Development of a New Tool to Assess Bolus Calculation and Carbohydrate Estimation
- PMID: 26907638
- DOI: 10.1089/dia.2015.0292
Development of a New Tool to Assess Bolus Calculation and Carbohydrate Estimation
Abstract
Background: Carbohydrate estimation and bolus calculation are two important skills for handling intensive insulin therapy and effectively using bolus calculators. Structured assessment of both skills is lacking. A new tool for the assessment of skills in carbohydrate estimation and bolus calculation was developed and evaluated.
Materials and methods: A new assessment tool (SMART) was developed that included 10 items for bolus calculation and 12 items for carbohydrate estimation. In total, 411 patients on intensive insulin treatment were recruited. Different parameters of glycemic control were used as validity criteria.
Results: The SMART tool achieved good reliability for the assessment of bolus calculation (Cronbach's α = 0.78) and sufficient reliability for the assessment of carbohydrate estimation (Cronbach's α = 0.67). A good bolus calculation skill was significantly associated with lower glycated hemoglobin values (r = -0.27), lower mean blood glucose levels (r = -0.29), and higher fluctuation of blood glucose control (r = -0.43). A good carbohydrate estimation skill was significantly associated with a lower frequency of severe hyperglycemia (r = -0.27) and a higher frequency of euglycemia (r = 0.26).
Conclusions: SMART is a reliable and valid tool for the assessment of both skills. Bolus calculation as well as carbohydrate estimation was associated with glycemic control. With the help of SMART, important skills for the management of intensive insulin therapy can be assessed separately. Thus, in clinical practice patients in need of assistance from a bolus calculator can be identified.
Similar articles
-
The relationship between carbohydrate and the mealtime insulin dose in type 1 diabetes.J Diabetes Complications. 2015 Nov-Dec;29(8):1323-9. doi: 10.1016/j.jdiacomp.2015.08.014. Epub 2015 Aug 20. J Diabetes Complications. 2015. PMID: 26422396 Review.
-
Long-term metabolic effects of continuous subcutaneous insulin infusion therapy in type 1 diabetes.Diabetes Technol Ther. 2013 Jul;15(7):544-9. doi: 10.1089/dia.2012.0331. Epub 2013 Apr 25. Diabetes Technol Ther. 2013. PMID: 23617252
-
The Use of a Smart Bolus Calculator Informed by Real-time Insulin Sensitivity Assessments Reduces Postprandial Hypoglycemia Following an Aerobic Exercise Session in Individuals With Type 1 Diabetes.Diabetes Care. 2020 Apr;43(4):799-805. doi: 10.2337/dc19-1675. Epub 2020 Mar 6. Diabetes Care. 2020. PMID: 32144167 Free PMC article. Clinical Trial.
-
Carbohydrate counting accuracy and blood glucose variability in adults with type 1 diabetes.Diabetes Res Clin Pract. 2013 Jan;99(1):19-23. doi: 10.1016/j.diabres.2012.10.024. Epub 2012 Nov 10. Diabetes Res Clin Pract. 2013. PMID: 23146371
-
Carbohydrate Counting in Children and Adolescents with Type 1 Diabetes.Nutrients. 2018 Jan 22;10(1):109. doi: 10.3390/nu10010109. Nutrients. 2018. PMID: 29361766 Free PMC article. Review.
Cited by
-
Efficacy of carbohydrate counting in people with type 1 and type 2 diabetes mellitus: a systematic review and meta-analysis.Diabetol Int. 2025 Apr 10;16(3):546-558. doi: 10.1007/s13340-025-00810-4. eCollection 2025 Jul. Diabetol Int. 2025. PMID: 40607153
-
Role of Automation/Technology in Day-to-Day Diabetes Care.Diabetes Technol Ther. 2016 May;18(5):273-5. doi: 10.1089/dia.2016.0091. Epub 2016 Mar 30. Diabetes Technol Ther. 2016. PMID: 27028696 Free PMC article. No abstract available.
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical