Background: Previous work derived a theoretically rigorous bolus insulin model. It was shown that the new model predicts insulin response of subjects without diabetes substantially better than the carbohydrate counting method (CHOcm). As most individuals with type 1 diabetes use the CHOcm, this article investigates if the new model can be applied to them. Methods: Equations are derived to characterize a person with type 1 diabetes. These are implemented on a cell phone that calculates bolus insulin dosages. In a small feasibility study the cell phone was used by 11 patients. Basal insulin remained unchanged. The subjects were experienced in the CHOcm and were using it at the start of the study. Continuous glucose monitoring data were recorded to capture blood glucose (BG) control elements such as average BG and tightness of control, as well as hypoglycemic and hyperglycemic events. A new rating method was proposed to estimate BG control. It (or a derivative thereof) may in the future become a valuable measure of total glycemic control. We used the status quo ante versus status quo approach to find indicative results. BG control for the same group when using CHOcm (status quo ante) was compared with BG control when using the new application (status quo). Results: Patients found the new application on the cell phone practical. Indicative results also showed BG control improvements, although the subjects were more experienced in the CHOcm. Depending on the weights assigned to the underlying control elements an improvement of between 26% and 64% was found. Conclusion: An indicative study (status quo ante vs. status quo) on 11 patients with type 1 diabetes showed that the new method can be practically and successfully applied on a cell phone. Glycemic control even improved. A new BG rating method was proposed. We believe there is enough preliminary indication to warrant a more detailed clinical trial in future by an institution with adequate funds and access to more patients.
ASJC Scopus subject areas
- Endocrinology, Diabetes and Metabolism
- Medical Laboratory Technology