ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

Endocrine Abstracts (2017) 51 P070 | DOI: 10.1530/endoabs.51.P070

Does maximising the use of bolus calculator glucose meters improves glycaemic control in children and adolescents with type 1 diabetes?

Fiona Rutherford, Murray Bain & Christina Wei

St George’s University Hospital NHS Foundation Trust, London, UK.

Introduction: Bolus calculator glucose meters (BCGM) facilitate self-management of patients with type 1 diabetes (T1DM). However, their effectiveness is dependent on the accuracy of the data entered, use of their smart functions and adherence to the insulin dosages advised. This study investigates whether optimising the use of BCGM is associated with better glycaemic control in children and adolescents with T1DM, and obstacles to preventing their effective use.

Methods: Subjects were BCGM (AccuChek Expert meter) users with T1DM on a daily multiple injection (MDI) regimen under a single paediatric diabetes centre in London. Patient demographics (current age, gender, age and time since diagnosis, deprivation scores) and most recent HbA1c were collected from the clinic database. Capillary blood glucose (CBG) and carbohydrate (CHO) recordings over 1 month within the corresponding 3-month period of HbA1c collected were obtained from routine clinic BCGM download (Diasend). Statistical analysis including Spearman’s correlation, multiple regression and Mann-Whitney-U test were performed using SPSSv23, at 5% significance.

Results: Data from 70 patients (29 males) were collected. Six were excluded including 3 diagnosed <6 months and 3 with incomplete data. Median(ranges) of current age was 12.9(1.2-18.7) years, age at diagnosis 7.0(1.1–17.0) years and length of diagnosis 2.7(0.7–13.5) years. Median HbA1c was 68(30–130) mmol/mol. Mean recorded episodes of CHO entered/day was 2.0(0–4.7) and CBG/day 4.1(0.3–12.4). HbA1c deteriorated with increased length of diagnosis (r=0.44, P<0.001), but showed no associations with current age, age at diagnosis, deprivation scores or gender. Better HbA1c was associated with increased CBG (r=−0.45, P<0.001) and CHO (r=−0.39, P=0.002) recordings. HbA1c remained positively associated with length of diagnosis (b=0.4, P=0.001) and negatively with increased CHO recordings (b=0.24, P=0.04) on multiple regression analysis. Increased length of diagnosis was associated with reduced frequency of CGB (r=−0.55, P<0.001) and CHO (r=−0.44, P<0.001) recordings. Patients who have been downloading BCGM data at home (n=19) demonstrated lower HbA1c than those who did not [62(43–77) vs 76(30–130), P=0.026].

Conclusion: Use of BCGM showed a positive effect on HbA1c. Deterioration of glycaemic control is associated with a decline usage over time. Additional support should target patients showing signs of “diabetes burn-out” over time from the demands of intensive self-management.

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