Glycemic Control and Muscle Damage in 3 Athletes With Type 1 Diabetes During a Successful Performance in a Relay Ultramarathon: A Case Report

Assessment of selected muscle damage markers and zonulin concentration after maximum-intensity exercise in men with type 1 diabetes treated with a personal insulin pump

AIM

Exercise-induced muscle damage depends on exercise intensity and duration and on individual susceptibility. Mechanical and metabolic stress may disturb the intestinal microflora. The study evaluated selected muscle damage markers and zonulin concentration after maximum-intensity exercise in type 1 diabetes (T1D) men compared with healthy controls.

METHODS

The study involved 16 T1D participants and 28 controls matched by age (22.7 [21.3-25.1] vs. 22.6 [20.9-26.3] years), body mass index (24.2 ± 1.6 vs. 24.2 ± 1.9 kg/m2), and body fat percentage (16.1 ± 5.2 vs. 14.9 ± 4.6%). The T1D group had 11.3 ± 5.1 years of diabetes duration and a suboptimal mean glycated haemoglobin level of 7.2 ± 1.1%. The subjects underwent a graded running treadmill test until exhaustion. Lactate concentration was assessed in arterialized blood at baseline and 3 and 20 min after the test. Cortisol, testosterone, tumour necrosis factor α, myoglobin, lactate dehydrogenase, zonulin, and vitamin D levels were evaluated in cubital fossa vein blood before and 60 min after the test.

RESULTS

T1D patients presented higher baseline zonulin, myoglobin concentration, testosterone/cortisol ratio, and lower maximal oxygen uptake. On adjusting for the baseline values, the groups differed in zonulin, lactate dehydrogenase, and myoglobin levels, testosterone/cortisol ratio, and lactate concentration determined 20 min after exercise (P < 0.05).

CONCLUSION

Maximum-intensity exercise increased muscle and intestinal damage in T1D participants. In patients with lower physical activity, very-high-intensity exercise should be recommended with caution. Observing the anabolic-catabolic index may help individualize effort intensity in T1D individuals.

Nutritional Strategies of an Athlete with Type 1 Diabetes Mellitus During a 217-km Ultramarathon

Considering the challenges in meeting the high nutritional demand during ultramarathons, the aim of this study was to analyze the nutritional strategies and glycemic response of an athlete with type 1 diabetes (DM1) during participation in a 217-km ultramarathon. A 36-y-old male athlete who was diagnosed with DM1 15 y earlier was studied during participation in the Brazil 135 ultramarathon. Food consumption and blood glucose were recorded during the race, and nutritional intake was calculated after the race. The athlete completed the race in 51 h 18 min. He consumed a total of 3592 kcal, 532 g carbohydrate, 166 g protein, 92 g lipid, and 14 L of water during the race. Glycemic values ranged from 3.6 to 18.2 mmol·L^-1. Most glycemic values (47%) ranged from 3.9 to 10 mmol·L^-1, whereas 5% were <3.9 mmol·L^-1, 16% were >10 to 13.9 mmol·L^-1, and 32% were >13.9 mmol·L^-1. This case report describes the dietary profile of an athlete with DM1 during a 217-km ultramarathon. Although the athlete implemented strategies that differed from those recommended in the literature, food and nutrient intake and the glycemic management strategy adopted allowed him to successfully finish the race. These results suggest that past personal experiences can be considered and that nutritional recommendations for athletes with DM1 should be individualized.

Contribution of Solid Food to Achieve Individual Nutritional Requirement during a Continuous 438 km Mountain Ultramarathon in Female Athlete

Background: Races and competitions over 100 miles have recently increased. Limited information exists about the effect of multiday continuous endurance exercise on blood glucose control and appropriate intake of food and drink in a female athlete. The present study aimed to examine the variation of blood glucose control and its relationship with nutritional intake and running performance in a professional female athlete during a 155.7 h ultramarathon race with little sleep. Methods: We divided the mountain course of 438 km into 33 segments by timing gates and continuously monitored the participant’s glucose profile throughout the ultramarathon. The running speed in each segment was standardized to the scheduled required time-based on three trial runs. Concurrently, the accompanying runners recorded the participant’s food and drink intake. Nutrient, energy, and water intake were then calculated. Results: Throughout the ultramarathon of 155.7 h, including 16.0 h of rest and sleep, diurnal variation had almost disappeared with the overall increase in blood glucose levels (25–30 mg/dL) compared with that during resting (p < 0.0001). Plasma total protein and triglyceride levels were decreased after the ultramarathon. The intake of protein and fat directly or indirectly contributed to maintaining blood glucose levels and running speed as substrates for gluconeogenesis or as alternative sources of energy when the carbohydrate intake was at a lower recommended limit. The higher amounts of nutrient intakes from solid foods correlated with a higher running pace compared with those from liquids and gels to supply carbohydrates, protein, and fat. Conclusion: Carbohydrate, protein, and fat intake from solid foods contributed to maintaining a fast pace with a steady, mild rise in blood glucose levels compared with liquids and gels when female runner completed a multiday continuous ultramarathon with little sleep.

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.

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.

Current Trends in Ultramarathon Running

Exercise is universally recognized for its health benefits and distance running has long been a popular form of exercise and sport. Ultramarathons, defined as races longer than a marathon, have become increasingly popular in recent years. The diverse ultramarathon distances and courses provide additional challenges in race performance and medical coverage for these events. As the sport grows in popularity, more literature has become available regarding ultramarathon-specific illnesses and injuries, nutrition guidelines, psychology, physiologic changes, and equipment. This review focuses on recent findings and trends in ultramarathon running.

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.

Glycaemic stability of a cyclist with Type 1 diabetes: 4011 km in 20 days on a ketogenic diet

BACKGROUND

Maintaining glycaemic control during exercise presents a significant challenge for people living with Type 1 diabetes. Significant glycaemic variability has been observed in athletes with Type 1 diabetes in competitive contexts. While very-low-carbohydrate ketogenic diets have been shown to minimize glycaemic excursions, no published data have examined if this translates to exercise.

CASE REPORT

We report the case of a 37-year-old man with Type 1 diabetes who successfully undertook a 4011 km cycle across Australia over 20 consecutive days whilst consuming a very-low-carbohydrate ketogenic diet. Continuous glucose monitoring data capture was 98.4% for the ride duration and showed remarkable glycaemic stability, with a standard deviation of 2.1 mmol/l (average interstitial glucose 6.1 mmol/l) and 80.4% of time spent within a range of 3.9-10 mmol/l. Interstitial glucose was <3 mmol/l for 2.1% of this time, with only a single episode of symptomatic hypoglycaemia prompting brief interruption of exercise for carbohydrate administration.

CONCLUSION

This case demonstrates the viability of a very-low-carbohydrate ketogenic diet in an individual with Type 1 diabetes undertaking exercise. While the effect of a very-low-carbohydrate ketogenic diet is yet to be examined more broadly in athletes with Type 1 diabetes, the glycaemic stability observed suggests that fat adaptation may attenuate glycaemic swings and reduce reliance on carbohydrate consumption during exercise for maintaining euglycaemia.

Mountain Ultramarathon Induces Early Increases of Muscle Damage, Inflammation, and Risk for Acute Renal Injury

Purpose: This study aimed to investigate changes in muscle damage during the course of a 217-km mountain ultramarathon (MUM). In an integrative perspective, inflammatory response and renal function were also studied.

Methods: Six male ultra-runners were tested four times: pre-race, at 84 km, at 177 km, and immediately after the race. Blood samples were analyzed for serum muscle enzymes, acute-phase protein, cortisol, and renal function biomarkers.

Results: Serum creatine kinase (CK), lactate dehydrogenase (LDH), and aspartate aminotransferase (AST) increased significantly throughout the race (P < 0.001, P < 0.001; P = 0.002, respectively), and effect size (ES) denoted a large magnitude of muscle damage. These enzymes increased from pre-race (132 ± 18, 371 ± 66, and 28 ± 3 U/L, respectively) to 84 km (30, 1.8, and 3.9-fold, respectively); further increased from 84 to 177 km (4.6, 2.9, and 6.1-fold, respectively), followed by a stable phase until the finish line. Regarding the inflammatory response, significant differences were found for C-reactive protein (CRP) (P < 0.001) and cortisol (P < 0.001). CRP increased from pre-race (0.9 ± 0.3 mg/L) to 177 km (243-fold), cortisol increased from pre-race (257 ± 30 mmol/L) to the 84 km (2.9-fold), and both remained augmented until the finish line. Significant changes were observed for creatinine (P = 0.03), urea (P = 0.001), and glomerular filtration rate (GFR) (P < 0.001), and ES confirmed a moderate magnitude of changes in renal function biomarkers. Creatinine and urea increased, and GFR decreased from pre-race (1.00 ± 0.03 mg/dL, 33 ± 6 mg/dL, and 89 ± 5 ml/min/1.73 m², respectively) to 84 km (1.3, 3.5, and 0.7-fold, respectively), followed by a plateau phase until the finish line.

Conclusion: This study shows evidence that muscle damage biomarkers presented early peak levels and they were followed by a plateau phase during the last segment of a 217-km MUM. The acute-phase response had a similar change of muscle damage. In addition, our data showed that our volunteers meet the risk criteria for acute kidney injury from 84 km until they finished the race, without demonstrating any clinical symptomatology.