Predicting the output error of the suboptimal state estimator to improve the performance of the MPC-based artificial pancreas

The error of single step-ahead output prediction is the information traditionally used to correct the state estimate while exploiting the new measurement of the system output.However,its dynamics and statistical properties can be further studied and exploited in other ways.It is known that in the case of suboptimal state estimation,this output prediction error forms a correlated sequence,hence it can be effectively predicted in real time.Such a suboptimal scenario is typical in applications where the process noise model is not known or it is uncertain.Therefore,the paper deals with the problems of analytical and empirical modeling,identification,and prediction of the output error of the suboptimal state estimator for the sake of improving the output prediction accuracy and ultimately the performance of the model predictive control.The improvements are validated on an empirical model of type 1 diabetes within an in-silico experiment focused on glycemia prediction and implementation of the MPC-based artificial pancreas.

Evaluation of hybrid closed-loop insulin delivery system in type 1 diabetes in real-world clinical practice:One-year observational study

BACKGROUND In 2016,the Food and Drug Administration approved the first hybrid closed-loop(HCL)insulin delivery system for adults with type 1 diabetes(T1D).There is limited information on the impact of using HCL systems on patient-reported outcomes(PROs)in patients with T1D in real-world clinical practice.In this independent study,we evaluated glycemic parameters and PROs over one year of continuous use of Medtronic’s 670G HCL in real-world clinical practice.AIM To assess the effects of hybrid closed loop system on glycemic control and quality of life in adults with T1D.METHODS We evaluated 71 patients with T1D(mean age:45.5±12.1 years;59%females;body weight:83.8±18.7 kg,body mass index:28.7±5.6 kg/m2,A1C:7.6%±0.8%)who were treated with HCL at Joslin Clinic from 2017 to 2019.We measured A1C and percent of glucose time-in-range(%TIR)at baseline and 12 months.We measured percent time in auto mode(%TiAM)for the last two weeks preceding the final visit and assessed PROs through several validated quality-of-life surveys related to general health and diabetes management.RESULTS At 12 mo,A1C decreased by 0.3%±0.1%(P=0.001)and%TIR increased by 8.1%±2.5%(P=0.002).The average%TiAM was only 64.3%±32.8%and was not associated with A1C,%TIR or PROs.PROs,provided at baseline and at the end of the study,showed that the physical functioning submodule of 36Item Short-Form Health Survey increased significantly by 22.9%(P<0.001).Hypoglycemia fear survey/worry scale decreased significantly by 24.9%(P<0.000);Problem Areas In Diabetes reduced significantly by-17.2%(P=0.002).The emotional burden submodules of dietary diversity score reduced significantly by-44.7%(P=0.001).Furthermore,analysis of Clarke questionnaire showed no increase in awareness of hypoglycemic episodes.WHO-5 showed no improvements in subject’s wellbeing among participants after starting the 670G HCL system.Finally,analysis of Pittsburgh Sleep Quality Index showed no difference in sleep quality,sleep latency,or duration of sleep from baseline to 12 mo.CONCLUSION The use of HCL in real-world clinical practice for one year was associated with significant improvements in A1C,%TIR,physical functioning,hypoglycemia fear,emotional distress,and emotional burden related to diabetes management.However,these changes were not associated with time in auto mode.