Modeling the acute effects of exercise on insulin kinetics in type 1 diabetes

Applying technologies to simplify strategies for exercise in type 1 diabetes

Challenges and fears related to managing glucose levels around planned and spontaneous exercise affect outcomes and quality of life in people living with type 1 diabetes. Advances in technology, including continuous glucose monitoring, open-loop insulin pump therapy and hybrid closed-loop (HCL) systems for exercise management in type 1 diabetes, address some of these challenges. In this review, three research or clinical experts, each living with type 1 diabetes, leverage published literature and clinical and personal experiences to translate research findings into simplified, patient-centred strategies. With an understanding of limitations in insulin pharmacokinetics, variable intra-individual responses to aerobic and anaerobic exercise, and the features of the technologies, six steps are proposed to guide clinicians in efficiently communicating simplified actions more effectively to individuals with type 1 diabetes. Fundamentally, the six steps centre on two aspects. First, regardless of insulin therapy type, and especially needed for spontaneous exercise, we provide an estimate of glucose disposal into active muscle meant to be consumed as extra carbohydrates for exercise ('ExCarbs'; a common example is 0.5 g/kg body mass per hour for adults and 1.0 g/kg body mass per hour for youth). Second, for planned exercise using open-loop pump therapy or HCL systems, we additionally recommend pre-emptive basal insulin reduction or using HCL exercise modes initiated 90 min (1-2 h) before the start of exercise until the end of exercise. Modifications for aerobic- and anaerobic-type exercise are discussed. The burden of pre-emptive basal insulin reductions and consumption of ExCarbs are the limitations of HCL systems, which may be overcome by future innovations but are unquestionably required for currently available systems.

Factors Affecting Reproducibility of Change in Glucose During Exercise: Results From the Type 1 Diabetes and EXercise Initiative

AIMS

To evaluate factors affecting within-participant reproducibility in glycemic response to different forms of exercise.

METHODS

Structured exercise sessions ~30 minutes in length from the Type 1 Diabetes Exercise Initiative (T1DEXI) study were used to assess within-participant glycemic variability during and after exercise. The effect of several pre-exercise factors on the within-participant glycemic variability was evaluated.

RESULTS

Data from 476 adults with type 1 diabetes were analyzed. A participant's change in glucose during exercise was reproducible within 15 mg/dL of the participant's other exercise sessions only 32% of the time. Participants who exercised with lower and more consistent glucose level, insulin on board (IOB), and carbohydrate intake at exercise start had less variability in glycemic change during exercise. Participants with lower mean glucose (P < .001), lower glucose coefficient of variation (CV) (P < .001), and lower % time <70 mg/dL (P = .005) on sedentary days had less variable 24-hour post-exercise mean glucose.

CONCLUSIONS

Reproducibility of change in glucose during exercise was low in this cohort of adults with T1D, but more consistency in pre-exercise glucose levels, IOB, and carbohydrates may increase this reproducibility. Mean glucose variability in the 24 hours after exercise is influenced more by the participant's overall glycemic control than other modifiable factors.

Effects of Aerobic Exercise on Systemic Insulin Degludec Concentrations in People with Type 1 Diabetes

BACKGROUND

There is conflicting evidence on the effect of exercise on systemic insulin concentrations in adults with type 1 diabetes.

METHODS

This prospective single-arm study examined the effect of exercise on systemic insulin degludec (IDeg) concentrations. The study involved 15 male adults with type 1 diabetes (age 30.7 ± 8.0 years, HbA1c 6.9 ± 0.7%) on stable IDeg regimen. Blood samples were collected every 15 minutes at rest, during 60 minutes of cycling (66% VO₂max) and until 90 minutes after exercise termination. IDeg concentrations were quantified using high-resolution mass-spectrometry and analyzed applying generalized estimation equations.

RESULTS

Compared to baseline, systemic IDeg increased during exercise over time (P < .001), with the highest concentrations observed toward the end of the 60-minute exercise (17.9% and 17.6% above baseline after 45 minutes and 60 minutes, respectively). IDeg levels remained elevated until the end of the experiment (14% above baseline at 90 minutes after exercise termination, P < .001).

CONCLUSIONS

A single bout of aerobic exercise increases systemic IDeg exposure in adults on a stable basal IDeg regimen. This finding may have important implications for future hypoglycemia mitigation strategies around physical exercise in IDeg-treated patients.

Modeling the acute effects of exercise on glucose dynamics in healthy nondiabetic subjects

To shed light on how acute exercise affects blood glucose (BG) concentrations in nondiabetic subjects, we develop a physiological pharmacokinetic/pharmacodynamic model of postprandial glucose dynamics during exercise. We unify several concepts of exercise physiology to derive a multiscale model that includes three important effects of exercise on glucose dynamics: increased endogenous glucose production (EGP), increased glucose uptake in skeletal muscle (SM), and increased glucose delivery to SM by capillary recruitment (i.e. an increase in surface area and blood flow in capillary beds). We compare simulations to experimental observations taken in two cohorts of healthy nondiabetic subjects (resting subjects (n = 12) and exercising subjects (n = 12)) who were each given a mixed-meal tolerance test. Metabolic tracers were used to quantify the glucose flux. Simulations reasonably agree with postprandial measurements of BG concentration and EGP during exercise. Exercise-induced capillary recruitment is predicted to increase glucose transport to SM by 100%, causing hypoglycemia. When recruitment is blunted, as in those with capillary dysfunction, the opposite occurs and higher than expected BG levels are predicted. Model simulations show how three important exercise-induced phenomena interact, impacting BG concentrations. This model describes nondiabetic subjects, but it is a first step to a model that describes glucose dynamics during exercise in those with type 1 diabetes (T1D). Clinicians and engineers can use the insights gained from the model simulations to better understand the connection between exercise and glucose dynamics and ultimately help patients with T1D make more informed insulin dosing decisions around exercise.

A single-blind, randomised, crossover study to reduce hypoglycaemia risk during postprandial exercise with closed-loop insulin delivery in adults with type 1 diabetes: announced (with or without bolus reduction) vs unannounced exercise strategies

AIMS/HYPOTHESIS

For individuals living with type 1 diabetes, closed-loop insulin delivery improves glycaemic control. Nonetheless, maintenance of glycaemic control during exercise while a prandial insulin bolus remains active is a challenge even to closed-loop systems. We investigated the effect of exercise announcement on the efficacy of a closed-loop system, to reduce hypoglycaemia during postprandial exercise.

METHODS

A single-blind randomised, crossover open-label trial was carried out to compare three strategies applied to a closed-loop system at mealtime in preparation for exercise taken 90 min after eating at a research testing centre: (1) announced exercise to the closed-loop system (increases target glucose levels) in addition to a 33% reduction in meal bolus (A-RB); (2) announced exercise to the closed-loop system and a full meal bolus (A-FB); (3) unannounced exercise and a full meal bolus (U-FB). Participants performed 60 min of exercise at 60% [Formula: see text] 90 min after eating breakfast. The investigators were not blinded to the interventions. However, the participants were blinded to the sensor glucose readings and to the insulin infusion rates throughout the intervention visits.

RESULTS

The trial was completed by 37 adults with type 1 diabetes, all using insulin pumps: mean±SD, 40.0 ± 15.0 years of age, HbA_1c 57.1 ± 10.8 mmol/mol (7.3 ± 1.0%). Reported results were based on plasma glucose values. During exercise and the following 1 h recovery period, time spent in hypoglycaemia (<3.9 mmol/l; primary outcome) was reduced with A-RB (mean ± SD; 2.0 ± 6.2%) and A-FB (7.0 ± 12.6%) vs U-FB (13.0 ± 19.0%; p < 0.0001 and p = 0.005, respectively). During exercise, A-RB had the least drop in plasma glucose levels: A-RB -0.3 ± 2.8 mmol/l, A-FB -2.6 ± 2.9 mmol/l vs U-FB -2.4 ± 2.7 mmol/l (p < 0.0001 and p = 0.5, respectively). Comparison of A-RB vs U-FB revealed a decrease in the time spent in target (3.9-10 mmol/l) by 12.7% (p = 0.05) and an increase in the time spent in hyperglycaemia (>10 mmol/l) by 21% (p = 0.001). No side effects were reported during the applied strategies.

CONCLUSIONS/INTERPRETATION

Combining postprandial exercise announcement, which increases closed-loop system glucose target levels, with a 33% meal bolus reduction significantly reduced time spent in hypoglycaemia compared with the other two strategies, yet at the expense of more time spent in hyperglycaemia.

TRIAL REGISTRATION

ClinicalTrials.gov NCT0285530 FUNDING: JDRF (2-SRA-2016-210-A-N), the Canadian Institutes of Health Research (354024) and the Fondation J.-A. DeSève chair held by RR-L.

Strength Training and Insulin Resistance: The Mediating Role of Body Composition

The main objective of the present study was to assess the association between participation in strength training and insulin resistance. Another goal was to assess the influence of several potential confounding variables on the strength training and insulin resistance relationship. Lastly, the influence of waist circumference, fat-free mass (kg), body fat percentage, and the fat-free mass index on the association between strength training and insulin resistance was assessed. This cross-sectional study included 6,561 randomly selected men and women in the U.S. Data were collected using the precise protocol established by NHANES. HOMA-IR was used as the outcome variable to index insulin resistance. Both time spent strength training and frequency of strength training bouts were used as exposure variables. There was not a statistically significant relationship between strength training and insulin resistance in women. However, before and after controlling for 11 potential confounding variables, men who reported no strength training had significantly higher levels of HOMA-IR compared to men who reported moderate or high levels of strength training (F = 9.87, P < 0.0001). Odds ratios were also assessed. Men reporting no strength training had 2.42 times the odds of having insulin resistance compared to men reporting moderate levels of strength training (95% CI: 1.19-4.93). Similarly, men reporting no strength training had 2.50 times the odds of having insulin resistance compared to men reporting high levels of strength training (95% CI: 1.25-5.00). In conclusion, there was a strong relationship between strength training and insulin resistance in U.S. men, but not in U.S. women. Differences in waist circumference, fat-free mass (kg), body fat percentage, and the fat-free mass index, as well as demographic and lifestyle measures, do not appear to mediate the relationship. The present study was not a clinical trial.

Carbohydrate Intake in the Context of Exercise in People with Type 1 Diabetes

Although the benefits of regular exercise on cardiovascular risk factors are well established for people with type 1 diabetes (T1D), glycemic control remains a challenge during exercise. Carbohydrate consumption to fuel the exercise bout and/or for hypoglycemia prevention is an important cornerstone to maintain performance and avoid hypoglycemia. The main strategies pertinent to carbohydrate supplementation in the context of exercise cover three aspects: the amount of carbohydrates ingested (i.e., quantity in relation to demands to fuel exercise and avoid hypoglycemia), the timing of the intake (before, during and after the exercise, as well as circadian factors), and the quality of the carbohydrates (encompassing differing carbohydrate types, as well as the context within a meal and the associated macronutrients). The aim of this review is to comprehensively summarize the literature on carbohydrate intake in the context of exercise in people with T1D.