Identification of Main Factors Explaining Glucose Dynamics During and Immediately After Moderate Exercise in Patients With Type 1 Diabetes

International audienceBACKGROUND:Physical activity is recommended for patients with type 1 diabetes (T1D). However, without proper management, it can lead to higher risk for hypoglycemia and impaired glycemic control. In this work, we identify the main factors explaining the blood glucose dynamics during exercise in T1D. We then propose a prediction model to quantify the glycemic drop induced by a mild to moderate physical activity.METHODS:A meta-data analysis was conducted over 59 T1D patients from 4 different studies in the United States and France (37 men and 22 women; 47 adults; weight, 71.4 ± 10.6 kg; age, 42 ± 10 years; 12 adolescents: weight, 60.7 ± 12.5 kg; age, 14.0 ± 1.4 years). All participants had physical activity between 3 and 5 pm at a mild to moderate intensity for approximately 30 to 45 min. A multiple linear regression analysis was applied to the data to identify the main parameters explaining the glucose dynamics during such physical activity.RESULTS:The blood glucose at the beginning of exercise ([Formula: see text]), the ratio of insulin on board over total daily insulin ([Formula: see text]) and the age as a categorical variable (1 for adult, 0 for adolescents) were significant factors involved in glucose evolution at exercise (all P < .05). The multiple linear regression model has an R-squared of .6.CONCLUSIONS:The main factors explaining glucose dynamics in the presence of mild-to-moderate exercise in T1D have been identified. The clinical parameters are formally quantified using real data collected during clinical trials. The multiple linear regression model used to predict blood glucose during exercise can be applied in closed-loop control algorithms developed for artificial pancreas

Le pancréas artificiel, un rêve sur le point de devenir réalité

International audienceAlmost 45 000 patients with type 1 diabetes are concerned in France by outpatient insulin pump therapy. The first systems of insulin pump therapy guided by glycaemia have evolved driven by the work carried out by multi-disciplinary research teams. Today, the outpatient treatment of type 1 diabetes by an artificial pancreas is on the point of becoming reality

Individualization of tDCS intensity according to corticospinal excitability does not improve stimulation efficacy over the primary motor cortex

Transcranial direct current stimulation (tDCS) applied at the same intensity for an entire group of people results in wide interindividual variability, limiting stimulation efficacy. Evidence suggests that tDCS efficacy might be linked to individual corticospinal excitability (CSE) levels measured by transcranial magnetic stimulation (TMS). However, no study has attempted to individualize tDCS parameters according to the CSE level. We aimed to investigate whether the tDCS effect could be improved by individualizing stimulation intensity based on CSE measured at baseline. Fourteen participants were included in a crossover single-blinded design study where anodal (1 mA), individualized anodal (between 0.9 and 1.6 mA) and sham tDCS were applied for 14 min over the primary motor cortex. The resting motor threshold (RMT), stimulus intensity for a 1 mV response (SI1mV) and the input-output curve (I–O curve) were measured before, immediately after, 15 after and 30 min after tDCS using single pulses of TMS. The tDCS intensity in the individualized anodal condition was determined according to the RMT value at baseline (i.e., CSE level). RMT, SI1mV and I–O curve MEPs did not change after any tDCS paradigm. Our results are consistent with previous investigations that did not show an effect of tDCS on CSE and supports that tDCS protocols suffer from large interindividual variability and a lack of efficiency. This calls for further investigations to find the optimal tDCS setting to reduce the inconsistency in the results and obtain reproducible effects

Kernel methods for mixed feature selection

Abstract. This paper introduces two feature selection methods to deal with heterogeneous data that include continuous and categorical variables. We propose to plug a dedicated kernel that handles both kind of variables into a Recursive Feature Elimination procedure using either a non-linear SVM or Multiple Kernel Learning. These methods are shown to offer significantly better predictive results than state-of-the-art alternatives on a variety of high-dimensional classification tasks.

Improvement of Glucose Control and Reduction of Hypoglycemia Following Intravenous Immune Globulins in a Child With Type 1 Diabetes and High Levels of Insulin Antibodies

International audienceNon

Development of a Smartphone Application to Capture Carbohydrate, Lipid, and Protein Contents of Daily Food : Need for Integration in Artificial Pancreas for Patients With Type 1 Diabetes?

International audienceBACKGROUND:Meal lipids (LIP) and proteins (PRO) may influence the effect of insulin doses based on carbohydrate (CHO) counting in patients with type 1 diabetes (T1D). We developed a smartphone application for CHO, LIP, and PRO counting in daily food and assessed its usability in real-life conditions and potential usefulness.METHODS:Ten T1D patients used the android application for 1 week to collect their food intakes. Data included meal composition, premeal and 2-hour postmeal blood glucose, corrections for hypo- or hyperglycemia after meals, and time for entering meals in the application. Meal insulin doses were based on patients' CHO counting (application in blinded mode). Linear mixed models were used to assess the statistical differences.RESULTS:In all, 187 meals were analyzed. Average computed CHO amount was 74.37 ± 31.78 grams; LIP amount: 20.26 ± 14.28 grams and PRO amount: 25.68 ± 16.68 grams. Average CHO, LIP, and PRO contents were significantly different between breakfast and lunch/dinner. The average time for meal entry in the application moved from 3-4 minutes to 2.5 minutes during the week. No significant impact of LIP and PRO was found on available blood glucose values.CONCLUSION:Our study shows CHO, LIP, and PRO intakes can be easily captured by an application on smartphone for meal entry used by T1D patients. Although LIP and PRO meal contents did not influence glucose levels when insulin doses were based on CHO in this pilot study, this application could be used for further investigation of this topic, including in closed-loop conditions

Long-Term Effects of Continuous Subcutaneous Insulin Infusion on Glucose Control and Microvascular Complications in Patients With Type 1 Diabetes

International audienc