Automatically accounting for physical activity in insulin dosing for type 1 diabetes
Introduction
In health, the human body's blood glucose (BG) regulation is accomplished via various feedback mechanisms that govern the secretion and action of insulin – the main BG lowering hormone. The destruction of insulin-secreting beta cells in type 1 diabetes (T1D) results in the break-down of the endogenous BG regulation [1]. Consequently, exogenous insulin injections and careful BG monitoring are required to maintain glycemic levels within a target range (generally 70–180 mg/dL) and avoid potentially severe complications [2]. Carbohydrate intake increases glucose levels and is required to be matched by insulin injection for proper BG control. In standard therapy, the amount of insulin required at mealtime is broken down into two components: the amount required to compensate for the carbohydrates ingested during the meal, and the amount required to correct for any current elevated BG level. Additionally, people with T1D also need to consider the previously injected insulin still in circulation when calculating the total dose to be administered. The prevalent method used to calculate the required dosage of insulin can be explicitly formalized as follows [3]:where CHO is the amount of meal carbohydrates (g), CR is a person's carbohydrate-to-insulin ratio (g/U) used to determine the appropriate dose of insulin that compensates for the estimated increase in BG from the ingested CHO, Gtarget is the target BG value (mg/dL), CF is the BG correction factor (mg/dL/U) to account for BG excursions away from this target, and G is the BG value at the time of the meal bolus (mg/dL). Since insulin affects BG concentrations for several hours following its injection [4], the active insulin in circulation from the previous insulin injections is tracked by a concept called insulin on board (IOB). IOB is computed as the convolution of insulin injections within the past four-hours and insulin action curve obtained from a previous study by Swan et al. [4].
Insulin needs vary among people with T1D, and hence the therapy is tailored to the individual through patient-specific treatment parameters (e.g., CR and CF). The treatment parameters can also be adjusted to account for systematic diurnal variations in BG dynamics. Deviation from these patterns, however, requires additional care. Existing literature on physical activity (PA) related BG control in T1D can be classified into two categories based on their methodologies: (a) studies based on dose-response experiments, that explore the BG responses to various insulin and carbohydrate doses surrounding an exercise bout [5], [6], [7], and (b) studies based on algorithms that use biosensors to take/suggest actions for an ongoing exercise bout [8], [9], [10]. Conversely, non-exercise PA has seen little attention, and its effects on BG metabolism have been presumed to be minor. However, recent studies show that even short bouts of walking in the course of otherwise sedentary days significantly affect glucose metabolism [11], [12], [13], and thus require treatment adjustments to improve overall BG control [14], [15], [16]. In the present work, we propose a method that extends the mealtime insulin bolus calculation to account for the accumulated prolonged glycemic impact of the daily PA.
Section snippets
Materials and methods
In the development of the PA informed insulin dosing method, we utilize retrospective data collected from individuals with T1D under their free-living conditions. We quantify PA through “step count” recorded via an off-the-shelf PA tracker and inform the insulin dosing by (i) a quantified accumulated glycemic impact of prior PA in real-time (ii) a PA profile extracted from retrospective data, that is representative of systematic glycemic disturbances resulting from the individual's routine PA,
Representative case
To provide a comparable example while evaluating the performances of standard vs. PA-informed boluses, we select two days that belong to the same participant and satisfy the following criteria:
- (i)
similar BG traces that do not exceed the target BG at the dinnertime,
- (ii)
same amounts of carbohydrate intake at the dinnertime,
- (iii)
no residual insulin from previous boluses at the dinner time (i.e., at least four hours have passed since the last bolus insulin),
- (iv)
same amounts of insulin injection at the dinnertime,
- (v)
Discussion
Our results indicate a significantly improved glycemic control using the PA-informed bolus when compared to the standard bolus method. This improvement was achieved by reducing exposure to hypoglycemia and increasing the time spent in the target BG range. Note that in our simulations, no additional carbohydrate intake or basal insulin dose reduction was applied to treat hypoglycemia events as opposed to the real-life practice. This potentially resulted in higher than clinically expected
Declaration of Competing Interest
None.
Acknowledgments
B.O has no conflict of interest to disclose. S.D.P is employed by Dexcom, Inc. whose sensors were used in NCT02558491, NCT03394352; SDP reports royalties from IP licenses in this field, managed by the University of Virginia. C.F reports consulting fees from Epsilon (Abbott). MDB reports research support from Dexcom, Sanofi, and Tandem Diabetes Care; MDB reports consulting fees and honoraria from Air Liquide, Dexcom, and Tandem Diabetes Care; MDB reports royalties from IP licenses in this field,
References (25)
- et al.
A new table for prevention of hypoglycaemia during physical activity in type 1 diabetic patients
Diabetes Metab.
(2004) Breaking prolonged sitting reduces postprandial glycemia in healthy, normal-weight adults: a randomized crossover trial
Am. J. Clin. Nutr.
(2013)- et al.
Breaking up prolonged sitting with light-intensity walking improves postprandial glycemia, but breaking up sitting with standing does not
J. Sci. Med. Sport
(2015) Exercise management in type 1 diabetes: a consensus statement
Lancet Diabetes Endocrinol.
(2017)- et al.
Glucose metabolism and regulation: beyond insulin and glucagon
Diabetes Spectr.
(2004) Long-term complications of diabetes mellitus
N. Engl. J. Med.
(1993)- et al.
Guidelines for optimal bolus calculator settings in adults
J. Diabetes Sci. Technol.
(2011) - et al.
Effect of age of infusion site and type of rapid-acting analog on pharmacodynamic parameters of insulin boluses in youth with type 1 diabetes receiving insulin pump therapy
Diabetes Care
(2009) - D. Zaharieva, S.M. Mcgaugh, R. Pooni, T. Vienneau, T.T. Ly, M. Riddell, Reducing Basal Insulin 90 Min Before Exercise...
- et al.
Basal insulin reductions in anticipation of multiple exercise sessions in people with type 1 diabetes—a clinical perspective
Ann. Transl. Med.
(2018)
Adding heart rate signal to a control-to-range artificial pancreas system improves the protection against hypoglycemia during exercise in type 1 diabetes. Diabetes technology & therapeutics
Classification of physical activity: information to artificial pancreas control systems in real time
J. Diabetes Sci. Technol.
Cited by (0)
Registry numbers of clinical trials of the data used in the analyses of this manuscript: clinicaltrials.gov: NCT02558491 and NCT03394352.