A5075609104- Diabetes Management and Research
- Pancreatic function and diabetes
- Diabetes and associated disorders
- Diabetes Treatment and Management
- Hyperglycemia and glycemic control in critically ill and hospitalized patients
- Heart Rate Variability and Autonomic Control
- Attention Deficit Hyperactivity Disorder
- Diabetes, Cardiovascular Risks, and Lipoproteins
- Diabetes Management and Education
- Diet and metabolism studies
- Neural and Behavioral Psychology Studies
- Older Adults Driving Studies
- ECG Monitoring and Analysis
- Gastrointestinal motility and disorders
- Mobile Health and mHealth Applications
- Mental Health Research Topics
- Advanced Control Systems Optimization
- Traffic and Road Safety
- Cardiovascular Function and Risk Factors
- Wireless Body Area Networks
- Spectroscopy Techniques in Biomedical and Chemical Research
- Gastroesophageal reflux and treatments
- Child Nutrition and Feeding Issues
- Cardiovascular Syncope and Autonomic Disorders
- Children's Physical and Motor Development
University of Virginia
2016-2025
Charlottesville Medical Research
2014-2024
University of Tampa
2020
University of Virginia Health System
2007-2018
Fukushima Medical University
2016
National Institutes of Health
2016
University of Pittsburgh
2016
Hunterdon Prevention Resources
2014
Saint Luke's Hospital
2012
KU Leuven
2012
Closed-loop systems that automate insulin delivery may improve glycemic outcomes in patients with type 1 diabetes.
Arguably, a minimally invasive system using subcutaneous (s.c.) continuous glucose monitoring (CGM) and s.c. insulin delivery via pump would be most feasible step to closed-loop control in type 1 diabetes mellitus (T1DM). Consequently, technology is focusing on developing an artificial pancreas algorithms link CGM with delivery. The future development of the will greatly accelerated by employing mathematical modeling computer simulation. Realistic simulation capable providing invaluable...
Recent studies have provided new insights into nonlinearities of insulin action in the hypoglycemic range and glucagon kinetics as it relates to response hypoglycemia. Based on these data, we developed a version UVA/PADOVA Type 1 Diabetes Simulator, which was submitted FDA 2013 (S2013). The model glucose hypoglycemia has been improved, implementing notion that insulin-dependent utilization increases nonlinearly when decreases below certain threshold. In addition, secretion models...
The Internet has become a major component to health care and important implications for the future of system. One most notable aspects Web is its ability provide efficient, interactive, tailored content user. Given wide reach extensive capabilities Internet, researchers in behavioral medicine have been using it develop deliver interactive comprehensive treatment programs with ultimate goal impacting patient behavior reducing unwanted symptoms. To date, however, many these interventions not...
The control of diabetes is an interdisciplinary endeavor, which includes a significant biomedical engineering component, with traditions success beginning in the early 1960s. It began modeling insulin-glucose system, and progressed to large-scale silico experiments, automated closed-loop (artificial pancreas). Here, we follow these efforts through last, almost 50 years. We begin now classic minimal approach discuss number subsequent models, have recently resulted first simulation model...
Recent studies show the importance of controlling blood glucose variability in relationship to both reducing hypoglycemia and attenuating risk for cardiovascular behavioral complications due hyperglycemia. It is therefore important design measures that are equally predictive low high excursions.We introduce average daily range (ADRR), a measure computed from routine self-monitored (SMBG) data. The ADRR was constructed using development dataset 39 31 adults with type 1 2 diabetes,...
The development of artificial pancreas has received a new impulse from recent technological advancements in subcutaneous continuous glucose monitoring and insulin pump delivery systems. However, the availability innovative sensors actuators, although essential, does not guarantee optimal glycemic regulation. Closed-loop control blood levels still poses challenges to automatic expert, most notable which are inevitable time delays between sensing actuation.A silico model is exploited for both...
Integrated closed-loop control (CLC), combining continuous glucose monitoring (CGM) with insulin pump (continuous subcutaneous infusion [CSII]), known as artificial pancreas, can help optimize glycemic in diabetes. We present a fundamental modular concept for CLC design, illustrated by clinical studies involving 11 adolescents and 27 adults at the Universities of Virginia, Padova, Montpellier. tested two constructs: standard to range (sCTR), designed augment plus CGM preventing extreme...
Abstract The significant and growing global prevalence of diabetes continues to challenge people with (PwD), healthcare providers, payers. While maintaining near-normal glucose levels has been shown prevent or delay the progression long-term complications diabetes, a proportion PwD are not attaining their glycemic goals. During past 6 years, we have seen tremendous advances in automated insulin delivery (AID) technologies. Numerous randomized controlled trials real-world studies that use AID...
Glucose control, glucose variability (GV), and risk for hypoglycemia are intimately related, it is now evident that GV important in both the physiology pathophysiology of diabetes. However, its quantitative assessment complex because blood (BG) fluctuations characterized by amplitude timing. Additional numerical complications arise from asymmetry BG scale. In this Perspective, we focus on acute manifestations GV, particularly hypoglycemia, review measures assessing routine self-monitored...
Background: A new version of the UVA/Padova Type 1 Diabetes (T1D) Simulator is presented which provides a more realistic testing scenario. The upgrades to previous simulator, was accepted by Food and Drug Administration in 2013, are described. Method: Intraday variability insulin sensitivity (S I ) has been modeled, based on clinical T1D data, accounting for both intra- intersubject daily S . Thus, time-varying distributions subject’s basal infusion insulin-to-carbohydrate ratio were...
The level of continuous glucose monitoring (CGM) accuracy needed for insulin dosing using sensor values (i.e., the permitting non-adjunct CGM use) is a topic ongoing debate. Assessment this in clinical experiments virtually impossible because magnitude errors cannot be manipulated and related prospectively to outcomes.A combination archival data (parallel CGM, pump, self-monitoring blood [SMBG] records, meals 56 pump users with type 1 diabetes) silico was used "replay" real-life treatment...
Background: The t:slim X2™ insulin pump with Control-IQ® technology from Tandem Diabetes Care is an advanced hybrid closed-loop system that was first commercialized in the United States January 2020. Longitudinal glycemic outcomes associated real-world use of this have yet to be reported. Methods: A retrospective analysis Control-IQ users who uploaded data Tandem's t:connect® web application as February 11, 2021 performed. Users age ≥6 years, >2 weeks continuous glucose monitoring (CGM) pre-...
Background: A composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful assisting with basic clinical interpretation CGM data. Methods: We assembled a data set 14-day 225 insulin-treated adults diabetes. Using balanced incomplete block design, 330 clinicians who were highly experienced analysis and ranked best to worst glycemia. used principal component multiple regressions develop model predict clinician ranking based on seven standard...
OBJECTIVE—The objective of this study was to introduce continuous glucose–error grid analysis (CG-EGA) as a method evaluating the accuracy glucose-monitoring sensors in terms both accurate blood glucose (BG) values and direction rate BG fluctuations illustrate application CG-EGA with data from TheraSense Freestyle Navigator. RESEARCH DESIGN AND METHODS—We approach design understanding that (CGSs) allow observation process time. We account for specifics characterization (location, speed,...