Towards a Model-Based Meal Detector for Type I Diabetics

Blood glucose management systems are an important class of Medical Cyber-Physical Systems that provide vital everyday decision support service to diabetics. An artificial pancreas, which integrates a continuous glucose monitor, a wearable insulin pump, and control algorithms running on embedded computing devices, can significantly improve the quality of life for millions of Type 1 diabetics. A primary problem in the development of an artificial pancreas is the accurate detection and estimation of meal carbohydrates, which cause significant glucose system disturbances. Meal carbohydrate detection is challenging since post-meal glucose responses greatly depend on patient-specific physiology and meal composition. In this paper, we develop a novel meal-time detector that leverages a linearized physiological model to realize a (nearly) constant false alarm rate (CFAR) performance despite unknown model parameters and uncertain meal inputs. Insilico evaluations using 10, 000 virtual subjects on an FDA-accepted maximal physiological model illustrate that the proposed CFAR meal detector significantly outperforms a current state-of-the-art meal detector that utilizes a voting scheme based on rate-of-change (RoC) measures. The proposed detector achieves 99.6% correct detection rate while averaging one false alarm every 24 days (a 1.4% false alarm rate), which represents an 84% reduction in false alarms and a 95% reduction in missed alarms when compared to the RoC approach

A Data-Driven Behavior Modeling and Analysis Framework for Diabetic Patients on Insulin Pumps

About 30%-40% of Type 1 Diabetes (T1D) patients in the United States use insulin pumps. Current insulin infusion systems require users to manually input meal carb count and approve or modify the system-suggested meal insulin dose. Users can give correction insulin boluses at any time. Since meal carbohydrates and insulin are the two main driving forces of the glucose physiology, the user-specific eating and pump-using behavior has a great impact on the quality of glycemic control. In this paper, we propose an “Eat, Trust, and Correct” (ETC) framework to model the T1D insulin pump users’ behavior. We use machine learning techniques to analyze the user behavior from a clinical dataset that we collected on 55 T1D patients who use insulin pumps. We demonstrate the usefulness of the ETC behavior modeling framework by performing in silico experiments. To this end, we integrate the user behavior model with an individually parameterized glucose physiological model, and perform probabilistic model checking on the user-in-the-loop system. The experimental results show that switching behavior types can significantly improve a patient’s glycemic control outcomes. These analysis results can boost the effectiveness of T1D patient education and peer support

Diabetes, Pancreatogenic Diabetes, and Pancreatic Cancer

The relationships between diabetes and pancreatic ductal adenocarcinoma (PDAC) are complex. Longstanding type 2 diabetes (T2DM) is a risk factor for pancreatic cancer, but increasing epidemiological data point to PDAC as also a cause of diabetes due to unknown mechanisms. New-onset diabetes is of particular interest to the oncology community as the differentiation of new-onset diabetes caused by PDAC as distinct from T2DM may allow for earlier diagnosis of PDAC. To address these relationships and raise awareness of the relationships between PDAC and diabetes, a symposium entitled Diabetes, Pancreatogenic Diabetes, and Pancreatic Cancer was held at the American Diabetes Association's 76th Scientific Sessions in June 2016. This article summarizes the data presented at that symposium, describing the current understanding of the interrelationships between diabetes, diabetes management, and pancreatic cancer, and identifies areas where additional research is needed

Characterizing Glycemic Control and Sleep in Adults with Long-Standing Type 1 Diabetes and Hypoglycemia Unawareness Initiating Hybrid Closed Loop Insulin Delivery

Nocturnal hypoglycemia is life threatening for individuals with type 1 diabetes (T1D) due to loss of hypoglycemia symptom recognition (hypoglycemia unawareness) and impaired glucose counter regulation. These individuals also show disturbed sleep, which may result from glycemic dysregulation. Whether use of a hybrid closed loop (HCL) insulin delivery system with integrated continuous glucose monitoring (CGM) designed for improving glycemic control, relates to better sleep across time in this population remains unknown. The purpose of this study was to describe long-term changes in glycemic control and objective sleep after initiating hybrid closed loop (HCL) insulin delivery in adults with type 1 diabetes and hypoglycemia unawareness. To accomplish this, six adults (median age = 58 y) participated in an 18-month ongoing trial assessing HCL effectiveness. Glycemic control and sleep were measured using continuous glucose monitoring and wrist accelerometers every 3 months. Paired sample t-tests and Cohen’s d effect sizes modeled glycemic and sleep changes and the magnitude of these changes from baseline to 9 months. Reduced hypoglycemia (d = 0:47‐0:79), reduced basal insulin requirements (d = 0:48), and a smaller glucose coefficient of variation (d = 0:47) occurred with medium-large effect sizes from baseline to 9 months. Hypoglycemia awareness improved from baseline to 6 months with medium-large effect sizes (Clarke score (d = 0:60), lability index (d = 0:50), HYPO score (d = 1:06)). Shorter sleep onset latency (d = 1:53; p \u3c 0:01), shorter sleep duration (d = 0:79), fewer total activity counts (d = 1:32), shorter average awakening length (d = 0:46), and delays in sleep onset (d = 1:06) and sleep midpoint (d = 0:72) occurred with medium-large effect sizes from baseline to 9 months. HCL led to clinically significant reductions in hypoglycemia and improved hypoglycemia awareness. Sleep showed a delayed onset, reduced awakening length and onset latency, and maintenance of high sleep efficiency after initiating HCL. Our findings add to the limited evidence on the relationships between diabetes therapeutic technologies and sleep health. This trial is registered with ClinicalTrials.gov (NCT03215914)

RS rearrangement frequency as a marker of receptor editing in lupus and type 1 diabetes

Continued antibody gene rearrangement, termed receptor editing, is an important mechanism of central B cell tolerance that may be defective in some autoimmune individuals. We describe a quantitative assay for recombining sequence (RS) rearrangement that we use to estimate levels of antibody light chain receptor editing in various B cell populations. RS rearrangement is a recombination of a noncoding gene segment in the κ antibody light chain locus. RS rearrangement levels are highest in the most highly edited B cells, and are inappropriately low in autoimmune mouse models of systemic lupus erythematosus (SLE) and type 1 diabetes (T1D), including those without overt disease. Low RS rearrangement levels are also observed in human subjects with SLE or T1D

Circulating B cells in type 1 diabetics exhibit fewer maturation-associated phenotypes

Although autoantibodies have been used for decades as diagnostic and prognostic markers in type 1 diabetes (T1D), further analysis of developmental abnormalities in B cells could reveal tolerance checkpoint defects that could improve individualized therapy. To evaluate B cell developmental progression in T1D, immunophenotyping was used to classify circulating B cells into transitional, mature naïve, mature activated, and resting memory subsets. Then each subset was analyzed for the expression of additional maturation-associated markers. While the frequencies of B cell subsets did not differ significantly between patients and controls, some T1D subjects exhibited reduced proportions of B cells that expressed transmembrane activator and CAML interactor (TACI) and Fas receptor (FasR). Furthermore, some T1D subjects had B cell subsets with lower frequencies of class switching. These results suggest circulating B cells exhibit variable maturation phenotypes in T1D. These phenotypic variations may correlate with differences in B cell selection in individual T1D patients

Bedtime habits in adults with and without type 2 diabetes

This study aimed to identify determinants of objectively-estimated bedtime habits and to determine if these bedtime habits differed between adults with and without type 2 diabetes. Adults with accelerometry data from the National Health and Nutrition Examination Survey 2003-2004 and 2005-2006 cohorts were classified as having no diabetes or type 2 diabetes and matched for age, gender, and BMI across the two groups. Multivariate linear regression models assessed bedtime habits (time-in-bed, early versus late bedtime periods, regularity), chronotype (mid-points), and type 2 diabetes status. While the results indicated no differences in bedtime habits between adults with and without type 2 diabetes, an interesting finding was the support for an association between objectively-estimated earlier bedtime midpoints and greater physical activity

Effect of angiotensin receptor blockade on insulin sensitivity and endothelial function in abdominally obese hypertensive patients with impaired fasting glucose

AngII (angiotensin II) may contribute to cardiovascular risk in obesity via adverse effects on insulin sensitivity and endothelial function. In the present study, we examined the effects of ARB (angiotensin receptor blocker) therapy (losartan, 100 mg/day) on insulin sensitivity and endothelial function in 53 subjects with stage I hypertension, abdominal obesity and impaired fasting glucose. The study design was a randomized double-blinded parallel design placebo-controlled multi-centre trial of 8 weeks duration. We used the hyperinsulinaemic-euglycaemic clamp technique to measure insulin sensitivity (expressed as the 'M/I' value) and RH-PAT (reactive hyperaemia-peripheral arterial tonometry) to measure endothelial function. Additional measures included HOMA (homoeostasis model assessment)-B, an index of pancreatic β-cell function, and markers of inflammation [e.g. CRP (C-reactive protein)] and oxidative stress (e.g. F2-isoprostanes). ARB therapy did not alter insulin sensitivity [5.2 (2.7) pre-treatment and 4.6 (1.6) post-treatment] compared with placebo therapy [6.1 (2.9) pre-treatment and 5.3 (2.7) post-treatment; P value not significant], but did improve the HOMA-B compared with placebo therapy (P=0.05). ARB therapy also did not change endothelial function [RH-PAT, 2.15 (0.7) pre-treatment and 2.11 (0.7) post-treatment] compared with placebo therapy [RH-PAT, 1.81 (0.5) pre-treatment and 1.76 (0.7) post-treatment; P value not significant]. Markers of inflammation and oxidative stress were not significantly changed by ARB therapy. In conclusion, ARB therapy did not alter peripheral insulin sensitivity or endothelial function in this cohort of patients with essential hypertension, abdominal obesity and impaired fasting glucose, but did improve pancreatic β-cell function