Biochemical, Physiological and Psychological Changes During Endurance Exercise in People With Type 1 Diabetes

Hypoglycemia and glycemic variability of people with type 1 diabetes with lower and higher physical activity loads in free-living conditions using continuous subcutaneous insulin infusion with predictive low-glucose suspend system

INTRODUCTION

Maintaining glycemic control during and after physical activity (PA) is a major challenge in type 1 diabetes (T1D). This study compared the glycemic variability and exercise-related diabetic management strategies of adults with T1D achieving higher and lower PA loads in nighttime-daytime and active- sedentary behavior hours in free-living conditions.

RESEARCH DESIGN AND METHODS

Active adults (n=28) with T1D (ages: 35±10 years; diabetes duration: 21±11 years; body mass index: 24.8±3.4 kg/m2; glycated hemoglobin A1c: 6.9±0.6%) on continuous subcutaneous insulin delivery system with predictive low glucose suspend system and glucose monitoring, performed different types, duration and intensity of PA under free-living conditions, tracked by accelerometer over 14 days. Participants were equally divided into lower load (LL) and higher load (HL) by median of daily counts per minute (61122). Glycemic variability was studied monitoring predefined time in glycemic ranges (time in range (TIR), time above range (TAR) and time below range (TBR)), coefficient of variation (CV) and mean amplitude of glycemic excursions (MAGE). Parameters were studied in defined hours timeframes (nighttime-daytime and active-sedentary behavior). Self-reported diabetes management strategies were analysed during and post-PA.

RESULTS

Higher glycemic variability (CV) was observed in sedentary hours compared with active hours in the LL group (p≤0.05). HL group showed an increment in glycemic variability (MAGE) during nighttime versus daytime (p≤0.05). There were no differences in TIR and TAR across all timeframes between HL and LL groups. The HL group had significantly more TBR during night hours than the LL group (p≤0.05). Both groups showed TBR above recommended values. All participants used fewer post-PA management strategies than during PA (p≤0.05).

CONCLUSION

Active people with T1D are able to maintain glycemic variability, TIR and TAR within recommended values regardless of PA loads. However, the high prevalence of TBR and the less use of post-PA management strategies highlights the potential need to increase awareness on actions to avoid glycemic excursions and hypoglycemia after exercise completion.

Nutritional intake when cycling under racing and training conditions in professional male cyclists with type 1 diabetes

This study sought to detail and compare the in-ride nutritional practices of a group of professional cyclists with type 1 diabetes (T1D) under training and racing conditions. We observed seven male professional road cyclists with T1D (Age: 28 ± 4 years, HbA_1c: 6.4 ± 0.4% [46 ± 4 mmol.mol^-1], VO_2max: 73.9 ± 4.3 ml.kg ^-1.min^-1) during pre-season training and during a Union Cycliste Internationale multi-stage road cycling race (Tour of Slovenia). In-ride nutritional, interstitial glucose, and performance variables were quantified and compared between the two events.    The in-ride energy intake was similar between training and racing conditions     (p = 0.909), with carbohydrates being the major source of fuel in both events during exercise at a rate of 41.9 ± 6.8 g.h^-1 and 45.4 ± 15.5 g.h^-1 (p = 0.548), respectively. Protein consumption was higher during training (2.6 ± 0.6 g.h^-1) than race rides (1.9 ± 0.9 g.h^-1; p = 0.051).   A similar amount of time was spent within the euglycaemic range (≥70-≤180 mg.dL^-1): training 77.1 ± 32.8% vs racing 73.4 ± 3.9%; p = 0.818. These data provide new information on the in-ride nutritional intake in professional cyclists with T1D during different stages of the competitive season.

A predictive model incorporating the change detection and Winsorization methods for alerting hypoglycemia and hyperglycemia

This paper focuses on establishing an effective predictive model to quickly and accurately alert hypoglycemia and hyperglycemia for helping control blood glucose levels of people with diabetes. In general, a good predictive model is established on the features of data. Inspired by this, we first analyze the characteristics of continuous glucose monitoring (CGM) data by the equality of variances test and outlier detection, which show time-varying fluctuations and jump points in CGM data. Therefore, we incorporate the change detection method and the Winsorization method into the predictive model based on the autoregressive moving average (ARMA) model and the recursive least squares (RLS) method to fit the above characteristics. To the best of our knowledge, the proposed method is the first attempt to give a solution for matching the time-varying fluctuations and jump points of CGM data simultaneously. A case study using CGM data is given to validate the effectiveness of the proposed method under 30-min-ahead prediction. The results show that the proposed method can improve the true alarm ratio of hypoglycemia and hyperglycemia from 0.7983 to 0.8783, and lengthen the average advance detection time of hypoglycemia and hyperglycemia from 19.77 to 22.64 min.

Acute hyperglycaemia does not have a consistent adverse effect on exercise performance in recreationally active young people with type 1 diabetes: a randomised crossover in-clinic study

AIMS/HYPOTHESIS

In individuals with type 1 diabetes, chronic hyperglycaemia impairs aerobic fitness. However, the effect of acute marked hyperglycaemia on aerobic fitness is unclear, and the impact of insulin level has not been examined. In this study, we explored if acute hyperglycaemia with higher or low insulin levels affects [Formula: see text] and other exercise performance indicators in individuals with type 1 diabetes.

METHODS

Eligible participants were aged 14 to 30 years, with complication-free, type 1 diabetes and HbA_1c ≤ 75 mmol/mol (≤9%). Participants exercised in a clinical laboratory under three clamp (constant insulin, variable glucose infusion) conditions: euglycaemia (5 mmol/l) with 20 mU [m² BSA]^-1 min^-1 insulin (where BSA is body surface area) (Eu20); hyperglycaemia (17 mmol/l) with 20 mU [m² BSA]^-1 min^-1 insulin (Hyper20); and hyperglycaemia (17 mmol/l) with 5 mU [m² BSA]^-1 min^-1 insulin (Hyper5) on separate days. Participants and the single testing assessor were blinded to condition, with participants allocated to randomised testing condition sequences as they were consecutively recruited. Standardised testing (in order) conducted on each of the three study days included: triplicate 6 second sprint cycling, grip strength, single leg static balance, vertical jump and modified Star Excursion Balance Test, ten simple and choice reaction times and one cycle ergometer [Formula: see text] test. The difference between conditions in the aforementioned testing measures was analysed, with the primary outcome being the difference in [Formula: see text].

RESULTS

Twelve recreationally active individuals with type 1 diabetes (8 male, mean ± SD 17.9 ± 3.9 years, HbA_1c 61 ± 11 mmol/mol [7.7 ± 1.0%], 7 ± 3 h exercise/week) were analysed. Compared with Eu20, [Formula: see text] was lower in Hyper20 (difference 0.17 l/min [95% CI 0.31, 0.04; p = 0.02] 6.6% of mean Eu20 level), but Hyper5 was not different (p = 0.39). Compared with Eu20, sprint cycling peak power was not different in Hyper20 (p = 0.20), but was higher in Hyper5 (64 W [95% CI 13, 115; p = 0.02] 13.1%). Hyper20 reaction times were not different (simple: p = 0.12) but Hyper5 reaction times were slower (simple: 11 milliseconds [95% CI 1, 22; p = 0.04] 4.7%) than Eu20. No differences between Eu20 and either hyperglycaemic condition were observed for the other testing measures (p > 0.05).

CONCLUSIONS/INTERPRETATION

Acute marked hyperglycaemia in the higher but not low insulin state impaired [Formula: see text] but to a small extent. Acute hyperglycaemia had an insulin-dependent effect on sprint cycling absolute power output and reaction time but with differing directionality (positive for sprint cycling and negative for reaction time) and no effect on the other indicators of exercise performance examined. We find that acute hyperglycaemia is not consistently adverse and does not impair overall exercise performance to an extent clinically relevant for recreationally active individuals with type 1 diabetes.

FUNDING

This research was funded by Diabetes Research Western Australia and Australasian Paediatric Endocrine Group grants.

Carbohydrate Requirement for Exercise in Type 1 Diabetes: Effects of Insulin Concentration

Physical activity is a keystone of a healthy lifestyle as well as of management of patients with type 1 diabetes. The risk of exercise-induced hypoglycemia, however, is a great challenge for these patients. The glycemic response to exercise depends upon several factors concerning the patient him/herself (eg, therapy, glycemic control, training level) and the characteristics of the exercise performed. Only in-depth knowledge of these factors will allow to develop individualized strategies minimizing the risk of hypoglycemia. The main factors affecting the exercise-induced hypoglycemia in patients with T1D have been analyzed, including the effects of insulin concentration. A model is discussed, which has the potential to become the basis for providing patients with individualized suggestions to keep constant glucose levels on each exercise occasion.

Bolus insulin dose depends on previous-day race intensity during 5 days of professional road-cycle racing in athletes with type 1 diabetes: A prospective observational study

AIMS

To assess insulin therapy, macronutrient intake and glycaemia in professional cyclists with type 1 diabetes (T1D) over a 5-day Union Cycliste Internationale road-cycle race.

MATERIAL AND METHODS

In this prospective observational study, seven professional cyclists with T1D (age 28 ± 4 years, body mass index 20.9 ± 0.9 kg/m² , glycated haemoglobin concentration 56 ± 7 mmol/mol [7.3% ± 0.6%]) were monitored during a five-stage professional road cycling race. Real-time continuous glucose monitoring (rtCGM) data, smart insulin pen dose data and macronutrient intake were assessed by means of repeated-measure one-way ANOVA and post hoc testing. Associations between exercise physiological markers and rtCGM data, insulin doses and macronutrient intake were assessed via linear regression modelling (P ≤ 0.05).

RESULTS

Bolus insulin dose was significantly reduced over the 5-day period (P = 0.03), while carbohydrate intake (P = 0.24) and basal insulin doses remained unchanged (P = 0.64). A higher mean previous-day race intensity was associated with a lower mean sensor glucose level (P = 0.03), less time above range level 2 (>13.9 mmol/L [250 mg/dL]; P = 0.05) and lower doses of bolus insulin (P = 0.04) on the subsequent day. No significant associations were found for any other glycaemic range and glycaemic variability (P > 0.05).

CONCLUSIONS

This is the first study to demonstrate the influence of previous-day race intensity on subsequent bolus insulin dose requirements in professional cyclists with T1D. These data may help inform therapeutic strategies to ensure safe exercise performance.

Coronavirus disease (Covid-19): How does the exercise practice in active people with type 1 diabetes change? A preliminary survey

AIMS

Coronavirus disease (Covid-19) could lead persons with pre-existing medical conditions to severe respiratory infections. The Italian Government introduced quarantine to limit viral transmission. This measure could lead people with type 1 diabetes (PWT1D) to disrupt daily care routine including PA practice with difficulties in glycemia management. This study aims to explore PA level in PWT1D before and during quarantine and to describe variation in glycemia values.

METHODS

An online survey investigating medical factors and the perceived and PA level in pre-established period before and after the introduction of quarantine was developed. Comparison between pre and post quarantine was assessed by Wilcoxon Signed Ranks test for continuous variables.

RESULTS

A total of 154 subjects satisfied the eligibility criteria (54.5% males, 44.8 ± 12.5 years). We found a decrease of PA level (Godin Scale Score 25 ± 1.7vs38.6 ± 1.7 points), steps number and minutes of exercise (respectively 12.606 ± 5026vs4.760 ± 3.145 and 66±4 vs 38±3) and an increase of glycemia values (142.1 ± 25.4 mg/dLvs150.8 ± 29.4 mg/dL).

CONCLUSIONS

PWT1D reported a decrease in exercise and worst glycemia. Although PWT1D tried to remain active, their PA level was inadequate to prevent glycemia rising. The difficult to maintain a glycemic control could expose patients to diabetes complications and to an higher risk to counteract infections.

Glycemic responses to strenuous training in male professional cyclists with type 1 diabetes: a prospective observational study

INTRODUCTION

This prospective observational study sought to establish the glycemic, physiological and dietary demands of strenuous exercise training as part of a 9-day performance camp in a professional cycling team with type 1 diabetes (T1D).

RESEARCH DESIGN AND METHODS

Sixteen male professional cyclists with T1D on multiple daily injections (age: 27±4 years; duration of T1D: 11±5 years; body mass index: 22±2 kg/m²; glycated hemoglobin: 7%±1% (50±6 mmol/mol); maximum rate of oxygen consumption: 73±4 mL/kg/min) performed road cycle sessions (50%-90% of the anaerobic threshold, duration 1-6 hours) over 9 consecutive days. Glycemic (Dexcom G6), nutrition and physiological data were collected throughout. Glycemic data were stratified into predefined glycemic ranges and mapped alongside exercise physiology and nutritional parameters, as well as split into daytime and night-time phases for comparative analysis. Data were assessed by means of analysis of variance and paired t-tests. A p value of ≤0.05 (two-tailed) was statistically significant.

RESULTS

Higher levels of antecedent hypoglycemia in the nocturnal hours were associated with greater time spent in next-day hypoglycemia overall (p=0.003) and during exercise (p=0.019). Occurrence of nocturnal hypoglycemia was associated with over three times the risk of next-day hypoglycemia (p<0.001) and a twofold risk of low glucose during cycling (p<0.001). Moreover, there was trend for a greater amount of time spent in mild hypoglycemia during the night compared with daytime hours (p=0.080).

CONCLUSION

The higher prevalence of nocturnal hypoglycemia was associated with an increased risk of next-day hypoglycemia, which extended to cycle training sessions. These data highlight the potential need for additional prebed carbohydrates and/or insulin dose reduction strategies around exercise training in professional cyclists with T1D.

TRIAL REGISTRATION NUMBER

DRKS00019923.

MUSCLE MITOCHONDRIAL CAPACITY AND ENDURANCE IN ADULTS WITH TYPE 1 DIABETES

The impact of type 1 diabetes (T1D) on muscle endurance and oxidative capacity is currently unknown.

Purpose

Measure muscle endurance and oxidative capacity of adults with T1D compared to controls.

Methods

A cross-sectional study design with a control group was used. Subjects (19-37 years old) with T1D (n=17) and controls (n=17) were assessed with hemoglobin A1c (HbA1c) and casual glucose. Muscle endurance was measured with an accelerometer at stimulation frequencies of 2, 4, and 6 Hz for a total of nine minutes. Mitochondrial capacity was measured using near-infrared spectroscopy after exercise as the rate constant of the rate of recovery of oxygen consumption.

Results

T1D and control groups were similar in age, sex, height, and race. The T1D group had slightly higher BMI values and adipose tissue thickness over the forearm muscles. Casual glucose was 150±70 mg/dL for T1D and 98±16 mg/dL for controls (P=0.006). HbA1c of T1D subjects was 7.1±0.9% and 5.0±0.4% for controls (P<0.01). Endurance indexes at 2, 4, and 6 Hz were 94.5±5.2%, 81.8±8.4%, and 68.6±13.5% for T1D and 94.6±4.1%, 85.9±6.3%, and 68.7±15.4% for controls (p = 0.97, 0.12, 0.99, respectively). There were no differences between groups in mitochondrial capacity (T1D= 1.9±0.5 min^-1 and control=1.8±0.4 min^-1, P=0.29) or reperfusion rate (T1D= 8.8±2.8s and control=10.3±3.0s, P=0.88). There were no significant correlations between HbA1c and either muscle endurance, mitochondrial capacity or reperfusion rate.

Conclusions

Adults with T1D did not have reduced oxidative capacity, muscle endurance or muscle reperfusion rates compared to controls. HbA1c also did not correlate with muscle endurance, mitochondrial capacity or reperfusion rates. Future studies should extend these measurements to older people or people with poorly-controlled T1D.

Effects of Moderate Cycling Exercise on Blood Glucose Regulation Following Successful Clinical Islet Transplantation

CONTEXT

Islet transplantation is effective in preventing hypoglycemia in patients with type 1 diabetes (T1D). However, it is unknown whether transplanted islets regulate plasma glucose concentrations appropriately during and after exercise in human islet transplant recipient (ITxs).

OBJECTIVE

To determine the effect of exercise on plasma glucose, insulin, and glucagon concentrations in ITxs compared with control subjects (CONs) without diabetes.

INTERVENTION

Participants completed two conditions in random order: 45 minutes of aerobic exercise (60% VO2peak) and 45 minutes of seated rest. Blood samples were drawn at baseline, immediately after exercise or rest, and every 15 minutes throughout a 60-minute recovery period. Postexercise (24 hours) interstitial glucose was monitored with continuous glucose monitoring (CGM).

RESULTS

Twenty-four participants (12 ITxs, 12 CONs) completed the protocol. Plasma glucose decreased more over time with exercise in ITxs compared with CONs [main effects of treatment (P = 0.019), time (P = 0.001), and group (P = 0.012)]. Plasma glucose was lower during exercise vs rest in ITxs but not CONs [treatment by group interaction (P = 0.028)]. Plasma glucose decreased more during exercise than during rest [treatment by time interaction (P = 0.001)]. One ITx and one CON experienced plasma glucose concentrations <3.5 mmol/L at the end of exercise, both of whom returned above that threshold within 15 minutes. Nocturnal CGM glucose <3.5 mmol/L was detected in two CONs but no ITxs.

CONCLUSION

Despite a greater plasma glucose decline during exercise in ITxs, hypoglycemia risk was similar during and after exercise in ITxs compared with CONs.

Low carbohydrate diet and improved glycaemic control in a patient with type one diabetes

We present the case of an adult female with type 1 diabetes, whose HbA1c was trending at 58 mmol/mol (7.5%) for the past 3 years. In August 2016, she reduced her total daily carbohydrate intake to 30–50 g and adjusted her other macronutrients to compensate for the calorific deficit. Her HbA1c fell to 34 mmol/mol (5.3%) by January 2017 and average daily blood glucose readings decreased significantly from 10.4 to 6.1 mmol/L. Moreover, she observed a marked reduction of average daily glucose variability. Notably, there were no significant episodes of hypo- or hyperglycaemia and her lipid profile remained static. Subjectively, she described an improvement in her quality of life and the dietary transition was extremely well tolerated. We discuss these findings in detail and the potential clinical benefits for patients with type 1 diabetes that can be gained by following a low carbohydrate diet.

Fear of hypoglycemia: Influence on glycemic variability and self-management behavior in young adults with type 1 diabetes

PURPOSE

The purpose of this study was to examine how fear of hypoglycemia (FOH) is associated with glycemic variability (GV) and self-management behavior in young adults (aged 18-35) with type 1 diabetes (T1DM).

PROCEDURES

Using a prospective repeated-measures design, in 35 young adults, within- and between-person and temporal associations of FOH, specific self-management behaviors, and GV were measured. The data were collected using questionnaires and real-time measures using daily diaries, insulin pump downloads, actigraphy, and continuous glucose monitoring.

FINDINGS

FOH was associated with greater glycemic variability. Significant temporal associations emerged. Concurrent day (glucose SD, p=.011) and previous-evening fear levels were associated with GV (glucose SD, p=.007). FOH was also associated with greater calorie intake (r=.492, p=.003) and less physical activity (light activity, r=-.341, p=.045).

CONCLUSIONS

The significant associations of FOH with GV, dietary patterns, and physical activity provide evidence for FOH as an important psychological factor associated with diabetes care.