Personalized short-term blood glucose prediction in T1DM

Insulin therapy for tight glycemia regulation in T1DM strongly depends on patients ́ daily decisions about insulin delivery adaptations in relation to: health status, current BG, target BG, insulin sensitivity, diet and foreseen activities. A personalized predictor providing near future BG predictions would support the users in the decision-making tasks while letting them maintaining control over their own treatments management

Bayesian Combination of Multiple Plasma Glucose Predictors

This paper presents a novel on-line approach of merging multiple different predictors of plasma glucose into a single optimized prediction. Various different predictors are merged by recursive weighting into a single prediction using regularized optimization. The approach is evaluated on 12 data sets of type I diabetes data, using three parallel predictors. The performance of the combined prediction is better, or in par, with the best predictor for each evaluated data set. The results suggest that the outlined method could be a suitable way to improve prediction performance when using multiple predictors, or as a means to reduce the risk associated with definite a priori model selection

Infinite Horizon Prediction of Post Prandial Breakfast Glucose Excursion

The objective of the study was to investigate infinite horizon prediction of post prandial blood glucose dynamics after breakfast ingestion using subspace based identification on empirical data

Comment faire émerger de la connaissance avec un algorithme d'intelligence artificielle et une visualisation de données pour la gestion du diabète

International audienc

Direct Continuous Time System Identification of MISO Transfer Function Models applied to Type 1 Diabetes

This paper shows an application of continuous-time system identification methods to Type 1 diabetes. First, a general MISO transfer function structure with individual nominator and denominator polynomials for each input is assumed and a parameter estimation procedure via an iterative prediction error method presented. Then, the proposed identification method is evaluated on a simple simulation example and finally applied on real-life data from Type 1 diabetes patients with the purpose of modeling blood glucose dynamics. To this aim, the method was extended to consider the time-varying nature of the system

Toward Defining the Threshold Between Low and High Glucose Variability in Diabetes

International audienceOBJECTIVE:To define the threshold for excess glucose variability (GV), one of the main features of dysglycemia in diabetes.RESEARCH DESIGN AND METHODS:A total of 376 persons with diabetes investigated at the University Hospital of Montpellier (Montpellier, France) underwent continuous glucose monitoring. Participants with type 2 diabetes were divided into several groups-groups 1, 2a, 2b, and 3 (n = 82, 28, 65, and 79, respectively)-according to treatment: 1) diet and/or insulin sensitizers alone; 2) oral therapy including an insulinotropic agent, dipeptidyl peptidase 4 inhibitors (group 2a) or sulfonylureas (group 2b); or 3) insulin. Group 4 included 122 persons with type 1 diabetes. Percentage coefficient of variation for glucose (%CV = [(SD of glucose)/(mean glucose)] × 100) and frequencies of hypoglycemia (interstitial glucose 36% were compared with those with %CV ≤36%.CONCLUSIONS:A %CV of 36% appears to be a suitable threshold to distinguish between stable and unstable glycemia in diabetes because beyond this limit, the frequency of hypoglycemia is significantly increased, especially in insulin-treated subjects

Effects of a multifaceted intervention on cardiovascular risk factors in high-risk hypertensive patients: the ESCAPE trial, a pragmatic cluster randomized trial in general practice

BACKGROUND: Several observational studies on hypertensive patients have shown a gap between therapeutic targets recommended in guidelines and those achieved in daily practice. The ESCAPE trial aimed to determine whether a multifaceted intervention focused on general practitioners (GPs), could increase significantly the proportion of hypertensive patients at high risk in primary prevention who achieved all their recommended therapeutic targets. METHODS: A pragmatic, cluster randomized trial involving 257 GPs randomized by region. The GPs in the intervention group had a one-day training session and were given an electronic blood pressure measurement device and a short recommendation leaflet. Along with usual follow-up, they focused one consultation on hypertension and other cardiovascular risk factors every six months for two years. They also received feedback at baseline and at one year on their patients’ clinical and biological parameters. Main outcome measures were change in the proportion of patients achieving all their therapeutic targets and each individual therapeutic target at two years, and quality of life. RESULTS: 1,832 high-risk hypertensive patients were included. After two years, the proportion of patients achieving all their therapeutic targets increased significantly in both groups, but significantly more in the intervention group: OR (odds-ratio) 1.89, (95% confidence interval (CI) 1.09 to 3.27, P = 0.02). Significantly more patients achieved their blood pressure targets in the intervention group than in the usual care group: OR 2.03 (95% CI 1.44 to 2.88, P < 0.0001). Systolic and diastolic blood pressures decreased significantly more in the intervention group than in the usual care group, by 4.8 mmHg and 1.9 mmHg, respectively (P < 0.0001 for both). There were no significant difference changes in physical and mental quality of life between groups. CONCLUSION: An easy-to-perform, multifaceted intervention targeting only GPs increased significantly the proportion of high-risk hypertensive patients in primary prevention achieving their recommended therapeutic targets. TRIAL REGISTRATION: This trial was registered with ClinicalTrials.gov, number NCT0034885