Blood glucose levels and performance in a sports cAMP for adolescents with type 1 diabetes mellitus: a field study. Int J Pediatr. 2010;2010. [PMID: 20811595 PMCID: PMC2929497 DOI: 10.1155/2010/216167]

Practical considerations for continuous glucose monitoring in elite athletes with type 1 diabetes mellitus: A narrative review

Type 1 diabetes mellitus (T1DM) refers to a metabolic condition where a lack of insulin impairs the usual homeostatic mechanisms to control blood glucose levels. Historically, participation in competitive sport has posed a challenge for those with T1DM, where the dynamic changes in blood glucose during exercise can result in dangerously high (hyperglycaemia) or low blood glucoses (hypoglycaemia) levels. Over the last decade, research and technological development has enhanced the methods of monitoring and managing blood glucose levels, thus reducing the chances of experiencing hyper- or hypoglycaemia during exercise. The introduction of continuous glucose monitoring (CGM) systems means that glucose can be monitored conveniently, without the need for frequent fingerpick glucose checks. CGM devices include a fine sensor inserted under the skin, measuring levels of glucose in the interstitial fluid. Readings can be synchronized to a reader or mobile phone app as often as every 1-5 min. Use of CGM devices is associated with lower HbA1c and a reduction in hypoglycaemic events, promoting overall health and athletic performance. However, there are limitations to CGM, which must be considered when being used by an athlete with T1DM. These limitations can be addressed by individualized education plans, using protective equipment to prevent sensor dislodgement, as well as further research aiming to: (i) account for disparities between CGM and true blood glucose levels during vigorous exercise; (ii) investigate the effects of temperature and altitude on CGM accuracy, and (iii) explore of the sociological impact of CGM use amongst sportspeople without diabetes on those with T1DM.

The effects of acute hyperglycaemia on sports and exercise performance in type 1 diabetes: A systematic review and meta-analysis

OBJECTIVES

People with type 1 diabetes (T1D) are advised by health care professionals to target mild hyperglycaemia before and during exercise, to reduce the risk of hypoglycaemia. This review aimed to summarise the available evidence on the effects of acute hyperglycaemia on sports and exercise performance in T1D.

DESIGN

Systematic review and meta-analysis.

METHODS

Medline, EMBASE, CENTRAL, and Web of Science were searched until 29th May 2023 for studies investigating the effects of acute hyperglycaemia on any sports or exercise performance outcome in T1D. Random-effects meta-analysis was performed using standardised mean differences (SMD) when more than one study reported data for similar outcomes. Certainty of evidence for each outcome was assessed using GRADE.

RESULTS

Seven studies were included in the review, comprising data from 119 people with T1D. Meta-analysis provided moderate-certainty evidence that acute hyperglycaemia does not significantly affect aerobic exercise performance (SMD -0.17; 95 % CI -0.59, 0.26; p = 0.44). There is low- or very-low certainty evidence that acute hyperglycaemia has no effect on anaerobic (two outcomes), neuromuscular (seven outcomes) or neurocognitive performance (three outcomes), except impaired isometric knee extension strength. One study provided low-certainty evidence that the performance effects of hyperglycaemia may depend on circulating insulin levels.

CONCLUSIONS

Acute hyperglycaemia before or during exercise appears unlikely to affect aerobic performance to an extent that is relevant to most people with T1D, based on limited evidence. Future research in this field should focus on anaerobic, neuromuscular and neurocognitive performance, and examine the relevance of circulating insulin levels.

Data-based modeling for hypoglycemia prediction: Importance, trends, and implications for clinical practice

Background and objective

Hypoglycemia is a key barrier to achieving optimal glycemic control in people with diabetes, which has been proven to cause a set of deleterious outcomes, such as impaired cognition, increased cardiovascular disease, and mortality. Hypoglycemia prediction has come to play a role in diabetes management as big data analysis and machine learning (ML) approaches have become increasingly prevalent in recent years. As a result, a review is needed to summarize the existing prediction algorithms and models to guide better clinical practice in hypoglycemia prevention.

Materials and methods

PubMed, EMBASE, and the Cochrane Library were searched for relevant studies published between 1 January 2015 and 8 December 2022. Five hypoglycemia prediction aspects were covered: real-time hypoglycemia, mild and severe hypoglycemia, nocturnal hypoglycemia, inpatient hypoglycemia, and other hypoglycemia (postprandial, exercise-related).

Results

From the 5,042 records retrieved, we included 79 studies in our analysis. Two major categories of prediction models are identified by an overview of the chosen studies: simple or logistic regression models based on clinical data and data-based ML models (continuous glucose monitoring data is most commonly used). Models utilizing clinical data have identified a variety of risk factors that can lead to hypoglycemic events. Data-driven models based on various techniques such as neural networks, autoregressive, ensemble learning, supervised learning, and mathematical formulas have also revealed suggestive features in cases of hypoglycemia prediction.

Conclusion

In this study, we looked deep into the currently established hypoglycemia prediction models and identified hypoglycemia risk factors from various perspectives, which may provide readers with a better understanding of future trends in this topic.

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.

Fear of hypoglycemia, a game changer during physical activity in type 1 diabetes mellitus patients

Hypoglycemia limits optimal glycemic management of patients with type 1 diabetes mellitus (T1DM). Fear of hypoglycemia (FoH) is a significant psychosocial consequence that negatively impacts the willingness of T1DM patients to engage in and profit from the health benefits of regular physical activity (e.g., cardiometabolic health, improved body composition, cardiovascular fitness, quality of life). Technological advances, improved insulin regimens, and a better understanding of the physiology of various types of exercise could help ameliorate FoH. This narrative review summarizes the available literature on FoH in children and adults and tools to avoid it.

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.

Exercise Management for Young People With Type 1 Diabetes: A Structured Approach to the Exercise Consultation

Regular physical activity during childhood is important for optimal physical and psychological development. For individuals with Type 1 Diabetes (T1D), physical activity offers many health benefits including improved glycemic control, cardiovascular function, blood lipid profiles, and psychological well-being. Despite these benefits, many young people with T1D do not meet physical activity recommendations. Barriers to engaging in a physically active lifestyle include fear of hypoglycemia, as well as insufficient knowledge in managing diabetes around exercise in both individuals and health care professionals. Diabetes and exercise management is complex, and many factors can influence an individual's glycemic response to exercise including exercise related factors (such as type, intensity and duration of the activity) and person specific factors (amount of insulin on board, person's stress/anxiety and fitness levels). International guidelines provide recommendations for clinical practice, however a gap remains in how to apply these guidelines to a pediatric exercise consultation. Consequently, it can be challenging for health care practitioners to advise young people with T1D how to approach exercise management in a busy clinic setting. This review provides a structured approach to the child/adolescent exercise consultation, based on a framework of questions, to assist the health care professional in formulating person-specific exercise management plans for young people with T1D.

Effect of insulin therapy and dietary adjustments on safety and performance during simulated soccer tests in people with type 1 diabetes: study protocol for a randomized controlled trial

Background

Despite the reduction in glycemic derangement in patients with type 1 diabetes mellitus (T1D) through dietary and therapeutic adjustments implemented before, during and after continuous exercise, evidence for its effectiveness with intermittent forms of exercise, such as soccer, is still lacking.

Methods/design

We designed a study protocol for a randomized, crossover, double-blinded, controlled trial, for the evaluation of the effect that a strategy of dietary and therapeutic modifications may have on safety and performance of persons with T1D in soccer training sessions and cognitive testing. Inclusion criteria comprise: age older than 18 years, more than 2 years since T1D diagnosis, low C-peptide level, a stable insulin regimen, HbA1c less than 9.0% and regular participation in soccer activities. Our primary outcome evaluates safety regarding hypoglycemia events in patients using dietary and therapeutic adjustments, compared with the performance under the implementation of current American Diabetes Association (ADA) usual recommendations for nutritional and pharmacological adjustments for exercise. Additionally, we will evaluate as secondary outcomes: soccer performance, indexed by performance in well-established soccer skill tests, cognitive functions (indexed by Stroop, digital vigilance test (DVT), Corsi block-tapping task (CBP), and rapid visual information processing (RVIP) tests), and glycemic control measured with a continuous glucose monitor (CGM).

Discussion

Dietary and insulin adjustments standardized under a 4-step method strategy have never been tested in a clinical trial setting with intermittent forms of exercise, such as soccer. We hypothesize that through this strategy we will observe better performance by persons with T1D in soccer and cognitive evaluations, and more stable control of glycemic parameters before, during and after exercise execution, indexed by CGM measurements.

Trial registration

ISRCTN, ISRCTN17447843. Registered on 5 January 2017.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-017-2078-1) contains supplementary material, which is available to authorized users.

Exercise management in type 1 diabetes: a consensus statement

Type 1 diabetes is a challenging condition to manage for various physiological and behavioural reasons. Regular exercise is important, but management of different forms of physical activity is particularly difficult for both the individual with type 1 diabetes and the health-care provider. People with type 1 diabetes tend to be at least as inactive as the general population, with a large percentage of individuals not maintaining a healthy body mass nor achieving the minimum amount of moderate to vigorous aerobic activity per week. Regular exercise can improve health and wellbeing, and can help individuals to achieve their target lipid profile, body composition, and fitness and glycaemic goals. However, several additional barriers to exercise can exist for a person with diabetes, including fear of hypoglycaemia, loss of glycaemic control, and inadequate knowledge around exercise management. This Review provides an up-to-date consensus on exercise management for individuals with type 1 diabetes who exercise regularly, including glucose targets for safe and effective exercise, and nutritional and insulin dose adjustments to protect against exercise-related glucose excursions.

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

BACKGROUND

Increasing numbers of people with diabetes are adopting exercise programs. Fear of hypoglycemia, hypoglycemia itself, and injuries are major issues for many people with diabetes undertaking physical activity. The purpose of this study was to investigate the effects of type 1 diabetes mellitus on the risk of hypoglycemia, glycemic variability, exercise performance, changes in body composition, changes in insulin dosage, and psychosocial well-being during a multiday endurance exercise event.

METHODS

Eleven participants (7 with type 1 diabetes, 4 with normal glucose tolerance) undertook a 15-day, 2300 km cycling tour from Barcelona to Vienna. Data were prospectively collected using bike computers, continuous glucose monitors, body composition analyzers, and mood questionnaires.

RESULTS

Mean blood glucose in riders with and without diabetes significantly reduced as the event progressed. Glycemic variability and time spent in hypoglycemia did not change throughout the ride for either set of riders. Riders with diabetes in the lowest quartile of sensor glucose values had significantly reduced power output. Percentage body fat also significantly fell. Hypo- and hyperglycemia provoked feelings of anxiety and worry.

CONCLUSIONS

This is the first study to describe a real-time endurance event in type 1 diabetes, and provides important new data that cannot be studied in laboratory conditions. Hypoglycemia continues to occurs in spite of peer support and large reductions in insulin dose. Glycemic variability is shown as a potential barrier to participation in physical activity through effects on mood and psychological well-being.

Classification of Physical Activity: Information to Artificial Pancreas Control Systems in Real Time

Physical activity has a wide range of effects on glucose concentrations in type 1 diabetes (T1D) depending on the type (ie, aerobic, anaerobic, mixed) and duration of activity performed. This variability in glucose responses to physical activity makes the development of artificial pancreas (AP) systems challenging. Automatic detection of exercise type and intensity, and its classification as aerobic or anaerobic would provide valuable information to AP control algorithms. This can be achieved by using a multivariable AP approach where biometric variables are measured and reported to the AP at high frequency. We developed a classification system that identifies, in real time, the exercise intensity and its reliance on aerobic or anaerobic metabolism and tested this approach using clinical data collected from 5 persons with T1D and 3 individuals without T1D in a controlled laboratory setting using a variety of common types of physical activity. The classifier had an average sensitivity of 98.7% for physiological data collected over a range of exercise modalities and intensities in these subjects. The classifier will be added as a new module to the integrated multivariable adaptive AP system to enable the detection of aerobic and anaerobic exercise for enhancing the accuracy of insulin infusion strategies during and after exercise.

Short and long term neuro-behavioral alterations in type 1 diabetes mellitus pediatric population

Type 1 diabetes mellitus (T1DM) is one of the most prevalent chronic conditions affecting individuals under the age of 18 years, with increasing incidence worldwide, especially among very young age groups, younger than 5. There is still no cure for the disease, and therapeutic goals and guidelines are a challenge. Currently, despite T1DM intensive management and technological interventions in therapy, the majority of pediatric patients do not achieve glycemic control goals. This leads to a potential prognosis of long term diabetic complications, nephrological, cardiac, ophthalmological and neurological. Unfortunately, the neurological manifestations, including neurocognitive and behavioral complications, may present soon after disease onset, during childhood and adolescence. These manifestations may be prominent, but at times subtle, thus they are often not reported by patients or physicians as related to the diabetes. Furthermore, the metabolic mechanism for such manifestations has been inconsistent and difficult to interpret in practical clinical care, as reported in several reviews on the topic of brain and T1DM. However, new technological methods for brain assessment, as well as the introduction of continuous glucose monitoring, provide new insights and information regarding brain related manifestations and glycemic variability and control parameters, which may impact the clinical care of children and youth with T1DM. This paper provides a comprehensive review of the most recently reported behavioral, cognitive domains, sleep related, electrophysiological, and structural alterations in children and adolescences from a novel point of view. The review focuses on reported impairments based on duration of T1DM, its timeline, and modifiable disease related risk parameters. These findings are not without controversy, and limitations of data are presented in addition to recommendations for future research direction.

Type 1 diabetes-associated cognitive decline: a meta-analysis and update of the current literature

BACKGROUND

Type 1 diabetes (T1D) can have a significant impact on brain structure and function, which is referred to as T1D-associated cognitive decline (T1DACD). Diabetes duration, early onset disease, and diabetes-associated complications are all proposed as factors contributing to T1DACD. However, there have been no comparisons in T1DACD between children and adults with T1D. To obtain a better insight into the occurrence and effects of T1DACD in T1D, the aim of the present meta-analysis was to investigate differences between children and adults and to analyse factors contributing T1DACD.

METHODS

Two electronic databases were consulted: PubMed and ISI Web of Knowledge. Literature published up until the end of 2013 was included in the analysis. Effect sizes (Cohen's d), which are standardized differences between experimental and control groups, were calculated.

RESULTS

There was a small to modest decrease in cognitive performance in T1D patients compared with non-diabetic controls. Children with T1D performed worse while testing for executive function, full intelligence quotient (IQ), and motor speed, whereas adults with T1D performed worse while testing the full, verbal and performance IQ, part of the executive function, memory, spatial memory, and motor speed. Episodes of severe hypoglycemia, chronic hyperglycemia, and age of onset can be significant factors influencing cognitive function in T1D.

CONCLUSIONS

The findings in the literature suggest that T1DACD is more severe in adults than children, indicating that age and diabetes duration contribute to this T1DACD.

An integrated multivariable artificial pancreas control system

The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.

Hypoglycemia induced by insulin as a triggering factor of cognitive deficit in diabetic children

This paper provides an overview of insulin-induced hypoglycemia as a triggering factor of cognitive deficit in children with type 1 diabetes mellitus. For this purpose, databases from 1961 to 2013 were used with the objective of detecting the primary publications that address the impact of hypoglycemia on cognitive performance of diabetic children. The results obtained from experimental animals were excluded. The majority of studies demonstrated that the cognitive deficit in diabetic children involves multiple factors including duration, intensity, severity, and frequency of hypoglycemia episodes. Additionally, age at the onset of type 1 diabetes also influences the cognitive performance, considering that early inception of the disease is a predisposing factor for severe hypoglycemia. Furthermore, the results suggest that there is a strong correlation between brain damage caused by hypoglycemia and cognitive deterioration. Therefore, a more cautious follow-up and education are needed to impede and treat hypoglycemia in children with diabetes mellitus.

Exercise and type 1 diabetes (T1DM)

Physical exercise is firmly incorporated in the management of type 1 diabetes (T1DM), due to multiple recognized beneficial health effects (cardiovascular disease prevention being preeminent). When glycemic values are not excessively low or high at the time of exercise, few absolute contraindications exist; practical guidelines regarding amount, type, and duration of age-appropriate exercise are regularly updated by entities such as the American Diabetes Association and the International Society for Pediatric and Adolescent Diabetes. Practical implementation of exercise regimens, however, may at times be problematic. In the poorly controlled patient, specific structural changes may occur within skeletal muscle fiber, which is considered by some to be a disease-specific myopathy. Further, even in well-controlled patients, several homeostatic mechanisms regulating carbohydrate metabolism often become impaired, causing hypo- or hyperglycemia during and/or after exercise. Some altered responses may be related to inappropriate exogenous insulin administration, but are often also partly caused by the "metabolic memory" of prior glycemic events. In this context, prior hyperglycemia correlates with increased inflammatory and oxidative stress responses, possibly modulating key exercise-associated cardio-protective pathways. Similarly, prior hypoglycemia correlates with impaired glucose counterregulation, resulting in greater likelihood of further hypoglycemia to develop. Additional exercise responses that may be altered in T1DM include growth factor release, which may be especially important in children and adolescents. These multiple alterations in the exercise response should not discourage physical activity in patients with T1DM, but rather should stimulate the quest for the identification of the exercise formats that maximize beneficial health effects.

Caffeine and glucose homeostasis during rest and exercise in diabetes mellitus

Caffeine is a substance that has been used in our society for generations, primarily for its effects on the central nervous system that causes wakefulness. Caffeine supplementation has become increasingly more popular as an ergogenic aid for athletes and considerable scientific evidence supports its effectiveness. Because of their potential to alter energy metabolism, the effects of coffee and caffeine on glucose metabolism in diabetes have also been studied both epidemiologically and experimentally. Predominantly targeting the adenosine receptors, caffeine causes alterations in glucose homeostasis by decreasing glucose uptake into skeletal muscle, thereby causing elevations in blood glucose concentration. Caffeine intake has also been proposed to increase symptomatic warning signs of hypoglycemia in patients with type 1 diabetes and elevate blood glucose levels in patients with type 2 diabetes. Other effects include potential increases in glucose counterregulatory hormones such as epinephrine, which can also decrease peripheral glucose disposal. Despite these established physiological effects, increased coffee intake has been associated with reduced risk of developing type 2 diabetes in large-scale epidemiological studies. This review paper highlights the known effects of caffeine on glucose homeostasis and diabetes metabolism during rest and exercise.

Hypoglycemia Early Alarm Systems Based On Multivariable Models

Hypoglycemia is a major challenge of artificial pancreas systems and a source of concern for potential users and parents of young children with Type 1 diabetes (T1D). Early alarms to warn the potential of hypoglycemia are essential and should provide enough time to take action to avoid hypoglycemia. Many alarm systems proposed in the literature are based on interpretation of recent trends in glucose values. In the present study, subject-specific recursive linear time series models are introduced as a better alternative to capture glucose variations and predict future blood glucose concentrations. These models are then used in hypoglycemia early alarm systems that notify patients to take action to prevent hypoglycemia before it happens. The models developed and the hypoglycemia alarm system are tested retrospectively using T1D subject data. A Savitzky-Golay filter and a Kalman filter are used to reduce noise in patient data. The hypoglycemia alarm algorithm is developed by using predictions of future glucose concentrations from recursive models. The modeling algorithm enables the dynamic adaptation of models to inter-/intra-subject variation and glycemic disturbances and provides satisfactory glucose concentration prediction with relatively small error. The alarm systems demonstrate good performance in prediction of hypoglycemia and ultimately in prevention of its occurrence.

Preventing exercise-induced hypoglycemia in type 1 diabetes using real-time continuous glucose monitoring and a new carbohydrate intake algorithm: an observational field study

BACKGROUND

Real-time (RT) continuous glucose monitoring (CGM) offers the possibility to better manage glucose levels during exercise in active individuals with type 1 diabetes mellitus (T1DM). However, studies have yet to determine the appropriate actions to take when glucose levels are trending toward hypoglycemia. The purpose of this observational field study was to test the effectiveness of RT-GCM and a new carbohydrate intake algorithm designed for maintaining euglycemia during sports.

METHODS

During a 2-week sports camp, 25 adolescents (8-17 years old) with T1DM were fitted with a RT-CGM device and instructed to ingest fast-acting carbohydrates (8-20 g, depending on the concentration of glucose at the time of RT-CGM alert and rates of change in glycemia) when glucose levels were trending toward hypoglycemia. Rates of change in glucose were measured before and after algorithm use, and the incidence of hypoglycemia was documented.

RESULTS

With RT-CGM and algorithm use, euglycemia was largely maintained with modest amounts of carbohydrate intake, even when glucose levels were initially dropping at an elevated rate (>0.55 mmol/L per 5 min). Mild biochemical hypoglycemia (3.0-3.9 mmol/L) occurred just twice out of 22 uses of the algorithm (9%) when trend arrows alerted the subjects that glucose levels were dropping. When glucose levels were already below target (<5.0 mmol/L), mild hypoglycemia occurred five times out of 13 events (38%), despite 16 g of carbohydrate being ingested. Average glucose levels during sports in the 60 min following algorithm use were 5.8 ± 1.2 mmol/L, 5.3 ± 1.0 mmol/L, and 6.2 ± 0.8 mmol/L in the 20-, 16-, and 8-g carbohydrate intake protocols when glucose levels were initially on target but dropping toward hypoglycemia.

CONCLUSION

When coupled with RT-CGM, a new carbohydrate intake algorithm prevents hypoglycemia and maintains euglycemia during exercise, particularly if patients ingest carbohydrate when trend arrows alert them of a drop in glycemia.