is reliable in children and adolescents with type 1 diabetes, except at the forearm for hypoglycemia detection, Diabetes Care, 2005;28:710–11.


4. Krouwer J, Cembrowski C, A review of standards and statistics used to describe blood glucose monitor performance, J Diabetes Sci Technol, 2010;4:75–83.


5. Boren S, Clarke W, Analytical and clinical performance of blood glucose monitors, J Diab Sci Technol, 2010;4:1–14.


6. Clarke W, Cox D, Gonder-Frederick L, Evaluating the clinical accuracy of self-blood glucose monitoring systems, Diabetes Care, 1987;10:622–8.


7. Pohl S, Gonder-Frederick L, Cox D, Evans W, Self- measurement of blood glucose concentration: clinical significance of patient-generated measurements, Diabetes Care, 1985;8:617–9.


8. Parkes J, Slatin S, Pardo S, Ginsberg B, A new consensus error grid to evaluate the clinical significance of inaccuracies in the measurement of blood glucose, Diabetes Care, 2000;23:1143–8.


9. Scott M, Bruns D, Boyd J, Sacks D, Tight glucose control in the intensive care unit: are glucose meters up to the task?, Clin Chem, 2009:55:18–20.


10. Zeigler R, Heidtmann B, Hilgard D, et al., Frequency of SMBG correlates with HbA1c and acute complications in children and adolescents with type 1 diabetes, Pediatr Diabetes, 2011;12:11–7.


11. Clarke W, Snyder A, Hypoglycemia; can the school system respond?, Diabetes Care, 1990;13:1097–8.


12. Klingensmith G, Kaufman F, Schatz D, Clarke W, Care of children with diabetes in the school and day care setting. ADA Position Statement, Diabetes Care, 1999;22:163–6.


13. Hellams M, Clarke W, Safe at School: A Virginia experience, Diabetes Care, 2007;30:1396–8.


14. Van den Berghe G, Wouters P, Weekers P, et al., Intensive insulin therapy in the critically ill patient, N Engl J Med, 2001;345:1359–67


15. Van den Berghe, G, Wilmer, A, Hermans G, et al. Intensive insulin therapy in the medical ICU, N Engl J Med,


2006;354:449–61.


16. The NICE-SUGAR Study Investigators, Intensive versus conventional glucose control in critically ill patients, N Engl J Med, 2009;360:1283–97.


17. Van den Berghe G, Schetz M, Vlasselaers D, et al., Clinical review: Intensive insulin therapy in critically ill patients: NICE-SUGAR or Leuven blood glucose target?, J Clin Endocrinol Metab, 2009;94:3163–70.


18. Preissig C, Rigby M, Pediatric critical illness hyperglycemia; risk factors associated with development and severity of hyperglycemia in critically ill children, J Pediatr, 2009;155:734–9.


19. Preissig C, Hansen I, Roerig P, Rigby M, A protocolized approach to identify and manage hyperglycemia in a pediatric critical care unit, Pediatr Crit Care Med, 2008;9:581–8.


20. Vlasselaers D, Milants I, Desmet I, et al., Intensive insulin therapy for patients in paediatric intensive care: a prospective, randomized, controlled study, Lancet, 2009;373:547–56.


21. Kovatchev B, Gonder-Frederick A, Cox D, Clarke W, Evaluating the accuracy of continuous glucose-monitoring sensors, Diabetes Care, 2004;27:1922–8.


22. Kovatchev B, Anderson S, Heinemann L, Clarke W, Comparison of the numerical and clinical accuracy of four continuous glucose monitors, Diabetes Care, 2008;31:1160–4.


23. McGarraugh G, Clarke W, Kovatchev B, Comparison of the clinical performance provided by the Free Style Navigator continuous interstitial glucose monitor versus traditional blood glucose readings, Diab Tech Therapeutics, 2010;12:365–71.


24. Gandrud L, Xing D, Kollman C, et al., The Medtronic MiniMed Gold continuous glucose monitoring system: an effective means to discover hypo- and hyperglycemia in children under 7 years of age, Diab Tech Therapeutics, 2007;9:307–16.


25. Wolpert H, Use of continuous glucose monitoring in the detection and prevention of hypoglycemia, J Diabetes Sci Technol, 2007;1:146–50.


26. Deiss D, Kordonououri O, Mayer K, et al., Long hypoglycemic periods detected by subcutaneous continuous glucose monitoring in toddlers and pre-school children with diabetes mellitus, Diab Med, 2001;18:337–8.


27. Kaufman F, Austin J Neinstein A, et al., Nocturnal hypoglycemia detected with continuous glucose monitoring system in pediatric patients with type 1 diabetes, J Pediatr, 2002;141:625–30.


28. Amin R, Roiss K, Acerini C, et al., Hypoglycemia prevalence in prepubertal children with type 1 diabetes on standard insulin regimen: use of continuous glucose monitoring, Diabetes Care, 2003;26:662–7.


SBGM has proved to be a standard-of-care, reliable method for day-to-day treatment decisions for adults and children with type 1 diabetes. Its use has been associated with reductions in average


glucose levels (HbA1c), glycaemic variability, severe hypoglycaemia and diabetic ketoacidosis.


Analytical accuracy of SBGM systems will need to improve if they are to be used in critically ill hospitalised children and adults to adjust insulin infusions safely as part of tight glucose control protocols. SBGM should be a part of each child’s school care plan. Indeed, the importance of maintaining relatively euglycaemic BG levels during school is supported by recent evidence suggesting that both hypo- and hyperglycaemia have negative effects on cognitive function.41


On the other hand, CGM is in its infancy. It clearly produces glucose readings that are less analytically and clinically accurate than those generated by SBGM devices, but the additional information that CGM data communicate can more than offset this inaccuracy. As these systems become more accurate, their use in new and more sophisticated applications can be anticipated.


The potential changes in diabetes care which this powerful new monitoring tool may be expected to produce include marked


reductions in severe hypoglycaemia, glycaemic variability, HbA1c and by extension acute and long-term complications of type 1 diabetes. The role of CGM systems in the development of a practical closed-loop artificial pancreas for outpatient management of children with type 1 diabetes is clearly one of the most anticipated applications. n


29. Buckingham B, Chase H, Dassau E, et al., Prevention of nocturnal hypoglycemia using predictive alarm algorithms and insulin pump suspension, Diabetes Care, 2010;33:1013–17.


30. Dassau EE, Cameron F, Lee H, et al., Real-time hypoglycemia prediction suite using continuous glucose monitoring, Diabetes Care, 2010;33:1249–54.


31. The JDRF Continuous Monitoring Study Group, Continuous glucose monitoring and intensive treatment of type 1 diabetes, N Engl J Med, 2008;359:1464–76.


32. Diabetes Research in Children Network (DirectNet) Study Group, Continuous glucose monitoring in children with type 1 diabetes, J Pediatr, 2007;151:388–93.


33. Chase H, Beck R, Xing D, et al., Continuous glucose monitoring in youth with type 1 diabetes: 12 month follow-up of the Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Randomized Trial, Diab Technol Ther, 2010;12:507–15.


34. Kovatchev B, Clarke W, Breton M, et al., Quantifying temporal glucose variability in diabetes via continuous glucose monitoring: mathematical methods and clinical application, Diabetes Technol & Therapeutics, 2005;7:849–62.


35. White N, Chase H, Arslanian S, et al., Comparison of glycemic variability associated with insulin glargine and intermediate- acting insulin when used as the basal component of multiple daily injections for adolescents with type 1 diabetes, Diabetes Care, 2009;32:387–93.


36. Diabetes Research in Children Network (DirectNet) Study Group, Use of the DirectNet Applied Treatment Algorithm (DATA) for diabetes management with a real-time continuous glucose monitor (the FreeStyle Navigator), Ped Diab, 2008;9:142–7.


37. Hovorka R, Continuous glucose monitoring and closed-loop systems, Diab Med, 2005;23:1–12.


38. Steil G, Rebrin K, Darwin C, et al., Feasibility of automating insulin delivery for the treatment of type 1 diabetes, Diabetes, 2006;55:3344–55.


39. Clarke WL, Kovatchev B, The artificial pancreas: how close are we to closing the loop?, Pediatr Endocrinol Rev, 2007;1:314–16.


40. Clarke W, Anderson S, Breton M, et al., Closed-loop artificial pancreas using subcutaneous glucose sensing and insulin delivery and a model predictive control algorithm: the Virginia experience, J Diab Sci Technol, 2009;5:1031–8.


41. Gonder-Frederick L, Zrebiec J, Bauchowitz A, et al., Cognitive function is disrupted by both hypo- and hyperglycemia in school-aged children with type 1 diabetes: a field study, Diabetes Care, 2009;32:1001–6.


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