Glycemic control is often difficult to achieve in patients with diabetes, especially in the presence of comorbid diseases or conditions such as steroid-use or liver cirrhosis, or in patients receiving enteral nutrition. Moreover, reactive hypoglycemia due to late dumping syndrome in people having undergone gastrectomy is also a matter of concern. Empirically and theoretically, the typical glyce...

AIMS There is no standardized protocol for measuring glycemic index (GI) that takes time-of-day effects into account. The software DegifXL2 and Medtronic-Minimed's CGMS and Solutions, makes the GI calculation at breakfast and dinner time possible. The aim of this study was to assess the enhanced data processing software (DegifXL4) enabling the GI calculation at breakfast, lunch, afternoon snack...

Recently, much research has focused on causal graphical models (CGMs) as a computational-level description of how children represent cause and effect. While this research program has shown promise, there are aspects of causal reasoning that CGMs have difficulty accommodating. We propose a new formalism that amends CGMs. This edge replacement grammar formalizes one existing and one novel theoret...

OBJECTIVE To evaluate in inpatient and outpatient conditions, using only non-calibration data, the accuracy of the Continuous Glucose Monitoring System (CG-MS). RESEARCH DESIGN AND METHODS Twelve, 21 and 20 type 1 diabetic patients participated in 3- day inhospital, 6-day ambulatory (i.e., 2 sensors worn consecutively) and 3-day ambulatory studies. Capillary glucose tests (7-8/day) served as ...

Causal graphical models (CGMs) are a popular formalism used to model human causal reasoning and learning. The key property of CGMs is the causal Markov condition, which stipulates patterns of independence and dependence among causally related variables. Five experiments found that while adult's causal inferences exhibited aspects of veridical causal reasoning, they also exhibited a small but te...

BACKGROUND Continuous glucose monitors (CGMs) present a problem of lack of accuracy, especially in the lower range, sometimes leading to missed or false hypoglycemia. A new algorithm is presented here aimed at improving the measurement accuracy and hypoglycemia detection. Its core is the estimation of blood glucose (BG) in real time (RT) from CGM intensity readings using autoregressive (AR) mod...

BACKGROUND Pregnancy in Type 1 diabetic patients is a precarious condition, both for mother and fetus with increased the risk of prematurity and, immediately after delivery with risk of respiratory distress syndrome and hypoglycaemia in newborns. A strict control and monitoring of diabetes throughout pregnancy is important in reducing the impact of the disease on the fetus and newborn. In recen...