Overnight Closed-Loop Control Improves Glycemic Control in a Multicenter Study of Adults With Type 1 Diabetes

Wearable and digital devices to monitor and treat metabolic diseases

Cardiometabolic diseases are a major public-health concern owing to their increasing prevalence worldwide. These diseases are characterized by a high degree of interindividual variability with regards to symptoms, severity, complications and treatment responsiveness. Recent technological advances, and the growing availability of wearable and digital devices, are now making it feasible to profile individuals in ever-increasing depth. Such technologies are able to profile multiple health-related outcomes, including molecular, clinical and lifestyle changes. Nowadays, wearable devices allowing for continuous and longitudinal health screening outside the clinic can be used to monitor health and metabolic status from healthy individuals to patients at different stages of disease. Here we present an overview of the wearable and digital devices that are most relevant for cardiometabolic-disease-related readouts, and how the information collected from such devices could help deepen our understanding of metabolic diseases, improve their diagnosis, identify early disease markers and contribute to individualization of treatment and prevention plans.

Effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes (T1D): systematic review and meta-analysis

BACKGROUND

The purpose of this study was to assess the effectiveness and safety of a model predictive control (MPC) algorithm for an artificial pancreas system in outpatients with type 1 diabetes.

METHODS

We searched PubMed, EMBASE, Cochrane Central, and the Web of Science to December 2021. The eligibility criteria for study selection were randomized controlled trials comparing artificial pancreas systems (MPC, PID, and fuzzy algorithms) with conventional insulin therapy in type 1 diabetes patients. The heterogeneity of the overall results was identified by subgroup analysis of two factors including the intervention duration (overnight and 24 h) and the follow-up periods (< 1 week, 1 week to 1 month, and > 1 month).

RESULTS

The meta-analysis included a total of 41 studies. Considering the effect on the percentage of time maintained in the target range between the MPC-based artificial pancreas and conventional insulin therapy, the results showed a statistically significantly higher percentage of time maintained in the target range in overnight use (10.03%, 95% CI [7.50, 12.56] p < 0.00001). When the follow-up period was considered, in overnight use, the MPC-based algorithm showed a statistically significantly lower percentage of time maintained in the hypoglycemic range (-1.34%, 95% CI [-1.87, -0.81] p < 0.00001) over a long period of use (> 1 month).

CONCLUSIONS

Overnight use of the MPC-based artificial pancreas system statistically significantly improved glucose control while increasing time maintained in the target range for outpatients with type 1 diabetes. Results of subgroup analysis revealed that MPC algorithm-based artificial pancreas system was safe while reducing the time maintained in the hypoglycemic range after an overnight intervention with a long follow-up period (more than 1 month).

An overview of advancements in closed-loop artificial pancreas system

Type 1 diabetes (T1D) is one of the world's health problems with a prevalence of 1.1 million for children and young adults under the age of 20. T1D is a health problem characterized by autoimmunity and the destruction of pancreatic cells that produce insulin. The available treatment is to maintain blood glucose within the desired normal range. To meet bolus and basal requirements, T1D patients may receive multiple daily injections (MDI) of fast-acting and long-acting insulin once or twice daily. In addition, insulin pumps can deliver multiple doses a day without causing injection discomfort in individuals with T1D. T1D patients have also monitored their blood glucose levels along with insulin replacement treatment using a continuous glucose monitor (CGM). However, this CGM has some drawbacks, like the sensor needs to be replaced after being inserted under the skin for seven days and needs to be calibrated (for some CGMs). The treatments and monitoring devices mentioned creating a lot of workloads to maintain blood glucose levels in individuals with T1D. Therefore, to overcome these problems, closed-loop artificial pancreas (APD) devices are widely used to manage blood glucose in T1D patients. Closed-loop APD consists of a glucose sensor, an insulin infusion device, and a control algorithm. This study reviews the progress of closed-loop artificial pancreas systems from the perspective of device properties, uses, testing procedures, regulations, and current market conditions.

Better TIR, HbA1c, and less hypoglycemia in closed-loop insulin system in patients with type 1 diabetes: a meta-analysis

The study aimed to evaluate the effectiveness and safety of long-term use of closed-loop insulin system (CLS) in non-pregnant patients with type 1 diabetes mellitus (T1DM) using systematic review and meta-analysis. A literature search was performed using MEDLINE, EMBASE, and the Cochrane Library. Randomized controlled trials (RCTs) on long-term use (not less than 8 weeks) of CLS in patients with T1DM were selected. Meta-analysis was performed with RevMan V.5.3.5 to compare CLS with controls (continuous subcutaneous insulin infusion with blinded continuous glucose monitoring or unblinded sensor-augmented pump therapy or multiple daily injections or predictive low-glucose suspend system) in adults and children with type 1 diabetes. Research quality evaluation was conducted using the Cochrane risk of bias tool. Eleven RCTs (817 patients) that satisfied the eligibility criteria were included in the meta-analysis. Compared with controls, the CLS group had a favorable effect on the proportion of time with sensor glucose level in 3.9-10 mmol/L (10.32%, 8.70% to 11.95%), above 10 mmol/L (-8.89%, -10.57% to -7.22%), or below 3.9 mmol/L (-1.09%, -1.54% to -0.64%) over 24 hours. The CLS group also had lower glycated hemoglobin levels (-0.30%, -0.41% to -0.19%), and glucose variability, coefficient of variation of glucose, and SD were lower by 1.41 (-2.38 to -0.44, p=0.004) and 6.37 mg/dL (-9.19 mg/dL to -3.55 mg/dL, p<0.00001). There were no significant differences between the CLS and the control group in terms of daily insulin dose, quality of life assessment, and satisfaction with diabetes treatment. CLS is a better solution than control treatment in optimizing blood glucose management in patients with T1DM. CLS could become a common means of treating T1DM in clinical practice.

Efficacy and safety of closed-loop insulin delivery versus sensor-augmented pump in the treatment of adults with type 1 diabetes: a systematic review and meta-analysis of randomized-controlled trials

BACKGROUND

Controversy remains regarding whether closed-loop (CL) insulin delivery or insulin sensor-augmented pump (SAP) delivery is more efficient for clinical treatment. Therefore, we aimed to compare the efficacy and safety of CL insulin delivery systems versus insulin SAP delivery for adults with type 1 diabetes (T1D).

METHODS

Embase, Ovid MEDLINE, PubMed, ScienceDirect, Scopus, the Cochrane Library, and other databases were searched for related articles, and we analyzed the average blood glucose (BG), time in range (TIR), and adverse effects (AEs) as primary endpoints to evaluate efficacy and safety.

RESULTS

Of 1616 articles, 12 randomized-controlled trials (RCTs) were included in the final analysis. Regarding BG control efficacy, CL insulin delivery resulted better outcomes than SAP therapy with regard to the average BG value, which was detected and recorded by continuous glucose monitoring (mean difference [MD][mmol/L]:  - 0.25 95% confidence interval [CI]  - 0.42 to - 0.08, p = 0.003); TIR 3.9-10 mmol/L (MD [%]: 7.91 95% CI 4.45-11.37, p < 0.00001). Similar results were observed for the secondary outcomes including low blood glucose index (LBGI) (MD:  - 0.41 95% CI - 0.55 to - 0.26, p < 0.00001), high blood glucose index (HBGI) (MD:  - 2.56 95% CI - 3.38 to - 1.74, p < 0.00001), and standard deviation (SD) of glucose variability (MD [mmol/L]: -0.25 95% CI - 0.44 to - 0.06, p = 0.01). Furthermore, SAP therapy was associated with more adverse effects (risk ratio: 0.20 95% CI 0.07-0.52, p = 0.001) than CL insulin delivery, and one of the most common adverse effects was hypoglycemia.

CONCLUSIONS

CL insulin delivery appears to be a better treatment method than SAP therapy for adults with T1D because of its increased BG control efficacy and decreased number of hypoglycemic events.

Transactions between Maternal and Child Depressive Symptoms Emerge Early in Life

Maternal depression is a robust risk factor for children's internalizing symptoms; however, the intergenerational transmission of mood disorders is likely more complex than unidirectional parent-directed effects. Theoretical models support transactional associations between maternal and child symptomatology over time but have not been well examined, especially in younger high-risk samples. The present investigation examined predictive transactional relations between maternal depression and children's internalizing in toddlerhood and early childhood using a cross-lagged panel model. Participants were 162 low-income, largely racial/ethnic minority mothers and their offspring (32% African American, 16% White, 52% Other/Multiethnic; 53% female) who were assessed when children were 18 months and 4 years old. There were significant cross-sectional relations between maternal depressive and child internalizing symptoms when children were 18 months but not 4 years of age. Cross-lagged associations were evident such that maternal depression symptoms at 18 months were positively associated with internalizing symptoms among children at 4 years, adjusting for prior maternal symptom levels and the cross-sectional correlations between maternal-child symptoms at 18 months. Within the same model, children's internalizing symptoms at 18 months were also positively associated with maternal depressive symptoms at 4 years, adjusting for prior child symptom levels and cross-sectional correlations. This study is among the first to demonstrate that transactional relations between maternal and child mood symptoms occur as early as toddlerhood/early childhood. Findings highlight the potential utility of inclusive, family-focused interventions that support both parents and children in the treatment of early emotional problems.

Physical Activity, Dietary Patterns, and Glycemic Management in Active Individuals with Type 1 Diabetes: An Online Survey

Individuals with type 1 diabetes (T1D) are able to balance their blood glucose levels while engaging in a wide variety of physical activities and sports. However, insulin use forces them to contend with many daily training and performance challenges involved with fine-tuning medication dosing, physical activity levels, and dietary patterns to optimize their participation and performance. The aim of this study was to ascertain which variables related to the diabetes management of physically active individuals with T1D have the greatest impact on overall blood glucose levels (reported as A1C) in a real-world setting. A total of 220 individuals with T1D completed an online survey to self-report information about their glycemic management, physical activity patterns, carbohydrate and dietary intake, use of diabetes technologies, and other variables that impact diabetes management and health. In analyzing many variables affecting glycemic management, the primary significant finding was that A1C values in lower, recommended ranges (<7%) were significantly predicted by a very-low carbohydrate intake dietary pattern, whereas the use of continuous glucose monitoring (CGM) devices had the greatest predictive ability when A1C was above recommended (≥7%). Various aspects of physical activity participation (including type, weekly time, frequency, and intensity) were not significantly associated with A1C for participants in this survey. In conclusion, when individuals with T1D are already physically active, dietary changes and more frequent monitoring of glucose may be most capable of further enhancing glycemic management.

Making Diabetes Care Fit—Are We Making Progress?

The care of patients with diabetes requires plans of care that make intellectual, practical, and emotional sense to patients. For these plans to fit well, patients and clinicians must work together to develop a common understanding of the patient’s problematic human situation and co-create a plan of care that responds well to it. This process, which starts at the point of care, needs to continue at the point of life. There, patients work to fit the demands of their care plan along with the demands placed by their lives and loves. Thought in this way, diabetes care goes beyond the control of metabolic parameters and the achievement of glycemic control targets. Instead, it is a highly individualized endeavor that must arrive at a care plan that reflects the biology and biography of the patient, the best available research evidence, and the priorities and values of the patient and her community. It must also be feasible within the life of the patient, minimally disrupting those aspects of the patient life that are treasured and justify the pursuit of care in the first place. Patient-centered methods such as shared decision making and minimally disruptive medicine have joined technological advances, patient empowerment, self-management support, and expert patient communities to advance the fit of diabetes care both at the point of care and at the point of life.

Glycemic Status Assessment by the Latest Glucose Monitoring Technologies

The advanced and performing technologies of glucose monitoring systems provide a large amount of glucose data that needs to be properly read and interpreted by the diabetology team in order to make therapeutic decisions as close as possible to the patient's metabolic needs. For this purpose, new parameters have been developed, to allow a more integrated reading and interpretation of data by clinical professionals. The new challenge for the diabetes community consists of promoting an integrated and homogeneous reading, as well as interpretation of glucose monitoring data also by the patient himself. The purpose of this review is to offer an overview of the glycemic status assessment, opened by the current data management provided by latest glucose monitoring technologies. Furthermore, the applicability and personalization of the different glycemic monitoring devices used in specific insulin-treated diabetes mellitus patient populations will be evaluated.

Beyond HbA1c : using continuous glucose monitoring metrics to enhance interpretation of treatment effect and improve clinical decision-making

Assessment of glycaemic outcomes in the management of Type 1 and Type 2 diabetes has been revolutionized in the past decade with the increasing availability of accurate, user-friendly continuous glucose monitoring (CGM). This advancement has brought a need for new techniques to appropriately analyse and understand the voluminous and complex CGM data for application in research-related goals and clinical guidance for individuals. Traditionally, HbA_1c was established using the Diabetes Control and Complications Trial (DCCT) and other trials as the ultimate measure of glycaemic control in terms of efficacy and, by default, risk of microvascular complications of diabetes. However, it is acknowledged that HbA_1c alone is inadequate at describing an individual's daily glycaemic variation and risks for hypo- and hyperglycaemia, and it does not provide the guidance needed to decrease those risks. CGM data provide means by which to characterize an individual's daily glycaemic excursions on a different time scale measured in minutes rather than months. As a consequence, clinical reports, such as the ambulatory glucose profile, increasingly include summary statistics related to averages (mean glucose, time in range) as well as markers related to glycaemic variability (coefficient of variation, standard deviation). However, there is a need to translate those metrics into specific risks that can be addressed in an actionable plan by individuals with diabetes and providers. This review presents several clinical scenarios of glycaemic outcomes from CGM data that can be analysed to describe glycaemic variability and its attendant risks of hyperglycaemia and hypoglycaemia, moving towards relevant interpretation of the complex CGM data streams.

Artificial pancreas treatment for outpatients with type 1 diabetes: systematic review and meta-analysis

OBJECTIVE

To evaluate the efficacy and safety of artificial pancreas treatment in non-pregnant outpatients with type 1 diabetes.

DESIGN

Systematic review and meta-analysis of randomised controlled trials.

DATA SOURCES

Medline, Embase, Cochrane Library, and grey literature up to 2 February 2018.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Randomised controlled trials in non-pregnant outpatients with type 1 diabetes that compared the use of any artificial pancreas system with any type of insulin based treatment. Primary outcome was proportion (%) of time that sensor glucose level was within the near normoglycaemic range (3.9-10 mmol/L). Secondary outcomes included proportion (%) of time that sensor glucose level was above 10 mmol/L or below 3.9 mmol/L, low blood glucose index overnight, mean sensor glucose level, total daily insulin needs, and glycated haemoglobin. The Cochrane Collaboration risk of bias tool was used to assess study quality.

RESULTS

40 studies (1027 participants with data for 44 comparisons) were included in the meta-analysis. 35 comparisons assessed a single hormone artificial pancreas system, whereas nine comparisons assessed a dual hormone system. Only nine studies were at low risk of bias. Proportion of time in the near normoglycaemic range (3.9-10.0 mmol/L) was significantly higher with artificial pancreas use, both overnight (weighted mean difference 15.15%, 95% confidence interval 12.21% to 18.09%) and over a 24 hour period (9.62%, 7.54% to 11.7%). Artificial pancreas systems had a favourable effect on the proportion of time with sensor glucose level above 10 mmol/L (-8.52%, -11.14% to -5.9%) or below 3.9 mmol/L (-1.49%, -1.86% to -1.11%) over 24 hours, compared with control treatment. Robustness of findings for the primary outcome was verified in sensitivity analyses, by including only trials at low risk of bias (11.64%, 9.1% to 14.18%) or trials under unsupervised, normal living conditions (10.42%, 8.63% to 12.2%). Results were consistent in a subgroup analysis both for single hormone and dual hormone artificial pancreas systems.

CONCLUSIONS

Artificial pancreas systems are an efficacious and safe approach for treating outpatients with type 1 diabetes. The main limitations of current research evidence on artificial pancreas systems are related to inconsistency in outcome reporting, small sample size, and short follow-up duration of individual trials.

Human Subcutaneous Tissue Response to Glucose Sensors: Macrophages Accumulation Impact on Sensor Accuracy

BACKGROUND

Subcutaneous (s.c.) glucose sensors have become a key component in type 1 diabetes management. However, their usability is limited by the impact of foreign body response (FBR) on their duration, reliability, and accuracy. Our study gives the first description of human acute and subacute s.c. response to glucose sensors, showing the changes observed in the sensor surface, the inflammatory cells involved in the FBR and their relationship with sensor performance.

METHODS

Twelve obese patients (seven type 2 diabetes) underwent two abdominal biopsies comprising the surrounding area where they had worn two glucose sensors: the first one inserted 7 days before and the second one 24 h before biopsy procedure. Samples were processed and studied to describe tissue changes by two independent pathologists (blind regarding sensor duration). Macrophages quantification was studied by immunohistochemistry methods in the area surrounding the sensor (CD68, CD163). Sensor surface changes were studied by scanning electron microscopy. Seven-day continuous glucose monitoring records were considered inaccurate when mean absolute relative difference was higher than 10%.

RESULTS

Pathologists were able to correctly classify all the biopsies regarding sensor duration. Acute response (24 h) was characterized by the presence of neutrophils while macrophages were the main cell involved in subacute inflammation. The number of macrophages around the insertion hole was higher for less accurate sensors compared with those performing more accurately (32.6 ± 14 vs. 10.6 ± 1 cells/0.01 mm²; P < 0.05).

CONCLUSION

The accumulation of macrophages at the sensor-tissue interface is related with decrease in accuracy of the glucose measure.

Hope vs hype: where are we in type 1 diabetes?

Much progress has been made in type 1 diabetes research. Biological replacement of islet function has been achieved with pancreas transplantation and with islet transplantation. In the future, human embryonic stem cells and/or induced pluripotent stem cells may offer a potentially unlimited source of cells for islet replacement. Another potential strategy is to induce robust beta cell replication so that regeneration of islets can be achieved. Immune interventions are being studied with the hope of arresting the type 1 diabetes disease process to either prevent the disease or help preserve beta cell function. Mechanical replacement of islet cell function involves the use of glucose sensor-controlled insulin infusion systems. As all of these avenues are pursued, headlines often overstate the case, thus hyping any given advance, which provides enormous hope for patients and families seeking a cure for type 1 diabetes. Often, however, it is an animal study or a pilot trial that is being described. The reality is that translation to successful trials in human beings may not be readily achievable. This article discusses both the hype and the hopes in type 1 diabetes research.

The UVA/Padova Type 1 Diabetes Simulator Goes From Single Meal to Single Day

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 the previous simulator, which was accepted by the Food and Drug Administration in 2013, are described.

METHOD

Intraday variability of insulin sensitivity (S_I) has been modeled, based on clinical T1D data, accounting for both intra- and intersubject variability of daily S_I. Thus, time-varying distributions of both subject's basal insulin infusion and insulin-to-carbohydrate ratio were calculated and made available to the user. A model of "dawn" phenomenon based on clinical T1D data has been also included. Moreover, the model of subcutaneous insulin delivery has been updated with a recently developed model of commercially available fast-acting insulin analogs. Models of both intradermal and inhaled insulin pharmacokinetics have been included. Finally, new models of error affecting continuous glucose monitoring and self-monitoring of blood glucose devices have been added.

RESULTS

One hundred in silico adults, adolescent, and children have been generated according to the above modifications. The new simulator reproduces the intraday glucose variability observed in clinical data, also describing the nocturnal glucose increase, and the simulated insulin profiles reflect real life data.

CONCLUSIONS

The new modifications introduced in the T1D simulator allow to extend its domain of validity from "single-meal" to "single-day" scenarios, thus enabling a more realistic framework for in silico testing of advanced diabetes technologies including glucose sensors, new insulin molecules and artificial pancreas.

Keeping Up with the Diabetes Technology: 2016 Endocrine Society Guidelines of Insulin Pump Therapy and Continuous Glucose Monitor Management of Diabetes

PURPOSE OF REVIEW

Decades after the invention of insulin pump, diabetes management has encountered a technology revolution with the introduction of continuous glucose monitoring, sensor-augmented insulin pump therapy and closed-loop/artificial pancreas systems. In this review, we discuss the significance of the 2016 Endocrine Society Guidelines for insulin pump therapy and continuous glucose monitoring and summarize findings from relevant diabetes technology studies that were conducted after the publication of the 2016 Endocrine Society Guidelines.

RECENT FINDINGS

The 2016 Endocrine Society Guidelines have been a great resource for clinicians managing diabetes in this new era of diabetes technology. There is good body of evidence indicating that using diabetes technology systems safely tightens glycemic control while managing both type 1 and type 2 diabetes. The first-generation diabetes technology systems will evolve as we gain more experience and collaboratively work to improve them with an ultimate goal of keeping people with diabetes complication and burden-free until the cure for diabetes becomes a reality.