L’impact du traitement des données sur les valeurs obtenues lors d’un test progressif maximal chez l’enfant

Objectif : Évaluer l’impact de différentes méthodes de traitement des données sur les valeurs de pointe obtenues lors d’un test maximal fait sur vélo stationnaire chez des enfants. Méthodes : Les données obtenues avec un système de mesure des échanges gazeux pour 124 tests maximaux ont été comparées entre le « cycle à cycle » respiratoire, des moyennes de temps sur 5, 10, 15, 20, 30, 45 et 60 secondes et des moyennes sur 3, 7, 11 et 21 respirations. Un modèle linéaire général avec mesures répétées a été utilisé afin d’évaluer les différences intra-sujets. Une analyse de la variance à deux facteurs fut appliquée pour évaluer la présence d’une interaction du sexe et du statut pondéral sur l’impact du traitement des données. Résultats : Comparativement à la VO2de pointe, les valeurs de pointe du ratio d’échange respiratoire et de la fréquence cardiaque étaient moins affectées par le choix du traitement. La plus haute valeur de VO2de pointe fut obtenue avec les données en respiration par respiration, avec une différence significative de 41,1% par rapport à la valeur obtenue sur 30 secondes. Aucune interaction du sexe et du statut pondéral n’a été démontré. Par contre, un effet simple entre le statut pondéral et les moyennes sur le nombre de respirations a été trouvé. Conclusion : Chez les enfants, des valeurs de VO2de pointe plus élevées seront obtenues avec l’utilisation d’intervalles plus courts, alors que les valeurs du ratio d’échange respiratoire et de la fréquence cardiaque seront plus basses. Cette étude confirme l’importance de considérer l’impact du choix de la méthode de traitement sur les valeurs obtenues lors d’un test avec mesure directe des échanges gazeux respiratoires.Purpose: The primary aim of this study was to evaluate the impact of different data averaging methods on the peak data obtained during a maximal exercise test in children. Methods: The results of a maximal cycling test of 124 children were included. Comparisons of the data obtained with a gas exchange system were made between breath-by-breath, time averages of 5-s, 10-s, 15-s, 20-s, 30-s, 45-s and 60-s and breath averages of 3-breaths, 7-breaths, 11-breaths and 21-breaths. Using the linear general model, repeated measures were performed and within-subject differences were evaluated. To assess the presence of an interaction of sex and body weight status, a two-way ANOVA analysis was also conducted. Results: As opposed to the VO2peak value, the peak respiratory exchange ratio and heart rate values were less affected by the choice of the sampling interval. The highest VO2peak value was the one corresponding to breath-by-breath data, with a significant difference of 41.1% when compared to the VO2peak value averaged over 30-s. No interaction effect of sex and body weight status was found for either time averaging or breath averaging. However, the analysis showed a single main effect of body weight status for breath averaging intervals. Conclusions: In children, using shorter averaging intervals will yield higher VO2peak values, whereas values of respiratory exchange ratio and heart rate peak will be lower. The present study confirmed that the way in which the VO2 data obtained from a maximal exercise test is processed will most certainly affect its values, therefore attention should be given to this significant impact

Minimizing the risk of exercise-induced glucose fluctuations in people living with type 1 diabetes using continuous subcutaneous insulin infusion: an overview of strategies

Physical activity (PA) is important for individuals living with type 1 diabetes (T1D) due to its various health benefits.Nonetheless, maintaining adequate glycemic control around PA remains a challenge for many individuals living with T1Dbecause of the difficulty to properly manage circulating insulin levels around PA. While the most common problem is increasedincidence of hypoglycemia during and after most types of PA, hyperglycemia can also occur. Accordingly, a large proportion ofpeople living with T1D are sedentary partly due to the fear of PA-associated hypoglycemia. Continuous subcutaneous insulininfusion (CSII) offers a higher precision and flexibility to adjust insulin basal rates and boluses according to the individual’sspecific needs around PA practice. Indeed, for physically active patients with T1D, CSII can be a preferred option to facilitateglucose regulation. To our knowledge, there are no guidelines to manage exercise-induced hypoglycemia during PA, specificallyfor individuals living with T1D and using CSII. This review highlights the current state of knowledge on exercise-related glucosevariations, especially the hypoglycemic risk as well as its underlying physiology. Further, we detail the currentrecommendations for insulin modulations according to the different PA modalities (type, intensity, duration, frequency) inindividuals living with T1D using CSII

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

For individuals living with type 1 diabetes, closed-loop insulin delivery improves glycaemic control. Nonetheless, maintenance of glycaemic control during exercise while a prandial insulin bolus remains active is a challenge even to closed-loop systems. We investigated the effect of exercise announcement on the efficacy of a closed-loop system, to reduce hypoglycaemia during postprandial exercise. A single-blind randomised, crossover open-label trial was carried out to compare three strategies applied to a closed-loop system at mealtime in preparation for exercise taken 90 min after eating at a research testing centre: (1) announced exercise to the closed-loop system (increases target glucose levels) in addition to a 33% reduction in meal bolus (A-RB); (2) announced exercise to the closed-loop system and a full meal bolus (A-FB); (3) unannounced exercise and a full meal bolus (U-FB). Participants performed 60 min of exercise at 60% [Formula: see text] 90 min after eating breakfast. The investigators were not blinded to the interventions. However, the participants were blinded to the sensor glucose readings and to the insulin infusion rates throughout the intervention visits. The trial was completed by 37 adults with type 1 diabetes, all using insulin pumps: mean±SD, 40.0 ± 15.0 years of age, HbA 57.1 ± 10.8 mmol/mol (7.3 ± 1.0%). Reported results were based on plasma glucose values. During exercise and the following 1 h recovery period, time spent in hypoglycaemia (10 mmol/l) by 21% (p = 0.001). No side effects were reported during the applied strategies. Combining postprandial exercise announcement, which increases closed-loop system glucose target levels, with a 33% meal bolus reduction significantly reduced time spent in hypoglycaemia compared with the other two strategies, yet at the expense of more time spent in hyperglycaemia. ClinicalTrials.gov NCT0285530 FUNDING: JDRF (2-SRA-2016-210-A-N), the Canadian Institutes of Health Research (354024) and the Fondation J.-A. DeSève chair held by RR-L

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

International audienceStudies 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. Data from 25 adults (10 males, 15 females, HbA: 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 (10.0 mmol/L) between conditions. Self-reported data about mitigation strategies applied to reduce the risk of nocturnal hypoglycemia was also analyzed. 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). 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

Effect of caloric restriction with or without physical activity on body composition and epicardial fat in type 2 diabetic patients: A pilot randomized controlled trial

There is debate over the independent and combined effects of caloric restriction (CR) and physical activity (PA) on reduction in fat mass and in epicardial fat thickness. We compared the impact of a similar energy deficit prescription by CR or by CR combined with PA on total fat mass, epicardial fat thickness, and cardiometabolic profile in individuals with type 2 diabetes. In this 16-week randomized controlled study, 73 individuals were randomly enrolled to receive: 1) a monthly motivational phone call (Control), 2) a caloric deficit of −700 kilocalories/day (CR), or 3) a caloric deficit of −500 kilocalories/day combined with a PA program of −200 kilocalories/day (CR&PA). Total fat mass, epicardial fat, and cardiometabolic profile were measured at baseline and after 16 weeks. While comparable weight loss occurred in both intervention groups (−3.9 ± 3.5 kg [CR], −5.1 ± 4.7 kg [CR&PA], −0.2 ± 2.9 kg [Control]), changes in total fat mass were significantly different between all groups (−2.4 ± 2.9 kg [CR], −4.5 ± 3.4 kg [CR&PA], +0.1 ± 2.1 kg [Control]; p < 0.05) as well as epicardial fat thickness (−0.4 ± 1.6 mm [CR], −1.4 ± 1.4 mm [CR&PA], +1.1 ± 1.3 mm [Control]; p < 0.05). There were no significant differences in trends for cardiometabolic parameters improvement between groups. For a similar energy deficit prescription and comparable weight loss, the combination of CR&PA provides a greater reduction in fat mass and epicardial fat thickness than CR alone in individuals with comparable weight loss and with a similar energy deficit prescription. These results, however, do not translate into significant improvements in cardiometabolic profiles. NCT01186952. •We prescribed the same energy deficit either with CR alone or combined with PA in individuals living with type 2 diabetes.•For a similar energy deficit and weight loss, the combination of CR and PA provides a greater reduction in fat mass than CR.•Combination of PA with CR produce a greater reduction in epicardial fat thickness than CR alone