Bolus Advisors: Sources of Error, Targets for Improvement

Abstract

Bolus advisors that are designed to improve the accuracy of individual bolus doses relative to a meal's carb content and the current glucose have not substantially changed since they were introduced 15 years ago despite an obvious need for enhancement and innovation. Although some glycemic benefits have been demonstrated, bolus advisors largely ignore the large amounts of clinical data they gather that could have a significant impact on glucose outcomes. Concerns have also been raised regarding the aggressive nature of largely unpublished or poorly explained bolus advisor algorithms. Hypoglycemia and hyperglycemia remain significant risks due to inaccurate bolus advisor settings and the absence of tracking or an inappropriate handling of bolus on board. This review covers common sources for bolus advisor error such as the selection of physiologically inappropriate bolus advisor settings, the use of short duration of insulin action times, poor algorithm logic that tends to cover all carb intake fully, and an excessive reliance on simplistic dosing algorithms. As well as discussing these areas, we provide 21 ways to improve current bolus calculators.

Carbohydrate counting: How accurate should it be to achieve glycemic control in patients on intensive insulin regimens?

“…where B is the bolus, CHO are the carbohydrates planned to be consumed in that meal, ICR is the insulin-to-carb ratio (n.b., ICR > 0), G is the pre-meal blood glucose, G T is the pre-meal blood glucose target, IS F is the insulin sensitivity factor (n.b., IS F > 0), K is a constant reflecting the physiologic status of the patient, and IOB (Insulin-on-Board) is the insulin remaining active from the previously administrated bolus [6,7]. In the following analysis, we will consider 250009-1 K = 1 (i.e., the influence of illness, physical activity or medication on insulin and glucose metabolism of patients is not addressed in this study) and IOB = 0 (i.e., the time between meals is higher than the duration of insulin action, and there is no insulin stacking).…”

Home glucose meters: How accurate should they be to avoid dysglycemia in patients using carbohydrate counting?

“…allows patients using carbohydrate counting to calculate the insulin bolus (i.e., prandial and correctional insulin) for each meal, according to the carbohydrates planned to be consumed in that meal (CHO), the insulin-to-carb ratio (ICR), the preprandial blood glucose target (G T ), the preprandial blood glucose value (G), the insulin sensitivity factor (IS F), the physiologic status of the patient represented by K, and the insulin remaining active from the last bolus (IOB, Insulin-on-Board) [5,6]. In the subsequent analysis, we will consider K = 1 (i.e., the impact of illness, physical activity or medication on insulin and glucose metabolism of patients will not be addressed in this study) and IOB = 0 (i.e., it will be considered that the time between meals is larger than the duration of the insulin action, and there is no insulin stacking).…”

Emerging Technologies for Diabetes Care

“…This would enable safer and more accurate adjustments to bolus doses and potentially reduce hypoglycemic and hyperglycemic events. 48 Factory calibration for CGMs eliminates user calibration errors, improves convenience, reduces the expense of meterbased calibrations, and potentially improves sensor accuracy. 49 One company currently developing an AP system reportedly chose a factory-calibrated CGM due to concerns about the potential inaccuracy introduced through user calibration errors.…”