Continuous glucose monitoring reveals delayed nocturnal hypoglycemia after intermittent high-intensity exercise in nontrained patients with type 1 diabetes

Modifiable self-management practices impact nocturnal and morning glycaemia in type 1 diabetes

AIMS

To identify risk factors for nocturnal/morning hypo- and hyperglycaemia in type 1 diabetes.

METHODS

Data on self-management practices were obtained from 3-day records. We studied the associations between self-management practices on the first recording day and the self-reported blood glucose (BG) concentrations on the subsequent night/morning.

RESULTS

Of the 1025 participants (39 % men, median age 45 years), 4.4 % reported nocturnal hypoglycaemia (<3.9 mmol/l), 9.8 % morning hypoglycaemia, 51.5 % morning euglycaemia, and 34.3 % morning hyperglycaemia (≥8.9 mmol/l). Within hypoglycaemic range, insulin pump use was associated with higher nocturnal BG concentration (B=0.486 [95 % Confidence Interval=0.121-0.852], p=0.009). HbA1c was positively (0.046 [0.028-0.065], p<0.001), while antecedent fibre intake (-0.327 [-0.543 - -0.111], p=0.003) and physical activity (PA) (-0.042 [-0.075 - -0.010], p=0.010) were inversely associated with morning BG concentration. The odds of morning hypoglycaemia were increased by previous day hypoglycaemia (OR=2.058, p=0.002) and alcohol intake (1.031, p=0.001). Previous day PA (0.977, p=0.031) and fibre intake (0.848, p=0.017) were inversely, while HbA1c (1.027, p<0.001) was positively associated with the risk of morning hyperglycaemia.

CONCLUSIONS

Alcohol avoidance may prevent nocturnal hypoglycaemia, while PA and fibre intake may reduce hyperglycaemia risk. Avoidance of daytime hypoglycaemia and keeping HbA1c in control may help maintain normoglycaemia also at night-time.

(Hybrid) Closed-Loop Systems: From Announced to Unannounced Exercise

Physical activity and exercise have many beneficial effects on general and type 1 diabetes (T1D) specific health and are recommended for individuals with T1D. Despite these health benefits, many people with T1D still avoid exercise since glycemic management during physical activity poses substantial glycemic and psychological challenges - which hold particularly true for unannounced exercise when using an AID system. Automated insulin delivery (AID) systems have demonstrated their efficacy in improving overall glycemia and in managing announced exercise in numerous studies. They are proven to increase time in range (70-180 mg/dL) and can especially counteract nocturnal hypoglycemia, even when evening exercise was performed. AID-systems consist of a pump administering insulin as well as a CGM sensor (plus transmitter), both communicating with a control algorithm integrated into a device (insulin pump, mobile phone/smart watch). Nevertheless, without manual pre-exercise adaptions, these systems still face a significant challenge around physical activity. Automatically adapting to the rapidly changing insulin requirements during unannounced exercise and physical activity is still the Achilles' heel of current AID systems. There is an urgent need for improving current AID-systems to safely and automatically maintain glucose management without causing derailments - so that going forward, exercise announcements will not be necessary in the future. Therefore, this narrative literature review aimed to discuss technological strategies to how current AID-systems can be improved in the future and become more proficient in overcoming the hurdle of unannounced exercise. For this purpose, the current state-of-the-art therapy recommendations for AID and exercise as well as novel research approaches are presented along with potential future solutions - in order to rectify their deficiencies in the endeavor to achieve fully automated AID-systems even around unannounced exercise.

Association of Smartphone-Based Activity Tracking and Nocturnal Hypoglycemia in People With Type 1 Diabetes

BACKGROUND

Nocturnal hypoglycemia (NH) remains a major burden for people with type 1 diabetes (T1D). Daytime physical activity (PA) increases the risk of NH. This pilot study tested whether cumulative daytime PA measured using a smartphone-based step tracker was associated with NH.

METHODS

Adults with T1D for ≥ 5 years (y) on multiple daily insulin or continuous insulin infusion, not using continuous glucose monitoring and HbA1c 6 to 10% wore blinded Freestyle Libre Pro sensors and recorded total daily carbohydrate (TDC) and total daily dose (TDD) of insulin. During this time, daily step count (DSC) was tracked using the smartphone-based Fitbit MobileTrack application. Mixed effects logistic regression was used to estimate the effect of DSC on NH (sensor glucose <70, <54 mg/dl for ≥15 minutes), while adjusting for TDC and TDD of insulin, and treating participants as a random effect.

RESULTS

Twenty-six adults, with 65.4% females, median age 27 years (interquartile range: 26-32) mean body mass index 23.9 kg/m2, median HbA1c 7.6% (7.1-8.1) and mean Gold Score 2.1 (standard deviation 1.0) formed the study population. The median DSC for the whole group was 2867 (1820-4807). There was a significant effect of DSC on NH episodes <70 mg/dl. (odds ratio 1.11 [95% CI: 1.01-1.23, P = .04]. There was no significant effect on NH <54 mg/dl.

CONCLUSION

Daily PA measured by a smartphone-based step tracker was associated with the risk of NH in people with type 1 diabetes.

Effects of postprandial exercise on blood glucose levels in adults with type 1 diabetes: a review

People with type 1 diabetes experience challenges in managing blood glucose around exercise. Previous studies have examined glycaemic responses to different exercise modalities but paid little attention to participants' prandial state, although this is an important consideration and will enhance our understanding of the effects of exercise in order to improve blood glucose management around activity. This review summarises available data on the glycaemic effects of postprandial exercise (i.e. exercise within 2 h after a meal) in people with type 1 diabetes. Using a search strategy on electronic databases, literature was screened until November 2022 to identify clinical trials evaluating acute (during exercise), subacute (≤2 h after exercise) and late (>2 h to ≤24 h after exercise) effects of postprandial exercise in adults with type 1 diabetes. Studies were systematically organised and assessed by exercise modality: (1) walking exercise (WALK); (2) continuous exercise of moderate intensity (CONT MOD); (3) continuous exercise of high intensity (CONT HIGH); and (4) interval training (intermittent high-intensity exercise [IHE] or high-intensity interval training [HIIT]). Primary outcomes were blood glucose change and hypoglycaemia occurrence during and after exercise. All study details and results per outcome were listed in an evidence table. Twenty eligible articles were included: two included WALK sessions, eight included CONT MOD, seven included CONT HIGH, three included IHE and two included HIIT. All exercise modalities caused consistent acute glycaemic declines, with the largest effect size for CONT HIGH and the smallest for HIIT, depending on the duration and intensity of the exercise bout. Pre-exercise mealtime insulin reductions created higher starting blood glucose levels, thereby protecting against hypoglycaemia, in spite of similar declines in blood glucose during activity between the different insulin reduction strategies. Nocturnal hypoglycaemia occurred after higher intensity postprandial exercise, a risk that could be diminished by a post-exercise snack with concomitant bolus insulin reduction. Research on the optimal timing of postprandial exercise is inconclusive. In summary, individuals with type 1 diabetes exercising postprandially should substantially reduce insulin with the pre-exercise meal to avoid exercise-induced hypoglycaemia, with the magnitude of the reduction depending on the exercise duration and intensity. Importantly, pre-exercise blood glucose and timing of exercise should be considered to avoid hyperglycaemia around exercise. To protect against late-onset hypoglycaemia, a post-exercise meal with insulin adjustments might be advisable, especially for exercise in the evening or with a high-intensity component.

Practical Aspects and Exercise Safety Benefits of Automated Insulin Delivery Systems in Type 1 Diabetes

Regular exercise is essential to overall cardiovascular health and well-being in people with type 1 diabetes, but exercise can also lead to increased glycemic disturbances. Automated insulin delivery (AID) technology has been shown to modestly improve glycemic time in range (TIR) in adults with type 1 diabetes and significantly improve TIR in youth with type 1 diabetes. Available AID systems still require some user-initiated changes to the settings and, in some cases, significant pre-planning for exercise. Many exercise recommendations for type 1 diabetes were developed initially for people using multiple daily insulin injections or insulin pump therapy. This article highlights recommendations and practical strategies for using AID around exercise in type 1 diabetes.

Modeling risk of hypoglycemia during and following physical activity in people with type 1 diabetes using explainable mixed-effects machine learning

BACKGROUND

Physical activity (PA) can cause increased hypoglycemia (glucose <70 mg/dL) risk in people with type 1 diabetes (T1D). We modeled the probability of hypoglycemia during and up to 24 h following PA and identified key factors associated with hypoglycemia risk.

METHODS

We leveraged a free-living dataset from Tidepool comprised of glucose measurements, insulin doses, and PA data from 50 individuals with T1D (6448 sessions) for training and validating machine learning models. We also used data from the T1Dexi pilot study that contains glucose management and PA data from 20 individuals with T1D (139 session) for assessing the accuracy of the best performing model on an independent test dataset. We used mixed-effects logistic regression (MELR) and mixed-effects random forest (MERF) to model hypoglycemia risk around PA. We identified risk factors associated with hypoglycemia using odds ratio and partial dependence analysis for the MELR and MERF models, respectively. Prediction accuracy was measured using the area under the receiver operating characteristic curve (AUROC).

RESULTS

The analysis identified risk factors significantly associated with hypoglycemia during and following PA in both MELR and MERF models including glucose and body exposure to insulin at the start of PA, low blood glucose index 24 h prior to PA, and PA intensity and timing. Both models showed overall hypoglycemia risk peaking 1 h after PA and again 5-10 h after PA, which is consistent with the hypoglycemia risk pattern observed in the training dataset. Time following PA impacted hypoglycemia risk differently across different PA types. Accuracy of hypoglycemia prediction using the fixed effects of the MERF model was highest when predicting hypoglycemia during the first hour following the start of PA (AUROCVALIDATION = 0.83 and AUROCTESTING = 0.86) and decreased when predicting hypoglycemia in the 24 h after PA (AUROCVALIDATION = 0.66 and AUROCTESTING = 0.68).

CONCLUSION

Hypoglycemia risk after the start of PA can be modeled using mixed-effects machine learning to identify key risk factors that may be used within decision support and insulin delivery systems. We published the population-level MERF model online for others to use.

New model of glucose-insulin regulation characterizes effects of physical activity and facilitates personalized treatment evaluation in children and adults with type 1 diabetes

Accurate treatment adjustment to physical activity (PA) remains a challenging problem in type 1 diabetes (T1D) management. Exercise-driven effects on glucose metabolism depend strongly on duration and intensity of the activity, and are highly variable between patients. In-silico evaluation can support the development of improved treatment strategies, and can facilitate personalized treatment optimization. This requires models of the glucose-insulin system that capture relevant exercise-related processes. We developed a model of glucose-insulin regulation that describes changes in glucose metabolism for aerobic moderate- to high-intensity PA of short and prolonged duration. In particular, we incorporated the insulin-independent increase in glucose uptake and production, including glycogen depletion, and the prolonged rise in insulin sensitivity. The model further includes meal absorption and insulin kinetics, allowing simulation of everyday scenarios. The model accurately predicts glucose dynamics for varying PA scenarios in a range of independent validation data sets, and full-day simulations with PA of different timing, duration and intensity agree with clinical observations. We personalized the model on data from a multi-day free-living study of children with T1D by adjusting a small number of model parameters to each child. To assess the use of the personalized models for individual treatment evaluation, we compared subject-specific treatment options for PA management in replay simulations of the recorded data with altered meal, insulin and PA inputs.

Exercise in adults with type 1 diabetes mellitus

Regular physical activity improves cardiometabolic and musculoskeletal health, helps with weight management, improves cognitive and psychosocial functioning, and is associated with reduced mortality related to cancer and diabetes mellitus. However, turnover rates of glucose in the blood increase dramatically during exercise, which often results in either hypoglycaemia or hyperglycaemia as well as increased glycaemic variability in individuals with type 1 diabetes mellitus (T1DM). A complex neuroendocrine response to an acute exercise session helps to maintain circulating levels of glucose in a fairly tight range in healthy individuals, while several abnormal physiological processes and limitations of insulin therapy limit the capacity of people with T1DM to exercise in a normoglycaemic state. Knowledge of the acute and chronic effects of exercise and regular physical activity is critical for the formulation of clinical strategies for the management of insulin and nutrition for active patients with T1DM. Emerging diabetes-related technologies, such as continuous glucose monitors, automated insulin delivery systems and the administration of solubilized glucagon, are demonstrating efficacy for preserving glucose homeostasis during and after exercise in this population of patients. This Review highlights the beneficial effects of regular exercise and details the complex endocrine and metabolic responses to different types of exercise for adults with T1DM. An overview of basic clinical strategies for the preservation of glucose homeostasis using emerging technologies is also provided.

Reassessing the evidence: prandial state dictates glycaemic responses to exercise in individuals with type 1 diabetes to a greater extent than intensity

Recent guidelines suggest that adding anaerobic (high intensity or resistance) activity to an exercise session can prevent blood glucose declines that occur during aerobic exercise in individuals with type 1 diabetes. This theory evolved from earlier study data showing that sustained, anaerobic activity (high intensity cycling) increases blood glucose levels in these participants. However, studies involving protocols where anaerobic (high intensity interval) and aerobic exercise are combined have extremely variable glycaemic outcomes, as do resistance exercise studies. Scrutinising earlier studies will reveal that, in addition to high intensity activity (intervals or weight lifting), these protocols had another common feature: participants were performing exercise after an overnight fast. Based on these findings, and data from recent exercise studies, it can be argued that participant prandial state may be a more dominant factor than exercise intensity where glycaemic changes in individuals with type 1 diabetes are concerned. As such, a reassessment of study outcomes and an update to exercise recommendations for those with type 1 diabetes may be warranted.

Continuous Glucose Monitoring and Physical Activity

Continuous glucose monitoring (CGM) use has several potential positive effects on diabetes management. These benefits are, e.g., increased time in range (TIR), optimized therapy, and developed documentation. Physical activity is a recommended intervention tool in diabetes management, especially for people with type 2 diabetes (T2D). The benefits of physical activity for people with diabetes can be seen as an improvement of glycemic control, glycemic variability, and the reduction of insulin resistance. In relation to the physical activity of people with T2D, the benefits of CGM use can even be increased, and CGM can be a helpful tool to prevent adverse events due to physical activity of people with diabetes, such as hypoglycemic events and nocturnal hypoglycemia after sports. This narrative review aims to provide solid recommendations for the use of CGM in everyday life physical activities based on the noted benefits and to give a general overview of the guidelines on physical activity and CGM use for people with diabetes.

Trends of glucose, lactate and ketones during anaerobic and aerobic exercise in subjects with type 1 diabetes: The ACTION-1 study

BACKGROUND

Exercise is part of type 1 diabetes (T1D) management due to its cardiovascular and metabolic benefits. However, despite using continuous glucose monitoring, many patients are reluctant to exercise because of fear for hypoglycaemia.

AIMS

We assessed trends in glucose, lactate and ketones during anaerobic and aerobic exercise in people with T1D and compared incremental area under the curve (AUC) between both exercises.

METHODS

Twenty-one men with T1D (median [IQR]: age 29 years [28-38], body mass index (BMI) 24.4 kg/m² [22.3-24.9], HbA1c 7.2% [6.7-7.8]), completed a cardiopulmonary exercise test (CPET) and a 60-min aerobic exercise (AEX) at 60% VO₂ peak on an ergometer bicycle within a 6-week period. Subjects consumed a standardised breakfast (6 kcal/kg, 20.2 g CHO/100 ml) before exercise without pre-meal insulin and basal insulin for pump users.

RESULTS

During CPET, glucose levels increased, peaking at 331 mg/dl [257-392] 1-3 h after exercise and reaching a nadir 6 h after exercise at 176 mg/dl [118-217]. Lactate levels peaked at 6.0 mmol/L [5.0-6.6] (max 13.5 mmol/L). During AEX, glucose levels also increased, peaking at 305 mg/dl [245-336] 80 min after exercise and reaching a nadir 6 h after exercise at 211 mg/dl [116-222]. Lactate levels rose quickly to a median of 4.3 mmol/L [2.7-6.7] after 10 min. Ketone levels were low during both tests (median ≤ 0.2 mmol/L). Lactate, but not glucose or ketone AUC, was significantly higher in CPET compared to AEX (p = 0.04).

CONCLUSIONS

Omitting pre-meal insulin and also basal insulin in pump users, did prevent hypoglycaemia but induced hyperglycaemia due to a too high carbohydrate ingestion. No ketosis was recorded during or after the exercises.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov: NCT05097339.

Protective effects of physical activity against health risks associated with type 1 diabetes: “Health benefits outweigh the risks”

The magnitude of diabetes mellitus (DM) has increased in recent decades, where the number of cases and the proportion of the disease have been gradually increasing over the past few decades. The chronic complications of DM affect many organ systems and account for the majority of morbidity and mortality associated with the disease. The prevalence of type 1 DM (T1DM) is increasing globally, and it has a very significant burden on countries and at an individual level. T1DM is a chronic illness that requires ongoing medical care and patient self-management to prevent complications. This study aims to discuss the health benefits of physical activity (PA) in T1DM patients. The present review article was performed following a comprehensive literature search. The search was conducted using the following electronic databases: “Cochrane Library”, Web of Science, PubMed, HINARI, EMBASE, Google for grey literature, Scopus, African journals Online, and Google Scholar for articles published up to June 21, 2021. The present review focused on the effects of PA on many outcomes such as blood glucose (BG) control, physical fitness, endothelial function, insulin sensitivity, well-being, the body defense system, blood lipid profile, insulin resistance, cardiovascular diseases (CVDs), insulin requirements, blood pressure (BP), and mortality. It was found that many studies recommended the use of PA for the effective management of T1DM. PA is a component of comprehensive lifestyle modifications, which is a significant approach for the management of T1DM. It provides several health benefits, such as improving BG control, physical fitness, endothelial function, insulin sensitivity, well-being, and the body defense system. Besides this, it reduces the blood lipid profile, insulin resistance, CVDs, insulin requirements, BP, and mortality. Overall, PA has significant and essential protective effects against the health risks associated with T1DM. Even though PA has several health benefits for patients with T1DM, these patients are not well engaged in PA due to barriers such as a fear of exercise-induced hypoglycemia in particular. However, several effective strategies have been identified to control exercise-induced hypoglycemia in these patients. Finally, the present review concludes that PA should be recommended for the management of patients with T1DM due to its significant health benefits and protective effects against associated health risks. It also provides suggestions for the future direction of research in this field.

Influence of Insulin Application Time and High-Intensity Intermittent Exercise on Hypoglycemic Risk in Adolescents With Type 1 Diabetes

PURPOSE

The study analyzed the influence of exercise on hypoglycemia episodes postexercise and in the subsequent 24 hours in children and adolescents with type 1 diabetes.

METHODS

Thirty young people performed the same protocol of physical exercises for 1 hour (Ex1h) and 2 hours (Ex2h) after the administration of insulin. They performed 30 minutes of exercise on a cycle ergometer with a load of 60% of maximal oxygen uptake, interspersed with maximum intensity sprints lasting 10 seconds every 5 minutes.

RESULTS

Regarding the occurrence of hypoglycemia, in the 8 hours following the exercises, there was no occurrence in Ex1h (χ2 = 0.001; P = .0001) and a greater proportion for Ex2h (n = 71 episodes, 53.8%), while Ex1h had a higher number of nocturnal hypoglycemic episodes (n = 60, 71.4%) compared with Ex2h (n = 31, 23.1%, χ2 = 49.521, P = .0001), Ex1h triggered a lower number of hypoglycemia (n = 84) than Ex2h (n = 134, χ2 = 11.504, P = .001). There was a greater reduction in the average amount of fast-acting insulin administered the day after Ex1h compared with Ex2h (P = .031).

CONCLUSIONS

Intermittent exercise performed 1 hour after insulin administration shows a lower risk of hypoglycemia within 8 hours after exercise, as well as a reduction in insulin the following day.

Prevalence of nocturnal hypoglycemia in free-living conditions in adults with type 1 diabetes: What is the impact of daily physical activity?

OBJECTIVE

Studies investigating strategies to limit the risk of nocturnal hypoglycemia associated with physical activity (PA) are scarce and have been conducted in standardized, controlled conditions in people with type 1 diabetes (T1D). This study sought to investigate the effect of daily PA level on nocturnal glucose management in free-living conditions while taking into consideration reported mitigation strategies to limit the risk of nocturnal hyoglycemia in people with T1D.

METHODS

Data from 25 adults (10 males, 15 females, HbA_1c: 7.6 ± 0.8%), 20-60 years old, living with T1D, were collected. One week of continuous glucose monitoring and PA (assessed using an accelerometer) were collected in free-living conditions. Nocturnal glucose values (midnight-6:00 am) following an active day "ACT" and a less active day "L-ACT" were analyzed to assess the time spent within the different glycemic target zones (<3.9 mmol/L; 3.9 - 10.0 mmol/L and >10.0 mmol/L) between conditions. Self-reported data about mitigation strategies applied to reduce the risk of nocturnal hypoglycemia was also analyzed.

RESULTS

Only 44% of participants reported applying a carbohydrate- or insulin-based strategy to limit the risk of nocturnal hypoglycemia on ACT day. Nocturnal hypoglycemia occurrences were comparable on ACT night versus on L-ACT night. Additional post-meal carbohydrate intake was higher on evenings following ACT (27.7 ± 15.6 g, ACT vs. 19.5 ± 11.0 g, L-ACT; P=0.045), but was frequently associated with an insulin bolus (70% of participants). Nocturnal hypoglycemia the night following ACT occurred mostly in people who administrated an additional insulin bolus before midnight (3 out of 5 participants with nocturnal hypoglycemia).

CONCLUSIONS

Although people with T1D seem to be aware of the increased risk of nocturnal hypoglycemia associated with PA, the risk associated with additional insulin boluses may not be as clear. Most participants did not report using compensation strategies to reduce the risk of PA related late-onset hypoglycemia which may be because they did not consider habitual PA as something requiring treatment adjustments.

Nocturnal hypoglycemia in type 1 and type 2 diabetes: an update on prevalence, prevention, pathophysiology and patient awareness

INTRODUCTION

Despite considerable progress in diabetes treatment, prevalence of nocturnal hypoglycemia in type 1 diabetes mellitus (T1DM) and advanced insulin treated type 2 diabetes mellitus (T2DM) remains high.

AREAS COVERED

The present manuscript describes the prevalence of night-time hypoglycemia as reported in observational and randomized controlled trials. Factors that affect the risk of hypoglycemia are highlighted. The authors also describe impaired awareness of hypoglycemia and available preventive methods.

EXPERT OPINION

Prevention of nocturnal hypoglycemia includes behavioral, dietary and pharmacologic interventions. The most recent development with the lowest rate of hypoglycemia is sensor-augmented pumps with predictive low glucose suspend technology. These pumps combine continuous subcutaneous insulin infusion with continuous glucose monitoring and use various algorithms to predict and stop hypoglycemia before it develops.

More Time in Glucose Range During Exercise Days than Sedentary Days in Adults Living with Type 1 Diabetes

Objective: This study analysis was designed to examine the 24-h effects of exercise on glycemic control as measured by continuous glucose monitoring (CGM). Methods: Individuals with type 1 diabetes (ages: 15-68 years; hemoglobin A1c: 7.5% ± 1.5% [mean ± standard deviation (SD)]) were randomly assigned to complete twice-weekly aerobic, high-intensity interval, or resistance-based exercise sessions in addition to their personal exercise sessions for a period of 4 weeks. Exercise was tracked with wearables and glucose concentrations assessed using CGM. An exercise day was defined as a 24-h period after the end of exercise, while a sedentary day was defined as any 24-h period with no recorded exercise ≥10 min long. Sedentary days start at least 24 h after the end of exercise. Results: Mean glucose was lower (150 ± 45 vs. 166 ± 49 mg/dL, P = 0.01), % time in range [70-180 mg/dL] higher (62% ± 23% vs. 56% ± 25%, P = 0.03), % time >180 mg/dL lower (28% ± 23% vs. 37% ± 26%, P = 0.01), and % time <70 mg/dL higher (9.3% ± 11.0% vs. 7.1% ± 9.1%, P = 0.04) on exercise days compared with sedentary days. Glucose variability and % time <54 mg/dL did not differ significantly between exercise and sedentary days. No significant differences in glucose control by exercise type were observed. Conclusion: Participants had lower 24-h mean glucose levels and a greater time in range on exercise days compared with sedentary days, with mode of exercise affecting glycemia similarly. In summary, this study offers data supporting frequency of exercise as a method of facilitating glucose control but does not suggest an effect for mode of exercise.

Post-exercise recovery for the endurance athlete with type 1 diabetes: a consensus statement

There has been substantial progress in the knowledge of exercise and type 1 diabetes, with the development of guidelines for optimal glucose management. In addition, an increasing number of people living with type 1 diabetes are pushing their physical limits to compete at the highest level of sport. However, the post-exercise recovery routine, particularly with a focus on sporting performance, has received little attention within the scientific literature, with most of the focus being placed on insulin or nutritional adaptations to manage glycaemia before and during the exercise bout. The post-exercise recovery period presents an opportunity for maximising training adaption and recovery, and the clinical management of glycaemia through the rest of the day and overnight. The absence of clear guidance for the post-exercise period means that people with type 1 diabetes should either develop their own recovery strategies on the basis of individual trial and error, or adhere to guidelines that have been developed for people without diabetes. This Review provides an up-to-date consensus on post-exercise recovery and glucose management for individuals living with type 1 diabetes. We aim to: (1) outline the principles and time course of post-exercise recovery, highlighting the implications and challenges for endurance athletes living with type 1 diabetes; (2) provide an overview of potential strategies for post-exercise recovery that could be used by athletes with type 1 diabetes to optimise recovery and adaptation, alongside improved glycaemic monitoring and management; and (3) highlight the potential for technology to ease the burden of managing glycaemia in the post-exercise recovery period.

Delayed effect of different exercise modalities on glycaemic control in type 1 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND AND AIMS

Despite the crucial role of exercise in the prevention of comorbidities and complications in type 1 diabetes mellitus (T1DM), people living with the disease are often insufficiently physically active, mainly due to the fear of hypoglycaemia. Research using continuous glucose monitoring (CGM) devices has shown that exercise affects glycaemic control in T1DM for over 24 h. The aim of this systematic review and meta-analysis is, therefore, to investigate the delayed effects of different exercise modalities on glycaemic control in adults with T1DM.

METHODS AND RESULTS

The literature search of experimental studies was conducted on PubMed, SPORTDiscus and EMBASE from January 2000 to September 2019. Twelve studies using CGM devices were included. Compared to endurance, intermittent exercise increased the time spent in hypoglycaemia (0.62, 0.07 to 1.18; standardised effect size, 95% CI) and reduced the mean interstitial glucose concentration (-0.88, -1.45 to -0.33). No differences emerged in the time spent in hyperglycaemia (-0.07, -0.58 to 0.45) or in the proportion of exercisers experiencing hypoglycaemic events (0.82, 0.45 to 1.49; proportion ratio, 95% CI) between conditions. The systematic review also found a reduced risk of hypoglycaemia if exercise is performed in the morning rather than in the afternoon, and with a 50% rapid-acting insulin reduction. It was not possible to determine the benefits of resistance exercise.

CONCLUSIONS

For the first time, we systematically investigated the delayed effect of exercise in adults with T1DM, highlighted undetected effects, shortcomings in the existing literature, and provided suggestions to design future comparable studies.

Extent and prevalence of post-exercise and nocturnal hypoglycemia following peri-exercise bolus insulin adjustments in individuals with type 1 diabetes

AIM

To detail the extent and prevalence of post-exercise and nocturnal hypoglycemia following peri-exercise bolus insulin dose adjustments in individuals with type 1 diabetes (T1D) using multiple daily injections of insulins aspart (IAsp) and degludec (IDeg).

METHODS AND RESULTS

Sixteen individuals with T1D, completed a single-centred, randomised, four-period crossover trial consisting of 23-h inpatient phases. Participants administered either a regular (100%) or reduced (50%) dose (100%; 5.1 ± 2.4, 50%; 2.6 ± 1.2 IU, p < 0.001) of individualised IAsp 1 h before and after 45-min of evening exercise at 60 ± 6% V̇O_2max. An unaltered dose of IDeg was administered in the morning. Metabolic, physiological and hormonal responses during exercise, recovery and nocturnal periods were characterised. The primary outcome was the number of trial day occurrences of hypoglycemia (venous blood glucose ≤ 3.9 mmol L ^-1). Inclusion of a 50% IAsp dose reduction strategy prior to evening exercise reduced the occurrence of in-exercise hypoglycemia (p = 0.023). Mimicking this reductive strategy in the post-exercise period decreased risk of nocturnal hypoglycemia (p = 0.045). Combining this strategy to reflect reductions either side of exercise resulted in higher glucose concentrations in the acute post-exercise (p = 0.034), nocturnal (p = 0.001), and overall (p < 0.001) periods. Depth of hypoglycemia (p = 0.302), as well as ketonic and counter-regulatory hormonal profiles were similar.

CONCLUSIONS

These findings demonstrate the glycemic safety of peri-exercise bolus dose reduction strategies in minimising the prevalence of acute and nocturnal hypoglycemia following evening exercise in people with T1D on MDI. Use of newer background insulins with current bolus insulins demonstrates efficacy and advances current recommendations for safe performance of exercise.

CLINICAL TRIALS REGISTER

DRKS00013509.

Reproducibility of Glucose Fluctuations Induced by Moderate Intensity Cycling Exercise in Persons with Type 1 Diabetes

AIMS

The purpose was to assess the reproducibility of glucose changes during three sessions of standardized moderate intensity continuous training of cycling on an individual level in people with type 1 diabetes.

METHODS

Twelve adults (six females) with type 1 diabetes performed three test sessions on an ergometer bicycle (30 min, 67% of predicted heart rate) on three different days. The participants were 36.5 (26.6-45.5) (median, IQR) years old, and their HbA1c was 65 ± 15 mmol/mol (mean ± SD). Two hours before the tests, the participants had a standard meal. Interstitial glucose (IG) and capillary glucose (CG) were measured using an iPro2 Medtronic continuous glucose monitor and the Bayer Contour XT-device, respectively. Prior to the test sessions, resting heart rate was measured using a digital blood pressure monitor to estimate the desired intensity of the exercise.

RESULTS

The average within-participant relationship between the average slope in glucose during sessions 2 and 1 was in IG -0.29 (95% CI -1.11; 0.58) and in CG -0.04 (-0.68; 0.77). Between sessions 3 and 2, IG is 0.18 (-0.27; 0.64) and in CG 0.13 (-0.25; 0.55). Between sessions 3 and 1, IG was 0.06 (-0.57; 0.71) and in CG 0.06 (-0.39; 0.52). The results indicate low reproducibility at participant levels and remained unchanged after adjustment for baseline glucose values.

CONCLUSION

On an individual level, the glucose declines during three standardized sessions of PA were not associated with identical responses of the measured IG and CG levels. An overall anticipated decline of glucose concentrations was found in the moderate intensity cycling sessions. This highlights the importance of regular CG measurements during and after physical activity and awareness towards potential exercise-induced hypoglycemia in persons with type 1 diabetes.

Weight Management in Youth with Type 1 Diabetes and Obesity: Challenges and Possible Solutions

PURPOSE OF REVIEW

This review highlights challenges associated with weight management in children and adolescents with type 1 diabetes (T1D). Our purpose is to propose potential solutions to improve weight outcomes in youth with T1D.

RECENT FINDINGS

A common barrier to weight management in T1D is reluctance to engage in exercise for fear of hypoglycemia. Healthcare practitioners generally provide limited guidance for insulin dosing and carbohydrate modifications to maintain stable glycemia during exercise. Adherence to dietary guidelines is associated with improved glycemia; however, youth struggle to meet recommendations. When psychosocial factors are addressed in combination with glucose trends, this often leads to successful T1D management. Newer medications also hold promise to potentially aid in glycemia and weight management, but further research is necessary. Properly addressing physical activity, nutrition, pharmacotherapy, and psychosocial factors while emphasizing weight management may reduce the likelihood of obesity development and its perpetuation in this population.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (i.e. before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes. Graphical abstract.

Glucose management for exercise using continuous glucose monitoring (CGM) and intermittently scanned CGM (isCGM) systems in type 1 diabetes: position statement of the European Association for the Study of Diabetes (EASD) and of the International Society for Pediatric and Adolescent Diabetes (ISPAD) endorsed by JDRF and supported by the American Diabetes Association (ADA)

Physical exercise is an important component in the management of type 1 diabetes across the lifespan. Yet, acute exercise increases the risk of dysglycaemia, and the direction of glycaemic excursions depends, to some extent, on the intensity and duration of the type of exercise. Understandably, fear of hypoglycaemia is one of the strongest barriers to incorporating exercise into daily life. Risk of hypoglycaemia during and after exercise can be lowered when insulin-dose adjustments are made and/or additional carbohydrates are consumed. Glycaemic management during exercise has been made easier with continuous glucose monitoring (CGM) and intermittently scanned continuous glucose monitoring (isCGM) systems; however, because of the complexity of CGM and isCGM systems, both individuals with type 1 diabetes and their healthcare professionals may struggle with the interpretation of given information to maximise the technological potential for effective use around exercise (ie, before, during and after). This position statement highlights the recent advancements in CGM and isCGM technology, with a focus on the evidence base for their efficacy to sense glucose around exercise and adaptations in the use of these emerging tools, and updates the guidance for exercise in adults, children and adolescents with type 1 diabetes.

Type 1 Diabetes and Physical Exercise: Moving (forward) as an Adjuvant Therapy

Type 1 diabetes is characterized by an autoimmune β-cell destruction resulting in endogenous insulin deficiency, potentially leading to micro- and macrovascular complications. Besides an exogenous insulin therapy and continuous glucose monitoring, physical exercise is recommended in adults with type 1 diabetes to improve overall health. The close relationship between physical exercise, inflammation, muscle contraction, and macronutrient intake has never been discussed in detail about type 1 diabetes. The aim of this narrative review was to detail the role of physical exercise in improving clinical outcomes, physiological responses to exercise and different nutrition and therapy strategies around exercise. Physical exercise has several positive effects on glucose uptake and systemic inflammation in adults with type 1 diabetes. A new approach via personalized therapy adaptations must be applied to target beneficial effects on complications as well as on body weight management. In combination with pre-defined macronutrient intake around exercise, adults with type 1 diabetes can expect similar physiological responses to physical exercise, as seen in their healthy counterparts. This review highlights interesting findings from recent studies related to exercise and type 1 diabetes. However, there is limited research available accompanied by a proper number of participants in the cohort of type 1 diabetes. Especially for this group of patients, an increased understanding of the impact of physical exercise can improve its effectiveness as an adjuvant therapy to move (forward).

Hypoglycaemia and its management in primary care setting

Hypoglycaemia is common in patients with type 1 diabetes and type 2 diabetes and constitutes a major limiting factor in achieving glycaemic control among people with diabetes. While hypoglycaemia is defined as a blood glucose level under 70 mg/dL (3.9 mmol/L), symptoms may occur at higher blood glucose levels in individuals with poor glycaemic control. Severe hypoglycaemia is defined as an episode requiring the assistance of another person to actively administer carbohydrate, glucagon, or take other corrective actions to assure neurologic recovery. Hypoglycaemia is the most important safety outcome in clinical studies of glucose lowering agents. The American Diabetes Association Standards of Medical Care recommends that a management protocol for hypoglycaemia should be designed and implemented by every hospital, along with a clear prevention and treatment plan. A tailored approach, using clinical and pathophysiologic disease stratification, can help individualize glycaemic goals and promote new therapies to improve quality of life of patients. Data from recent large clinical trials reported low risk of hypoglycaemic events with the use of newer anti-diabetic drugs. Increased hypoglycaemia risk is observed with the use of insulin and/or sulphonylureas. Vulnerable patients with T2D at dual risk of severe hypoglycaemia and cardiovascular outcomes show features of "frailty." Many of such patients may be better treated by the use of GLP-1 receptor agonists or SGLT2 inhibitors rather than insulin. Continuous glucose monitoring (CGM) should be considered for all individuals with increased risk for hypoglycaemia, impaired hypoglycaemia awareness, frequent nocturnal hypoglycaemia and with history of severe hypoglycaemia. Patients with impaired awareness of hypoglycaemia benefit from real-time CGM. The diabetes educator is an invaluable resource and can devote the time needed to thoroughly educate the individual to reduce the risk of hypoglycaemia and integrate the information within the entire construct of diabetes self-management. Conversations about hypoglycaemia facilitated by a healthcare professional may reduce the burden and fear of hypoglycaemia among patients with diabetes and their family members. Optimizing insulin doses and carbohydrate intake, in addition to a short warm up before or after the physical activity sessions may help avoiding hypoglycaemia. Several therapeutic considerations are important to reduce hypoglycaemia risk during pregnancy including administration of rapid-acting insulin analogues rather than human insulin, pre-conception initiation of insulin analogues, and immediate postpartum insulin dose reduction.

Impact of Daily Physical Activity as Measured by Commonly Available Wearables on Mealtime Glucose Control in Type 1 Diabetes

Objective: In contrast with exercise, or structured physical activity (PA), glycemic disturbances due to daily unstructured PA in patients with type 1 diabetes (T1D) is largely underresearched, with limited information on treatment recommendations. We present results from retrospective analysis of data collected under patients' free-living conditions that illuminate the association between PA, as measured by an off-the-shelf activity tracker, and postprandial blood glucose control. Research Design and Methods: Data from 37 patients with T1D during two clinical studies with identical data collection protocols were analyzed retrospectively: 4 weeks of continuous glucose monitoring, carbohydrate intake, insulin injections, and PA (assessed through wearable activity tracker) were collected in free-living conditions. Five-hour glucose area under curves (GAUCs) following the last-bolused meal of every day were computed to assess postprandial glucose excursions, and their relation with corresponding antecedent PA was analyzed using linear mixed-effects regression models, accounting for meal, insulin, and current glycemic state. Results: Datasets yielded 845 days of data from 37 subjects (22.8 ± 11.6 days/subject); postmeal GAUC was negatively associated with total daily PA measured by step count (P = 0.025), and total time spent performing higher than light-intensity PA (P = 0.042). Patients with higher median total daily PA exhibited lower average postprandial GAUC (P < 0.01). Additional analyses indicated that daily PA likely presents an immediate and delayed impact on glucose control. Conclusion: Daily PA assessed by commonly available sensors is significantly associated with glycemic exposure after an evening meal, indicating that quantitative assessment of PA may be useful in mealtime treatment decisions.

Fasting May Alter Blood Glucose Responses to High-Intensity Interval Exercise in Adults With Type 1 Diabetes: A Randomized, Acute Crossover Study

OBJECTIVES

In individuals with type 1 diabetes (T1D), changes in blood glucose (BG) during high-intensity interval exercise (HIIE) are smaller than those observed during aerobic exercise. Study outcomes, however, have been variable, with some demonstrating significant BG decreases and others showing BG increases. This study compared BG outcomes between fasting (AME) and postprandial (PME) HIIE in T1D to test the hypothesis that AME would produce a BG increase, yet PME would cause BG to decline.

METHODS

Twelve (6 men and 6 women) physically active individuals with T1D performed two 45-minute exercise sessions (AME at 7:00 AM, PME at 5:00 PM) in random order, separated by at least 48 hours. Sessions consisted of a 10-minute warmup (50%VO_2peak), followed by 10-second sprints every 2 minutes for 24 minutes, and then an 11-minute cooldown. Capillary glucose was measured pre- and postexercise, and then 60 minutes postexercise. Interstitial glucose was recorded for 24 hours postexercise using continuous glucose monitoring.

RESULTS

AME caused capillary glucose to increase (from 7.6±1.4 to 9.2±2.9 mmol/L during exercise, and 9.9±2.8 mmol/L in recovery), whereas PME produced a decline in capillary glucose (from 9.9±3.1 to 9.5±3.4 mmol/L during exercise and 8.9±2.7 mmol/L during recovery; time × treatment interaction, p=0.014). PME was associated with a higher frequency of hyperglycemic events in the 6 hours and overnight (midnight to 6:00 AM) after exercise.

CONCLUSIONS

Fasting HIIE results in a different BG trajectory than postprandial exercise in T1D, and may be beneficial for hypoglycemia avoidance during exercise.

Improved glycaemic variability and basal insulin dose reduction during a running competition in recreationally active adults with type 1 diabetes-A single-centre, prospective, controlled observational study

INTRODUCTION

To investigate the glycaemic response, macronutrient intake and insulin management in people with type 1 diabetes (T1D) compared to healthy individuals around a running competition.

MATERIAL AND METHODS

This was a single-centre, prospective, controlled observational study performed in individuals with T1D and healthy people. 24 people (12 T1D) were included in this study (age: T1D 41±12 vs. healthy 38±6 years, females: 3 vs. 6, BMI: 25.53.0 vs. 22.9±2.8 kg/m2). Both groups received an intermittently scanned continuous glucose monitoring (isCGM; FreeStyle Libre 1, Abbott, USA) system to assess glycaemia 24 hours before, during and 24 hours after a running competition. During this period, participants recorded their food intake and insulin administration. Data were analysed via ANOVA and mixed model analyses with post-hoc testing (p≤0.05).

RESULTS

For overall glycaemic ranges in comparison of groups, significant differences were found for time in range (T1D 63±21% vs. healthy 89±13%, p = 0.001), time above range (TAR) 1 (T1D 21±15% vs. healthy 0±0%, p<0.001) and TAR 2 (T1D 8 [0-16%] vs. healthy 0±0%, p<0.001). When glycaemic variability was assessed, people with T1D had a higher glycaemic variability compared to healthy individuals (p<0.0001). Basal insulin dose was significantly reduced when compared against the regular pre-study basal insulin dose (pre-study 22±6 vs. pre-competition day 11±9 (-50±41%), p = 0.02; competition day 15±5 (-32± 1%)).

CONCLUSION

People with T1D have impaired glucose responses around a running competition compared to healthy individuals. However, basal insulin dose reductions were sufficient to prevent further dysglycaemia.

CLINICAL TRIAL ID

drks.de; DRKS00019886.

Five Evidence-Based Lifestyle Habits People With Diabetes Can Use

Several evidence-based lifestyle habits focusing on the composition, timing, and sequence of meals and on pre- and postmeal exercise can improve diabetes management. Consuming low-carbohydrate, balanced meals and eating most carbohydrates early in the day are helpful habits. Eating the protein and vegetable components of a meal first and consuming the carbohydrates 30 minutes later can moderate glucose levels. Postmeal glucose surges can be blunted without precipitating hypoglycemia with moderate exercise 30-60 minutes before the anticipated peak. Short-duration, high-intensity exercise could also be effective. Premeal exercise can improve insulin sensitivity but can also cause post-exertion glucose elevations. Moreover, high-intensity premeal exercise may precipitate delayed hypoglycemia in some people. Glycemia benefits can be enhanced by eating a light, balanced breakfast after premeal exercise.

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

OBJECTIVE

Insulin dosing in type 1 diabetes (T1D) is oftentimes complicated by fluctuating insulin requirements driven by metabolic and psychobehavioral factors impacting individuals' insulin sensitivity (IS). In this context, smart bolus calculators that automatically tailor prandial insulin dosing to the metabolic state of a person can improve glucose management in T1D.

RESEARCH DESIGN AND METHODS

Fifteen adults with T1D using continuous glucose monitors (CGMs) and insulin pumps completed two 24-h admissions in a hotel setting. During the admissions, participants engaged in an early afternoon 45-min aerobic exercise session, after which they received a standardized dinner meal. The dinner bolus was computed using a standard bolus calculator or smart bolus calculator informed by real-time IS estimates. Glucose control was assessed in the 4 h following dinner using CGMs and was compared between the two admissions.

RESULTS

The IS-informed bolus calculator allowed for a reduction in postprandial hypoglycemia as quantified by the low blood glucose index (2.02 vs. 3.31, P = 0.006) and percent time <70 mg/dL (8.48% vs. 15.18%, P = 0.049), without increasing hyperglycemia (high blood glucose index: 3.13 vs. 2.09, P = 0.075; percent time >180 mg/dL: 13.24% vs. 10.42%, P = 0.5; percent time >250 mg/dL: 2.08% vs. 1.19%, P = 0.317). In addition, the number of hypoglycemia rescue treatments was reduced from 12 to 7 with the use of the system.

CONCLUSIONS

The study shows that the proposed IS-informed bolus calculator is safe and feasible in adults with T1D, appropriately reducing postprandial hypoglycemia following an exercise-induced IS increase.

High-intensity interval exercise and hypoglycaemia minimisation in adults with type 1 diabetes: A randomised cross-over trial

AIMS

We aimed to examine the feasibility and safety of undertaking high-intensity interval exercise (HIIE) with evening basal insulin dose reduction on exercise-related hypoglycaemia following an afternoon bout of HIIE, compared with moderate-intensity continuous exercise and a non-exercise control day in adults with type 1 diabetes in a free-living environment.

METHODS

Twelve adults with type 1 diabetes participated in a randomised, crossover trial (9 female/3 male, mean age 40.4 ± 9.9 years, duration 16.5 ± 9.8 years, HbA1c 8.0 ± 0.8%). Each participant undertook five conditions: a non-exercise day, and four exercise conditions on separate afternoons: a moderate-intensity continuous exercise bout; and three HIIE bouts with 10%, 20% and 30% evening basal insulin reduction. Post-exercise glucose response was measured for 24 h by continuous glucose monitoring and compared across conditions.

RESULTS

HIIE with 10%, 20% and 30% evening basal insulin dose reduction was not associated with an increase in hypoglycaemia compared with moderate-intensity continuous exercise, or the non-exercise day. There was no difference in hyperglycaemia, time-in-range or glucose variability across all exercise regimens and the non-exercise day (p > .05).

CONCLUSIONS

Exercise-related hypoglycaemia was not increased following afternoon HIIE when diabetes management strategies incorporating evening basal insulin dose reduction were utilised.

The Athlete with Type 1 Diabetes: Transition from Case Reports to General Therapy Recommendations

Fear of hypoglycemia is a common barrier to exercise and physical activity for individuals with type 1 diabetes. While some of the earliest studies in this area involved only one or two participants, the link between exercise, exogenous insulin, and hypoglycemia was already clear, with the only suggested management strategies being to decrease insulin dosage and/or consume carbohydrates before and after exercise. Over the past 50 years, a great deal of knowledge has been developed around the impact of different types and intensities of exercise on blood glucose levels in this population. Recent decades have also seen the development of technologies such as continuous glucose monitors, faster-acting insulins and commercially available insulin pumps to allow for the real-time observation of interstitial glucose levels, and more precise adjustments to insulin dosage before, during and after activity. As such, there are now evidence-based exercise and physical activity guidelines for individuals with type 1 diabetes. While the risk of hypoglycemia has not been completely eliminated, therapy recommendations have evolved considerably. This review discusses the evolution of the knowledge and the technology related to type 1 diabetes and exercise that have allowed this evolution to take place.

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.

Continuous Glucose Monitors and Activity Trackers to Inform Insulin Dosing in Type 1 Diabetes: The University of Virginia Contribution

Objective: Suboptimal insulin dosing in type 1 diabetes (T1D) is frequently associated with time-varying insulin requirements driven by various psycho-behavioral and physiological factors influencing insulin sensitivity (IS). Among these, physical activity has been widely recognized as a trigger of altered IS both during and following the exercise effort, but limited indication is available for the management of structured and (even more) unstructured activity in T1D. In this work, we present two methods to inform insulin dosing with biosignals from wearable sensors to improve glycemic control in individuals with T1D. Research Design and Methods: Continuous glucose monitors (CGM) and activity trackers are leveraged by the methods. The first method uses CGM records to estimate IS in real time and adjust the insulin dose according to a person’s insulin needs; the second method uses step count data to inform the bolus calculation with the residual glucose-lowering effects of recently performed (structured or unstructured) physical activity. The methods were tested in silico within the University of Virginia/Padova T1D Simulator. A standard bolus calculator and the proposed “smart” systems were deployed in the control of one meal in presence of increased/decreased IS (Study 1) and following a 1-hour exercise bout (Study 2). Postprandial glycemic control was assessed in terms of time spent in different glycemic ranges and low/high blood glucose indices (LBGI/HBGI), and compared between the dosing strategies. Results: In Study 1, the CGM-informed system allowed to reduce exposure to hypoglycemia in presence of increased IS (percent time < 70 mg/dL: 6.1% versus 9.9%; LBGI: 1.9 versus 3.2) and exposure to hyperglycemia in presence of decreased IS (percent time > 180 mg/dL: 14.6% versus 18.3%; HBGI: 3.0 versus 3.9), tending toward optimal control. In Study 2, the step count-informed system allowed to reduce hypoglycemia (percent time < 70 mg/dL: 3.9% versus 13.4%; LBGI: 1.7 versus 3.2) at the cost of a minor increase in exposure to hyperglycemia (percent time > 180 mg/dL: 11.9% versus 7.5%; HBGI: 2.4 versus 1.5). Conclusions: We presented and validated in silico two methods for the smart dosing of prandial insulin in T1D. If seen within an ensemble, the two algorithms provide alternatives to individuals with T1D for improving insulin dosing accommodating a large variety of treatment options. Future work will be devoted to test the safety and efficacy of the methods in free-living conditions.

Morning (Fasting) vs Afternoon Resistance Exercise in Individuals With Type 1 Diabetes: A Randomized Crossover Study

OBJECTIVE

To determine the effect of morning exercise in the fasting condition vs afternoon exercise on blood glucose responses to resistance exercise (RE).

RESEARCH DESIGN AND METHODS

For this randomized crossover design, 12 participants with type 1 diabetes mellitus [nine females; aged 31 ± 8.9 years; diabetes duration, 19.1 ± 8.3 years; HbA1c, 7.4% ± 0.8% (57.4 ± 8.5 mmol/mol)] performed ∼40 minutes of RE (three sets of eight repetitions, seven exercises, at the individual's predetermined eight repetition maximum) at either 7 am (fasting) or 5 pm. Sessions were performed at least 48 hours apart. Venous blood samples were collected immediately preexercise, immediately postexercise, and 60 minutes postexercise. Interstitial glucose was monitored overnight postexercise by continuous glucose monitoring (CGM).

RESULTS

Data are presented as mean ± SD. Blood glucose rose during fasting morning exercise (9.5 ± 3.0 to 10.4 ± 3.0 mmol/L), whereas it declined with afternoon exercise (8.2 ± 2.5 to 7.4 ± 2.6 mmol/L; P = 0.031 for time-by-treatment interaction). Sixty minutes postexercise, blood glucose concentration was significantly higher after fasting morning exercise than after afternoon exercise (10.9 ± 3.2 vs 7.9 ± 2.9 mmol/L; P = 0.019). CGM data indicated more glucose variability (2.7 ± 1.1 vs 2.0 ± 0.7 mmol/L; P = 0.019) and more frequent hyperglycemia (12 events vs five events; P = 0.025) after morning RE than after afternoon RE.

CONCLUSIONS

Compared with afternoon RE, morning (fasting) RE was associated with distinctly different blood glucose responses and postexercise profiles.

The hypoglycemia associated autonomic failure triggered by exercise in the patients with "brittle" diabetes and the strategy for prevention

Exercise is a fundamental component of diabetes management. However, choosing inappropriate type or timing of exercise is associated with mild or severe hypoglycemia either during exercise or several hours after exercise. Several studies have shown that impaired counterregulatory responses triggers hypoglycemia. Therefore, in this investigation, we explored the appropriate intensity and time of exercise in patients with diabetes. The mechanisms of counterregulatory responses and hypoglycemia associated autonomic failure (HAAF), as well as the strategies for preventing episodes of hypoglycemia after exercise were also investigated. In this study, we obtained the following results: 1) High intensity interval exercise is more suitable for diabetic patients. 2) Morning exercise reduces nocturnal hypoglycemia risks compared with midday, afternoon and evening exercise. 3) Hypoglycemia can be prevented by dietary approach, reduction or suspension of insulin dose, use of mini dose glucagon, caffeine, mitigation methods, prediction algorithm, autonomic feedback controlled close-loop insulin delivery, real time continuous glucose monitoring. Based on these results we concluded that exercise may cause severe hypoglycemia or induce blunted response in patients with diabetes. For Diabetes Mellitus (DM) patients, the intensity and time of exercise influence the occurrence of hypoglycemia. This review summarizes the clinical characteristics of different types of exercises and time of exercise that can be potentially used to educate and guide patients regarding the role of exercise in standard of care.

Carbohydrate Restriction in Type 1 Diabetes: A Realistic Therapy for Improved Glycaemic Control and Athletic Performance?

Around 80% of individuals with Type 1 diabetes (T1D) in the United States do not achieve glycaemic targets and the prevalence of comorbidities suggests that novel therapeutic strategies, including lifestyle modification, are needed. Current nutrition guidelines suggest a flexible approach to carbohydrate intake matched with intensive insulin therapy. These guidelines are designed to facilitate greater freedom around nutritional choices but they may lead to higher caloric intakes and potentially unhealthy eating patterns that are contributing to the high prevalence of obesity and metabolic syndrome in people with T1D. Low carbohydrate diets (LCD; <130 g/day) may represent a means to improve glycaemic control and metabolic health in people with T1D. Regular recreational exercise or achieving a high level of athletic performance is important for many living with T1D. Research conducted on people without T1D suggests that training with reduced carbohydrate availability (often termed "train low") enhances metabolic adaptation compared to training with normal or high carbohydrate availability. However, these "train low" practices have not been tested in athletes with T1D. This review aims to investigate the known pros and cons of LCDs as a potentially effective, achievable, and safe therapy to improve glycaemic control and metabolic health in people with T1D. Secondly, we discuss the potential for low, restricted, or periodised carbohydrate diets in athletes with T1D.

Reduction in insulin degludec dosing for multiple exercise sessions improves time spent in euglycaemia in people with type 1 diabetes: A randomized crossover trial

AIMS

To compare the time spent in specified glycaemic ranges in people with type 1 diabetes (T1D) during 5 consecutive days of moderate-intensity exercise while on either 100% or 75% of their usual insulin degludec (IDeg) dose.

MATERIALS AND METHODS

Nine participants with T1D (four women, mean age 32.1 ± 9.0 years, body mass index 25.5 ± 3.8 kg/m² , glycated haemoglobin 55 ± 7 mmol/mol (7.2% ± 0.6%) on IDeg were enrolled in the trial. Three days before the first exercise period, participants were randomized to either 100% or 75% of their usual IDeg dose. Participants exercised on a cycle ergometer for 55 minutes at a moderate intensity for 5 consecutive days. After a 4-week wash-out period, participants performed the last exercise period for 5 consecutive days with the alternate IDeg dose. Time spent in specified glycaemic ranges, area under the curve and numbers of hypoglycaemic events were compared for the 5 days on each treatment allocation using a paired Students' t test, Wilcoxon matched-pairs signed-rank test and two-way ANOVA.

RESULTS

Time spent in euglycaemia over 5 days was greater for the 75% IDeg dose versus the 100% IDeg dose (4008 ± 938 minutes vs. 3566 ± 856 minutes; P = 0.04). Numbers of hypoglycaemic events (P = 0.91) and time spent in hypoglycaemia (P = 0.07) or hyperglycaemia (P = 0.38) was similar for both dosing schemes.

CONCLUSIONS

A 25% reduction in usual IDeg dose around regular exercise led to more time spent in euglycaemia, with small effects on time spent in hypo- and hyperglycaemia.

Reproducibility in the cardiometabolic responses to high-intensity interval exercise in adults with type 1 diabetes

AIMS

Patients with type 1 diabetes (T1D) often report a rise in their blood glucose level following brief intense exercise. We sought to determine the reproducibility of the cardiometabolic responses to high-intensity interval training (HIIT).

METHODS

Sixteen adults with T1D, using an optimized multiple daily injection with basal insulin glargine 300 U/mL (Gla-300), performed four fasted HIIT sessions over a 4-6-week period. Exercise consisted of high-intensity interval cycling and multimodal training over 25 min.

RESULTS

Heart rate and rating of perceived exertion rose similarly in all sessions, as did lactate, catecholamine and growth hormone levels. Plasma glucose increased in response to HIIT in 62 of 64 visits (97%), with an overall increase of 3.7 ± 1.6 mmol/L (Mean ± SD) (P < 0.001). In within-patient comparisons, the change in plasma glucose among the four HIIT sessions was significantly correlated with a composite correlation of 0.58 ([r² = 0.34]; 95% CI 0.35-0.80; P < 0.01).

CONCLUSIONS

Intersession observations of four separate HIIT sessions showed high intrasubject reproducibility in the cardiometabolic responses to exercise, including the rise in plasma glucose, when adults with T1D perform the activity in a fasted state.

Gaps in Knowledge and the Need for Patient-Partners in Research Related to Physical Activity and Type 1 Diabetes: A Narrative Review

Regular physical activity (PA) is a cornerstone in the management of complications associated with type 1 diabetes (T1D). Most national guidelines advocate for regular PA for persons living with T1D, however the evidence to support these recommendations has not be reviewed recently. Additionally, in an era of patient-centered care and patient oriented research, the role of patient partners in the area of PA and T1D interventions has never been explored. The purpose of this narrative review is to overcome these two gaps in the literature. Here we review selected epidemiological evidence and identify gaps in research that would add important information to guide practitioners and future guidelines. We also provide an overview of patient-oriented research projects co-developed with persons living with T1D. Significant gaps in the field include: (1) a lack of adequately powered prospective cohort studies using serial measures of PA and hard chronic disease end-points; (2) no multi-centered, highly powered, randomized controlled trials of PA, and long-term health outcomes; (3) little data on the role of new technologies to support PA-related behavior change, and (4) no trials that involved patients in the design and execution of PA-based clinical trials. This review provides a template for scientists and patient partners to develop future research priorities and agendas in the field.