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Published in: BMC Endocrine Disorders 1/2019

Open Access 01-12-2019 | Hypoglycemia | Study protocol

Effect of 6 months’ flash glucose monitoring in adolescents and young adults with type 1 diabetes and suboptimal glycaemic control: managing diabetes in a ‘flash’ randomised controlled trial protocol

Authors: Sara E. Boucher, Andrew R. Gray, Martin de Bock, Esko J. Wiltshire, Barbara C. Galland, Paul A. Tomlinson, Jenny Rayns, Karen E. MacKenzie, Benjamin J. Wheeler

Published in: BMC Endocrine Disorders | Issue 1/2019

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Abstract

Background

Teenagers and young adults with type 1 diabetes (T1D) experience significant burden managing this serious chronic condition and glycaemic control is at its unhealthiest during this life stage. Flash glucose monitoring (FGM) is a new technology that reduces the burden of glucose monitoring by easily and discreetly displaying glucose information when an interstitial glucose sensor worn on the upper arm is scanned with a handheld reader, as opposed to traditional capillary glucose sampling by finger prick (otherwise known as self-monitored blood glucose, SMBG). The effectiveness of this technology and impacts of its long-term use in youth with pre-existing suboptimal glycaemic control are unknown. This study therefore aims to investigate the effectiveness of FGM in addition to standard care in young people with T1D.

Methods

This is a two phase study programme including a multi-centre randomised, parallel-group study consisting of a 6-month comparison between SMBG and FGM, with an additional 6-month continuation phase. We will enrol adolescents with T1D aged 13–20 years (inclusive), with suboptimal glycaemic control (mean glycated haemoglobin (HbA1c) in past 6 months ≥75 mmol/mol [≥9%]). Participants will be randomly allocated (1:1) to FGM (FreeStyle Libre; intervention group) or to continue SMBG with capillary blood glucose testing (usual care group). All participants will continue other aspects of standard care with the study only providing the FreeStyle Libre. At 6 months, the control group will cross over to the intervention. The primary outcome is the between group difference in changes in HbA1c at 6 months. Additional outcomes include a range of psychosocial and health economic measures as well as FGM acceptability.

Discussion

>If improvements are found, this will further encourage steps towards integrating FGM into regular diabetes care for youth with unhealthy glycaemic control, with the expectation it will reduce daily diabetes management burden and improve short- and long-term health outcomes in this high-risk group.

Trial registration

This trial was registered with the Australian New Zealand Clinical Trials Registry on 5 March 2018 (ACTRN12618000320​257p) and the World Health Organization International Clinical Trials Registry Platform (Universal Trial Number U1111-1205-5784).
Literature
1.
go back to reference Mayer-Davis EJ, Kahkoska AR, Jefferies C, Dabelea D, Balde N, Gon CX, Aschner P, Craig ME. ISPAD clinical practice consensus guidelines 2018: definition, epidemiology and classification of diabetes in children and adolescents. Pediatr Diabetes. 2018;19(Supp. 27):7–19.CrossRef Mayer-Davis EJ, Kahkoska AR, Jefferies C, Dabelea D, Balde N, Gon CX, Aschner P, Craig ME. ISPAD clinical practice consensus guidelines 2018: definition, epidemiology and classification of diabetes in children and adolescents. Pediatr Diabetes. 2018;19(Supp. 27):7–19.CrossRef
5.
go back to reference Bendas A, Rothe U, Kiess W, Kapellen TM, Stange T, Manuwald U, Salzsieder E, Holl RW, Schoffer O, Stahl-Pehe A. Trends in incidence rates during 1999-2008 and prevalence in 2008 of childhood type 1 diabetes mellitus in Germany–model-based National Estimates. PLoS One. 2015;10(7):e0123716.CrossRef Bendas A, Rothe U, Kiess W, Kapellen TM, Stange T, Manuwald U, Salzsieder E, Holl RW, Schoffer O, Stahl-Pehe A. Trends in incidence rates during 1999-2008 and prevalence in 2008 of childhood type 1 diabetes mellitus in Germany–model-based National Estimates. PLoS One. 2015;10(7):e0123716.CrossRef
6.
7.
go back to reference Dabelea D, Mayer-Davis EJ, Saydah S, et al. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778–86.CrossRef Dabelea D, Mayer-Davis EJ, Saydah S, et al. Prevalence of type 1 and type 2 diabetes among children and adolescents from 2001 to 2009. JAMA. 2014;311(17):1778–86.CrossRef
8.
go back to reference Reynolds KA, Helgeson V. Children with diabetes compared to peers: depressed? Distressed? A meta-analytic review. Ann of Behav Med. 2011;42(1):29–41.CrossRef Reynolds KA, Helgeson V. Children with diabetes compared to peers: depressed? Distressed? A meta-analytic review. Ann of Behav Med. 2011;42(1):29–41.CrossRef
9.
go back to reference Hood KK, Peterson CM, Rohan JM, Drotar D. Association between adherence and glycemic control in pediatric type 1 diabetes: a meta-analysis. Pediatrics. 2009;124(6):e1171–9.CrossRef Hood KK, Peterson CM, Rohan JM, Drotar D. Association between adherence and glycemic control in pediatric type 1 diabetes: a meta-analysis. Pediatrics. 2009;124(6):e1171–9.CrossRef
10.
go back to reference Rewers M, Pihoker C, Donaghue K, et al. Assessment and monitoring of glycemic control in children and adolescents with diabetes. Pediatr Diabetes. 2009;10(s12):71–81.CrossRef Rewers M, Pihoker C, Donaghue K, et al. Assessment and monitoring of glycemic control in children and adolescents with diabetes. Pediatr Diabetes. 2009;10(s12):71–81.CrossRef
11.
go back to reference Miller KM, Beck RW, Bergenstal RM, et al. Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D exchange clinic registry participants. Diabetes Care. 2013;36(7):2009–14.CrossRef Miller KM, Beck RW, Bergenstal RM, et al. Evidence of a strong association between frequency of self-monitoring of blood glucose and hemoglobin A1c levels in T1D exchange clinic registry participants. Diabetes Care. 2013;36(7):2009–14.CrossRef
12.
go back to reference Ziegler 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(1):11–7.CrossRef Ziegler 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(1):11–7.CrossRef
13.
go back to reference Davidson M, Penney ED, Muller B, Grey M. Stressors and self-care challenges faced by adolescents living with type 1 diabetes. Appl Nurs Res. 2004;17(2):72–80.CrossRef Davidson M, Penney ED, Muller B, Grey M. Stressors and self-care challenges faced by adolescents living with type 1 diabetes. Appl Nurs Res. 2004;17(2):72–80.CrossRef
14.
go back to reference Hains AA, Berlin KS, Davies WH, et al. Attributions of adolescents with type 1 diabetes in social situations: relationship with expected adherence, diabetes stress, and metabolic control. Diabetes Care. 2006;29(4):818–22.CrossRef Hains AA, Berlin KS, Davies WH, et al. Attributions of adolescents with type 1 diabetes in social situations: relationship with expected adherence, diabetes stress, and metabolic control. Diabetes Care. 2006;29(4):818–22.CrossRef
15.
go back to reference Borus JS, Laffel L. Adherence challenges in the management of type 1 diabetes in adolescents: prevention and intervention. Curr Opin Pediatr. 2010;22(4):405–11.CrossRef Borus JS, Laffel L. Adherence challenges in the management of type 1 diabetes in adolescents: prevention and intervention. Curr Opin Pediatr. 2010;22(4):405–11.CrossRef
16.
go back to reference Carroll AE, Downs SM, Marrero DG. What adolescents with type I diabetes and their parents want from testing technology: a qualitative study. Comput Inform Nurs. 2007;25(1):23–9.CrossRef Carroll AE, Downs SM, Marrero DG. What adolescents with type I diabetes and their parents want from testing technology: a qualitative study. Comput Inform Nurs. 2007;25(1):23–9.CrossRef
17.
go back to reference Dickinson JK, O’Reilly MM. The lived experience of adolescent females with type 1 diabetes. Diab Educ. 2004;30(1):99–107.CrossRef Dickinson JK, O’Reilly MM. The lived experience of adolescent females with type 1 diabetes. Diab Educ. 2004;30(1):99–107.CrossRef
18.
go back to reference Miller KM, Foster NC, Beck RW, et al. Current state of type 1 diabetes treatment in the US: updated data from the T1D exchange clinic registry. Diabetes Care. 2015;38(6):971–8.CrossRef Miller KM, Foster NC, Beck RW, et al. Current state of type 1 diabetes treatment in the US: updated data from the T1D exchange clinic registry. Diabetes Care. 2015;38(6):971–8.CrossRef
21.
go back to reference Foster NC, Beck RW, Miller KM, Clements MA, Rickels MR, DiMeglio LA, Maahs DM, Tamborlane WV, Bergenstal R, Smith E. State of type 1 diabetes management and outcomes from the T1D Exchange in 2016–2018. Diab Technol Ther. 2019;21(2). doi.org/https://doi.org/10.1089/dia.2018.0384 Foster NC, Beck RW, Miller KM, Clements MA, Rickels MR, DiMeglio LA, Maahs DM, Tamborlane WV, Bergenstal R, Smith E. State of type 1 diabetes management and outcomes from the T1D Exchange in 2016–2018. Diab Technol Ther. 2019;21(2). doi.org/https://​doi.​org/​10.​1089/​dia.​2018.​0384
25.
go back to reference Edge J, Acerini C, Campbell F, et al. An alternative sensor-based method for glucose monitoring in children and young people with diabetes. Arch Dis Child. 2017;102(6):543–9.CrossRef Edge J, Acerini C, Campbell F, et al. An alternative sensor-based method for glucose monitoring in children and young people with diabetes. Arch Dis Child. 2017;102(6):543–9.CrossRef
26.
go back to reference Bailey T, Bode BW, Christiansen MP, et al. The performance and usability of a factory-calibrated flash glucose monitoring system. Diabetes Technol Ther. 2015;17(11):787–94.CrossRef Bailey T, Bode BW, Christiansen MP, et al. The performance and usability of a factory-calibrated flash glucose monitoring system. Diabetes Technol Ther. 2015;17(11):787–94.CrossRef
27.
go back to reference Massa GG, Gys I, Op‘t Eyndt A, et al. Evaluation of the FreeStyle® libre flash glucose monitoring system in children and adolescents with type 1 diabetes. Horm Res Peadiatr. 2018;89(3):189–99.CrossRef Massa GG, Gys I, Op‘t Eyndt A, et al. Evaluation of the FreeStyle® libre flash glucose monitoring system in children and adolescents with type 1 diabetes. Horm Res Peadiatr. 2018;89(3):189–99.CrossRef
28.
go back to reference Dunn TC, Xu Y, Hayter G, Ajjan RA. Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: a European analysis of over 60 million glucose tests. Diabetes Res Clin Pract. 2018;137:37–46.CrossRef Dunn TC, Xu Y, Hayter G, Ajjan RA. Real-world flash glucose monitoring patterns and associations between self-monitoring frequency and glycaemic measures: a European analysis of over 60 million glucose tests. Diabetes Res Clin Pract. 2018;137:37–46.CrossRef
29.
go back to reference Campbell F, Bolinder J. FreeStyle Libre™ use for self-management of diabetes in teenagers and young adults. Diabetes. 208;67(Supplement 1). Campbell F, Bolinder J. FreeStyle Libre™ use for self-management of diabetes in teenagers and young adults. Diabetes. 208;67(Supplement 1).
30.
go back to reference Campbell FM, Murphy NP, Stewart C, et al. Outcomes of using flash glucose monitoring technology by children and young people with type 1 diabetes in a single arm study. Pediatr Diabetes. 2018;19(7):1294–301.CrossRef Campbell FM, Murphy NP, Stewart C, et al. Outcomes of using flash glucose monitoring technology by children and young people with type 1 diabetes in a single arm study. Pediatr Diabetes. 2018;19(7):1294–301.CrossRef
31.
go back to reference Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet. 2016;388(10057):2254–63.CrossRef Bolinder J, Antuna R, Geelhoed-Duijvestijn P, et al. Novel glucose-sensing technology and hypoglycaemia in type 1 diabetes: a multicentre, non-masked, randomised controlled trial. Lancet. 2016;388(10057):2254–63.CrossRef
33.
go back to reference Skinner H, Biscope S, Poland B, Goldberg E. How adolescents use technology for health information: implications for health professionals from focus group studies. J Med Internet Res. 2003;5(4):e32.CrossRef Skinner H, Biscope S, Poland B, Goldberg E. How adolescents use technology for health information: implications for health professionals from focus group studies. J Med Internet Res. 2003;5(4):e32.CrossRef
35.
go back to reference The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008;359(14):1464–76.CrossRef The Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group. Continuous glucose monitoring and intensive treatment of type 1 diabetes. N Engl J Med. 2008;359(14):1464–76.CrossRef
38.
go back to reference Chae M, Reith DM, Tomlinson PA, et al. Accuracy of verbal self-reported blood glucose in teenagers with type I diabetes at diabetes ski camp. J Diab Metab Disord. 2014;13(1):14.CrossRef Chae M, Reith DM, Tomlinson PA, et al. Accuracy of verbal self-reported blood glucose in teenagers with type I diabetes at diabetes ski camp. J Diab Metab Disord. 2014;13(1):14.CrossRef
39.
go back to reference Sjoeholm A, Gray A, Rayns J, et al. Prior knowledge of blood glucose meter download improves the accuracy of verbal self-reported blood glucose in teenagers with type I diabetes at ski camp. Acta Diabetol. 2016;53(4):637–42.CrossRef Sjoeholm A, Gray A, Rayns J, et al. Prior knowledge of blood glucose meter download improves the accuracy of verbal self-reported blood glucose in teenagers with type I diabetes at ski camp. Acta Diabetol. 2016;53(4):637–42.CrossRef
40.
41.
go back to reference Clarke W, Jones T, Rewers A, et al. Assessment and management of hypoglycemia in children and adolescents with diabetes. Pediatr Diabetes. 2009;10(s12):134–45.CrossRef Clarke W, Jones T, Rewers A, et al. Assessment and management of hypoglycemia in children and adolescents with diabetes. Pediatr Diabetes. 2009;10(s12):134–45.CrossRef
42.
go back to reference Ogden CL, Kuczmarski RJ, Flegal KM, et al. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics. 2002;109(1):45–60.CrossRef Ogden CL, Kuczmarski RJ, Flegal KM, et al. Centers for Disease Control and Prevention 2000 growth charts for the United States: improvements to the 1977 National Center for Health Statistics version. Pediatrics. 2002;109(1):45–60.CrossRef
43.
go back to reference Ministry of Health (NZ). HISO 10001:2017 ethnicity data protocols. Wellington: Ministry of Health. 2017. Ministry of Health (NZ). HISO 10001:2017 ethnicity data protocols. Wellington: Ministry of Health. 2017.
45.
go back to reference Lenters-Westra E, Slingerland RJ. Six of eight hemoglobin A1c point-of-care instruments do not meet the general accepted analytical performance criteria. Clin Chem. 2010;56(1):44–52.CrossRef Lenters-Westra E, Slingerland RJ. Six of eight hemoglobin A1c point-of-care instruments do not meet the general accepted analytical performance criteria. Clin Chem. 2010;56(1):44–52.CrossRef
46.
go back to reference Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.CrossRef Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.CrossRef
47.
go back to reference Varni JW, Seid M, Rode CA. The PedsQL™: measurement model for the pediatric quality of life inventory. Med Care. 1999;37(2):126–39.CrossRef Varni JW, Seid M, Rode CA. The PedsQL™: measurement model for the pediatric quality of life inventory. Med Care. 1999;37(2):126–39.CrossRef
48.
go back to reference Varni JW, Seid M, Kurtin PS. PedsQL™ 4.0: reliability and validity of the pediatric quality of life inventory™ version 4.0 generic Core scales in healthy and patient populations. Med Care. 2001;39(8):800–12.CrossRef Varni JW, Seid M, Kurtin PS. PedsQL™ 4.0: reliability and validity of the pediatric quality of life inventory™ version 4.0 generic Core scales in healthy and patient populations. Med Care. 2001;39(8):800–12.CrossRef
49.
go back to reference Varni JW, Burwinkle TM, Jacobs JR, et al. The PedsQL™ in type 1 and type 2 diabetes. Diabetes Care. 2003;26(3):631–7.CrossRef Varni JW, Burwinkle TM, Jacobs JR, et al. The PedsQL™ in type 1 and type 2 diabetes. Diabetes Care. 2003;26(3):631–7.CrossRef
50.
go back to reference Gonder-Frederick LA, Schmidt KM, Vajda KA, et al. Psychometric properties of the hypoglycemia fear survey-ii for adults with type 1 diabetes. Diabetes Care. 2011;34(4):801–6.CrossRef Gonder-Frederick LA, Schmidt KM, Vajda KA, et al. Psychometric properties of the hypoglycemia fear survey-ii for adults with type 1 diabetes. Diabetes Care. 2011;34(4):801–6.CrossRef
51.
go back to reference Cox DJ, Irvine A, Gonder-Frederick L, et al. Fear of hypoglycemia: quantification, validation, and utilization. Diabetes Care. 1987;10(5):617–21.CrossRef Cox DJ, Irvine A, Gonder-Frederick L, et al. Fear of hypoglycemia: quantification, validation, and utilization. Diabetes Care. 1987;10(5):617–21.CrossRef
53.
go back to reference Bradley C. Diabetes treatment satisfaction questionnaire: DTSQ. In: Bradley C, editor. Handbook of psychology and diabetes: a guide to psychological measurement in diabetes research and practice. Chur, Switzerland: Harwood Academic Publishers; 1994. p. 111–32. Bradley C. Diabetes treatment satisfaction questionnaire: DTSQ. In: Bradley C, editor. Handbook of psychology and diabetes: a guide to psychological measurement in diabetes research and practice. Chur, Switzerland: Harwood Academic Publishers; 1994. p. 111–32.
54.
go back to reference Galland BC, Kennedy GJ, Mitchell EA, Taylor BJ. Algorithms for using an activity-based accelerometer for identification of infant sleep–wake states during nap studies. Sleep Med. 2012;13(6):743–51.CrossRef Galland BC, Kennedy GJ, Mitchell EA, Taylor BJ. Algorithms for using an activity-based accelerometer for identification of infant sleep–wake states during nap studies. Sleep Med. 2012;13(6):743–51.CrossRef
55.
go back to reference Tan E, Healey D, Gray AR, Galland BC. Sleep hygiene intervention for youth aged 10 to 18 years with problematic sleep: a before-after pilot study. BMC Pediatr. 2012;12(1):189.CrossRef Tan E, Healey D, Gray AR, Galland BC. Sleep hygiene intervention for youth aged 10 to 18 years with problematic sleep: a before-after pilot study. BMC Pediatr. 2012;12(1):189.CrossRef
56.
go back to reference Meredith-Jones K, Williams S, Galland B, et al. 24 h Accelerometry: impact of sleep-screening methods on estimates of sedentary behaviour and physical activity while awake. J Sports Sci. 2016;34(7):679–85.CrossRef Meredith-Jones K, Williams S, Galland B, et al. 24 h Accelerometry: impact of sleep-screening methods on estimates of sedentary behaviour and physical activity while awake. J Sports Sci. 2016;34(7):679–85.CrossRef
57.
go back to reference Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.CrossRef Buysse DJ, Reynolds CF, Monk TH, et al. The Pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213.CrossRef
58.
go back to reference Galland BC, Gray AR, Penno J, et al. Gender differences in sleep hygiene practices and sleep quality in New Zealand adolescents aged 15 to 17 years. Sleep Health. 2017;3(2):77–83.CrossRef Galland BC, Gray AR, Penno J, et al. Gender differences in sleep hygiene practices and sleep quality in New Zealand adolescents aged 15 to 17 years. Sleep Health. 2017;3(2):77–83.CrossRef
59.
go back to reference Kahan BC, Morris TP. Improper analysis of trials randomised using stratified blocks or minimisation. Stat Med. 2012;31(4):328–40.CrossRef Kahan BC, Morris TP. Improper analysis of trials randomised using stratified blocks or minimisation. Stat Med. 2012;31(4):328–40.CrossRef
Metadata
Title
Effect of 6 months’ flash glucose monitoring in adolescents and young adults with type 1 diabetes and suboptimal glycaemic control: managing diabetes in a ‘flash’ randomised controlled trial protocol
Authors
Sara E. Boucher
Andrew R. Gray
Martin de Bock
Esko J. Wiltshire
Barbara C. Galland
Paul A. Tomlinson
Jenny Rayns
Karen E. MacKenzie
Benjamin J. Wheeler
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Endocrine Disorders / Issue 1/2019
Electronic ISSN: 1472-6823
DOI
https://doi.org/10.1186/s12902-019-0378-z

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