The Effect of Mobile Application Euglyca in Glycemic Control of Children and Adolescents With Diabetes Mellitus Type-1
Phase: NA
Conditions: Diabetes Mellitus, Type 1
Sponsor: Aristotle University Of Thessaloniki

The effect of mobile application Euglyca on glycemic control of Children and 
Adolescents with Diabetes Mellitus Type 1 
 
Thessaloniki, Greece 12/30/2016 

Protocol 
Children and adolescents with T1DM who visited consecutively our clinic were asked 
to participate in the study provided they owned an Android smartphone and were 
familiar with its use. Patients were included after one of their parents or their legal 
guardian signed an informed consent. Inclusion criteria were: 1. Treatment with 
multiple daily injections (MDI) or continuous subcutaneous insulin infusion (CSII); 2. 
satisfactory knowledge of the concept of carbohydrates and lipids counting acquired 
following previous training by the physicians and nutritionist of the department at initial 
diagnosis and thereafter during follow-up visits. Exclusion criteria were:  1. Use of 
another medical application for diabetes in the previous 3 months; 2. lack of capacity 
of reading greek. Eighty patients were finally eligible to participate in the study. 80 
patients met the inclusion criteria and agreed to participate in the study. Subsequently 
they were randomized to two equally numbered groups by drawing one of two 
nontransparent envelopes which contained one ticket inscribed with either a E (for 
Euglyca group) or a C (for Control group). To ensure equal allocation rates within the 
2 groups, block randomization was employed. 
 
 
At the initial visit, patients randomized to the E group were advised to download 
the Euglyca application on their smartphones and they were asked to use the application 
for the calculation of the bolus insulin dose. Patients randomized to the C group were 
advised to calculate bolus insulin dose, the way they used to do. Patients repeated their 
visit to the endocrine pediatric clinic at 3, 6 and 12 months, the latter set as the terminal 
time-point of this study following the initial visit. At all 4 visits, anthropometrics 
(weight, height, BMI), blood pressure measurement and heart rate were noted down, 
while a peripheral blood sample was drawn from all patients in the morning of each 
visit after an overnight fast for measurement of glycemia and glycosylated hemoglobin 
(HbA1c) levels. Glucose measurements between 70 and 180 mg/dl were categorized as 
normoglycemia; any glucose measurement below 70mg/dl was categorized as 
hypoglycemia; glucose measurements at two hours postprandial measurement found 
above 180mg/dl were categorized as hyperglycemia. At baseline (first visit), at 6 
months (third visit) and at terminal time-point (12 months) all patients filled the World 
Health Organization-Standard DTSQ. Patients’ logbooks and readings from their 
glucose meters were reviewed by the physicians and nutritionist of the department at 
each of the four visits and the percentage of normoglycemic, hypoglycemic and 
hyperglycemic episodes during the preceding trimester was calculated for each patient. 

The change of HbA1c values from baseline to the terminal time-point for each group 
was set as primary outcome, while the percentage of normoglycemic, hypoglycemic 
and hyperglycemic events over the total number of glucose measurements during the 
preceding trimester of each visit was set as secondary outcome.  
 
Statistics 
 
Sample size was determined by estimating the change in HbA1c values 
(primary outcome) based on previous studies (7, 8), assuming 0.5% reduction in HbA1c 
in the intervention group with 80% power and 5% significance level. Power calculation 
resulted in 14 patients per group, while the target of the study had been set at 
recruitment of 80 patients altogether. Results are reported as mean ± standard deviation 
(SD) for quantitative variables. The absolute difference in a quantitative variable 
between two different time points was defined as Δ. All quantitative variables (HbA1c; 
ΔHbA1c; percentages of normoglycemic, hypoglycemic and hyperglycemic events 
over a total number of glucose measurements; DTSQ’s scores) were normally 
distributed and they were compared between the two studied groups of patients at the 
different time-points by employing  General Linear Models ANOVA and Bonferroni 
post-hoc test. Repeated measures ANOVA involved one factor between patients (factor 
“Group” with two levels) and one factor for the repeated measures within patients 
(factor “time” with 4 or 3 levels depending on the compared variable). Qualitative 
variables (gender and type of therapy) were compared by employing x2 (chi square) test 
after having computed absolute and relative frequencies (percentages %), Statistical 
significance was set at P<0,05. An intention to treat analysis was followed. IBM SPSS 
V23 Chicago, USA software was used for the statistical analysis.