Demonstrating the Central Limit Theorem Using MATLAB

In this paper MATLAB is used in a demonstration of the central limit theorem (CLT). MATLAB is a powerful computer program used in educa­tion and industry. MATLAB allows us to increase the sample size and not sacrifice speed of computation while demonstrating the basic concept of the CLT as it applies to probability and statistics. We will give its history as well as a clear understanding of its power. In addition to reproducing previous work[l], we will provide the MATLAB code used to perform further dem­onstrations. Our program will select 30 integers between one and six, as in Lazari et. al. It will then compute each individual mean (L1) and store it in a list (L5) while repeating itself n times, where n is the total number of en­sembles. Upon completion, distribution plots are obtained for then means as well as a combined histogram for each individual (L5). For a very large n, the program does indeed demonstrate that the distribution of the sample means is really normal as in Lazari et al

The OmniPod Insulin Management System: the latest innovation in insulin pump therapy

This review of insulin pump therapy focuses on the OmniPod® Insulin Management System (Insulet Corp., Bedford, MA, USA). The OmniPod System is the first commercially available “patch pump.” It is a fully integrated wearable pump, controlled wirelessly through a handheld device containing a built-in blood glucose meter. This is an evaluation of the OmniPod System, with the aim of providing an educational tool for physicians who are considering recommending this product to their patients. The review includes a discussion of the traditional insulin pump configuration and its limitations, a detailed overview of the OmniPod System, references to clinical study data, planned product enhancements, its use as an insulin delivery system in the Juvenile Diabetes Research Foundation’s Artificial Pancreas Project, and its use to deliver additional compounds

Clinical targets for continuous glucose monitoring data interpretation : recommendations from the international consensus on time in range

Improvements in sensor accuracy, greater convenience and ease of use, and expanding reimbursement have led to growing adoption of continuous glucose monitoring (CGM). However, successful utilization of CGM technology in routine clinical practice remains relatively low. This may be due in part to the lack of clear and agreed-upon glycemic targets that both diabetes teams and people with diabetes can work toward. Although unified recommendations for use of key CGM metrics have been established in three separate peer-reviewed articles, formal adoption by diabetes professional organizations and guidance in the practical application of these metrics in clinical practice have been lacking. In February 2019, the Advanced Technologies & Treatments for Diabetes (ATTD) Congress convened an international panel of physicians, researchers, and individuals with diabetes who are expert in CGM technologies to address this issue. This article summarizes the ATTD consensus recommendations for relevant aspects of CGM data utilization and reporting among the various diabetes populations

Improved blood glucose control for critically ill subjects

For patients in intensive care units (ICUs), control of blood glucose level is an important factor in reducing serious complications and mortality. Standard protocols for glucose control in ICUs have been based on infrequent glucose measurements, look-up tables to determine the appropriate insulin infusion rates, and bedside administration of the insulin infusion by ICU staff. In this paper a new automatic control strategy is proposed based on frequent glucose measurements and a self-tuning control technique. During a short initial time period when manual glucose control is performed using a standard protocol, a simple dynamic model of the glucose\u2013insulin system is identified in real time using recursive least squares. Then an adaptive PID controller is tuned, based on the model parameters, and the controller is turned on. A simulation study based on detailed physiological models of the glucose\u2013insulin dynamics demonstrates that the proposed control strategy performs better than standard protocols for insulin infusion