Abstract
Background and Objective: Controversy exists regarding which individuals will benefit most from commencement of diabetes technologies such as continuous subcutaneous insulin infusion (CSII) or continuous glucose monitoring systems (CGMS), such as 'real-time' sensor-augmented pumping (SAP). Because higher usage correlates with haemoglobin A1c (HbA1c) achieved, we aimed to predict future usage of technologies using a questionnaire-based tool. Subjects: The tool was distributed to two groups of youth with type 1 diabetes; group A (n=50; mean age 12±2.5yr) which subsequently commenced 'real-time' CGMS and group B (n=47; mean age 13±3yr) which commenced CSII utilisation. Methods: For the CGMS group, recommended usage was ≥5days (70%) per week [≥70%=high usage (HU); <70%=low usage (LU)], assessed at 3months. In the CSII group, HU was quantified as entering ≥5 blood sugars per day to the pump and LU as <5 blood sugars per day, at 6months from initiation. Binary logistic regression with forward stepwise conditional was used to utilise tool scales and calculate an applied formula. Results: Of the CGMS group, using gender, baseline HbA1c, and two subscales of the tool generated a formula which predicted both high and low usage with 92% accuracy. Twelve (24%) showed HU vs. 38 who exhibited LU at 3months. Of the CSII group, 32 (68%) exhibited HU vs. 15 who exhibited LU at 6months. Four tool items plus gender predicted HU/LU with 95% accuracy. Conclusions: This pilot study resulted in successful prediction of individuals who will and those who will not go on to show recommended usage of CSII and CGMS.
| Original language | English |
|---|---|
| Journal | Pediatric Diabetes |
| Volume | 17 |
| Issue number | 3 |
| Pages (from-to) | 174-183 |
| Number of pages | 10 |
| ISSN | 1399-543X |
| DOIs | |
| Publication status | Published - 1 May 2016 |
Keywords
- CGMS
- CSII
- HbA1c
- Self-care
- Type 1 diabetes
