Control and Decision-Making Support in a Personalized Insulin Therapy System

2021 ◽  
Vol 26 (2) ◽  
pp. 162-171
Author(s):  
E.L. Litinskaia ◽  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Insulin Therapy ◽  
Closed Loop ◽  
Operation Time ◽  
Diabetes Mellitus Type 1 ◽  
Target Range ◽  
Loop Control ◽  
Closed Loop Systems ◽  
Glycemic Regulation

Insulin therapy automation is an actual research line in the glycemic control of diabetes mellitus type 1 patients. Development of closed-loop systems and methods will allow blood glucose maintaining in the physiological range. The work proposes the personalized insulin therapy system considered as a closed-loop control system based on feedback and external disturbances compensation principles. Automatic feedback-based glycemic control includes proportional reg-ulation of basal insulin infusion rate in relation to optimized thresholds inside the target range. To achieve bidirectional glycemic regulation the author proposes model predictive control for calculation of not only optimal profile of bolus infusion but also recommended corrective dose of carbohydrates. Besides, the comparative analysis of trends in measured and predicted profiles of blood glucose allows detecting and compensation of its unpredicted deviations. In silico testing of developed algorithms on nine virtual adults for 72 hours shows an ability for glucose maintaining in the target range for whole system operation time.

scholarly journals Transient bilateral diabetic cataracts in a Brazilian Terrier puppy

2005 ◽  
Vol 35 (3) ◽  
pp. 709-712
Author(s):  
Carla de Freitas Campos ◽  
Lilian Stefanoni Ferreira ◽  
Marlos Gonçalves Sousa ◽  
Fernanda Gomes Velasque Gama ◽  
José Luiz Laus ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Insulin Therapy ◽  
Lens Opacity ◽  
Human Beings ◽  
Glucose Levels ◽  
Blood Glucose Levels ◽  
And Control

A case of a Brazilian Terrier puppy presenting diabetic lens opacity that restored transparency after insulin therapy and control of blood glucose levels is reported. This entity has been rarely reported in human beings and has not been reported in dogs before. The rapid glycemic control may have been responsible for the transparency recovery.

scholarly journals Closed-loop management of inpatient hyperglycaemia

2019 ◽  
Vol 80 (11) ◽  
pp. 665-669
Author(s):  
CK Boughton ◽  
R Hovorka
Keyword(s):  
Health Care ◽  
Insulin Therapy ◽  
Health Care Professionals ◽  
Glucose Control ◽  
Closed Loop ◽  
Diabetes Management ◽  
Inpatient Setting ◽  
Glucose Levels ◽  
Closed Loop Systems ◽  
Inpatient Diabetes

The prevalence of diabetes in the inpatient setting is increasing, and suboptimal glucose control in hospital is associated with increased morbidity and mortality. Attaining the recommended glucose levels is challenging with standard insulin therapy. Hypoglycaemia and hyperglycaemia are common and diabetes management in hospital can be a considerable workload burden for health-care professionals. Fully automated insulin delivery (closed-loop) has been shown to be safe, and achieves superior glucose control than standard insulin therapy in the hospital, including in those patients receiving haemodialysis and enteral or parenteral nutrition where glucose control can be particularly challenging. Evidence that the improved glucose control achieved using closed-loop systems can translate into improved clinical outcomes for patients is key to support widespread adoption of this technology. The closed-loop approach has the potential to provide a paradigm shift in the management of inpatient diabetes, particularly in the most challenging inpatient populations, and may reduce staff work burden and the health-care costs associated with inpatient diabetes.

scholarly journals Utilizing Technology-Enabled Intervention to Improve Blood Glucose Self-Management Outcome in Type 2 Diabetic Patients Initiated on Insulin Therapy: A Retrospective Real-World Study

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Jian Lin ◽  
Xia Li ◽  
Shan Jiang ◽  
Xiao Ma ◽  
Yuxin Yang ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glycemic Control ◽  
Insulin Therapy ◽  
Fasting Blood Glucose ◽  
Blood Glucose Control ◽  
Diabetic Patients ◽  
Premixed Insulin ◽  
Type 2 Diabetic Patients ◽  
Self Monitoring

Background. The aim of this study was to assess the benefits of a mobile-enabled app through Lilly Connected Care Program (LCCP) in achieving blood glucose control and adhering to self-monitoring of blood glucose in patients with type 2 diabetes mellitus (T2DM). Methods. This retrospective study included T2DM patients who were initiated on insulin therapy (mostly premixed insulin) after failure to respond to oral antidiabetic drugs. Patients were provided with glucometers enabled with synchronous data transmission to healthcare providers and family members. The primary objective was to assess the benefits of LCCP based on changes in fasting blood glucose (FBG) and postprandial glucose (PPG) levels from baseline to 12 weeks. Paired t-test was used to assess the change in blood glucose (BG) from baseline to week 12. Results. In total, 14,085 T2DM patients were recruited. Compared with baseline, significant reductions in FBG and PPG were evident at week 12 (FBG: -0.39 mmol/L; PPG: −0.79 mmol/L; both P < 0.001 ). Furthermore, at week 12, the proportion of patients attaining a target glucose level of FBG <7.0 mmol/L and PPG <10.0 mmol/L was 25.37% and 59.68%, respectively, with a statistically significant increase compared with that at baseline (6.74% and 45.59%, respectively, both P < 0.001 ). The frequent monitoring of patients could gain a higher target achievement of FBG (28.1% vs 24.2%) and PPG (64.4% vs 55.1%) than the occasional monitoring patients. Additionally, the incidence of hypoglycemia gradually decreased and was significantly lower than the baseline level. Conclusions. In T2DM patients with poor glycemic control, the application of mobile enabled intervention (LCCP) along with insulin significantly reduced the hypoglycemia while improving glycemic control during period of naïve initiating insulin therapy. Additionally, the high frequency of BG self-monitoring was associated with better glycemic control.

scholarly journals Continuous Glucose Monitoring in Critically Ill Patients With COVID-19: Results of an Emergent Pilot Study

2020 ◽  
Vol 14 (6) ◽  
pp. 1065-1073
Author(s):  
Archana R. Sadhu ◽  
Ivan Alexander Serrano ◽  
Jiaqiong Xu ◽  
Tariq Nisar ◽  
Jessica Lucier ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Pilot Study ◽  
Insulin Therapy ◽  
Critically Ill ◽  
Continuous Glucose Monitoring ◽  
Critically Ill Patients ◽  
Point Of Care ◽  
Glucose Monitoring ◽  
Blood Glucose Monitoring ◽  
Target Range

Background: Amidst the coronavirus disease 2019 (COVID-19) pandemic, continuous glucose monitoring (CGM) has emerged as an alternative for inpatient point-of-care blood glucose (POC-BG) monitoring. We performed a feasibility pilot study using CGM in critically ill patients with COVID-19 in the intensive care unit (ICU). Methods: Single-center, retrospective study of glucose monitoring in critically ill patients with COVID-19 on insulin therapy using Medtronic Guardian Connect and Dexcom G6 CGM systems. Primary outcomes were feasibility and accuracy for trending POC-BG. Secondary outcomes included reliability and nurse acceptance. Sensor glucose (SG) was used for trends between POC-BG with nursing guidance to reduce POC-BG frequency from one to two hours to four hours when the SG was in the target range. Mean absolute relative difference (MARD), Clarke error grids analysis (EGA), and Bland-Altman (B&A) plots were calculated for accuracy of paired SG and POC-BG measurements. Results: CGM devices were placed on 11 patients: Medtronic ( n = 6) and Dexcom G6 ( n = 5). Both systems were feasible and reliable with good nurse acceptance. To determine accuracy, 437 paired SG and POC-BG readings were analyzed. For Medtronic, the MARD was 13.1% with 100% of readings in zones A and B on Clarke EGA. For Dexcom, MARD was 11.1% with 98% of readings in zones A and B. B&A plots had a mean bias of −17.76 mg/dL (Medtronic) and −1.94 mg/dL (Dexcom), with wide 95% limits of agreement. Conclusions: During the COVID-19 pandemic, CGM is feasible in critically ill patients and has acceptable accuracy to identify trends and guide intermittent blood glucose monitoring with insulin therapy.

scholarly journals Proportional Insulin Infusion in Closed-Loop Control of Blood Glucose

PLoS ONE ◽  
2017 ◽  
Vol 12 (1) ◽  
pp. e0169135
Author(s):  
Johan Grasman ◽  
Hannah L. Callender ◽  
Marco Mensink
Keyword(s):  
Blood Glucose ◽  
Insulin Infusion ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control

scholarly journals Formulation and Simulations of the Conserving Algorithm for Feedback Stabilization on Rigid Body Rotations

2014 ◽  
Vol 2014 ◽  
pp. 1-11
Author(s):  
Yong-Ren Pu ◽  
Thomas A. Posbergh
Keyword(s):  
Rigid Body ◽  
Closed Loop ◽  
Numerical Algorithms ◽  
Open Loop ◽  
Rigid Bodies ◽  
Feedback Stabilization ◽  
Conserved Quantities ◽  
Control Laws ◽  
Loop Control ◽  
Closed Loop Systems

The problem of stabilization of rigid bodies has received a great deal of attention for many years. People have developed a variety of feedback control laws to meet their design requirements and have formulated various but mostly open loop numerical algorithms for the dynamics of the corresponding closed loop systems. Since the conserved quantities such as energy, momentum, and symmetry play an important role in the dynamics, we investigate the conserved quantities for the closed loop control systems which formally or asymptotically stabilize rigid body rotation and modify the open loop numerical algorithms so that they preserve these important properties. Using several examples, the authors first use the open loop algorithm to simulate the tumbling rigid body actions and then use the resulting closed loop one to stabilize them.

In Silico Testing and in Vivo Experiments with Closed-Loop Control of Blood Glucose in Diabetes

2008 ◽  
Vol 41 (2) ◽  
pp. 4234-4239 ◽  
Author(s):  
B. Kovatchev ◽  
D.M. Raimondo ◽  
M. Breton ◽  
S. Patek ◽  
C. Cobelli
Keyword(s):  
Blood Glucose ◽  
In Silico ◽  
Closed Loop ◽  
Closed Loop Control ◽  
Loop Control ◽  
In Vivo Experiments
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