Remote glucose monitoring in camp setting reduces the risk of prolonged nocturnal hypoglycemia

Neural-Net Artificial Pancreas: A Randomized Crossover Trial of a First-in-Class Automated Insulin Delivery Algorithm

Background: Automated insulin delivery (AID) is now integral to the clinical practice of type 1 diabetes (T1D). The objective of this pilot-feasibility study was to introduce a new regulatory and clinical paradigm-a Neural-Net Artificial Pancreas (NAP)-an encoding of an AID algorithm into a neural network that approximates its action and assess NAP versus the original AID algorithm. Methods: The University of Virginia Model-Predictive Control (UMPC) algorithm was encoded into a neural network, creating its NAP approximation. Seventeen AID users with T1D were recruited and 15 participated in two consecutive 20-h hotel sessions, receiving in random order either NAP or UMPC. Their demographic characteristics were ages 22-68 years old, duration of diabetes 7-58 years, gender 10/5 female/male, White Non-Hispanic/Black 13/2, and baseline glycated hemoglobin 5.4%-8.1%. Results: The time-in-range (TIR) difference between NAP and UMPC, adjusted for entry glucose level, was 1 percentage point, with absolute TIR values of 86% (NAP) and 87% (UMPC). The two algorithms achieved similar times <70 mg/dL of 2.0% versus 1.8% and coefficients of variation of 29.3% (NAP) versus 29.1 (UMPC)%. Under identical inputs, the average absolute insulin-recommendation difference was 0.031 U/h. There were no serious adverse events on either controller. NAP had sixfold lower computational demands than UMPC. Conclusion: In a randomized crossover study, a neural-network encoding of a complex model-predictive control algorithm demonstrated similar performance, at a fraction of the computational demands. Regulatory and clinical doors are therefore open for contemporary machine-learning methods to enter the AID field. Clinical Trial Registration number: NCT05876273.

The effect of do-it-yourself real-time continuous glucose monitoring on psychological and glycemic variables in children with type 1 diabetes: A randomized crossover trial

BACKGROUND

Continuous glucose monitoring (CGM) decreases fear of hypoglycemia (FOH) and improves glycemic control among those affected by type 1 diabetes (T1D). No studies to date have examined the impact of using do-it-yourself real-time continuous glucose monitoring (DIY RT-CGM) on psychological and glycemic outcomes.

METHODS

Child-parent dyads were recruited for a multicentre randomized crossover trial. Children with T1D were current intermittently scanned CGM (isCGM) users and aged 2-13 years. Families received either 6 weeks of DIY RT-CGM with parental remote monitoring (intervention) or 6 weeks of isCGM plus usual diabetes care (control), followed by a 4-week washout period, then crossed over. The primary outcome was parental FOH. Secondary outcomes were glycemic control using traditional CGM metrics, as well as a range of other psychosocial measures.

FINDINGS

Fifty five child-parent dyads were recruited. The child mean age was 9.1 ± 2.8 years. Although, there was no effect on parental FOH, -0.1 (95%CI: -0.3, 0.1, p = 0.4), time-in-range (TIR) (%3.9-10 mmol/L) was significantly higher with DIY RT-CGM over isCGM (54.3% ± 13.7 vs. 48.1% ± 13.6), mean difference, 5.7% (95%CI 1.8, 9.6, p <0.004). There was no difference for time spent in hypoglycemia. Parent diabetes treatment satisfaction was significantly higher following DIY RT-CGM compared to isCGM, mean difference 5.3 (95%CI: 2.3, 8.2, p <0.001).

CONCLUSION

The use of DIY RT-CGM versus isCGM did not improve parental FOH; however, TIR and parental satisfaction with diabetes treatment were significantly improved. This suggests in the short term, DIY RT-CGM appears safe and may offer families some clinically important advantages over isCGM.

Remote Monitoring of Patient- and Family-Generated Health Data in Pediatrics

In this article, we provide an overview of remote monitoring of pediatric PGHD and family-generated health data, including its current uses, future opportunities, and implementation resources.

Glycemic variability and indices of glycemic control among pregnant women with type 1 diabetes (T1D) based on the use of continuous glucose monitoring share technology

BACKGROUND

Pregnancies complicated by type 1 diabetes (T1D) experience high levels of glycemic variability, which may be associated with adverse maternal and neonatal outcomes. Therefore, strategies that help pregnant women with T1D manage their glycemic control are of great interest.

METHODS

We examined associations with or without remote monitoring of Continuous Glucose Monitor (CGM) data by friends and family with indices of glycemic control and glycemic variability during pregnancies complicated by T1D in a pilot non-randomized trial (n = 28). During preconception or the first trimester, participants were placed in one of two groups based on device compatibility: (1) CGM Alone (n = 13): women without iPhone, iPad or iPod Touch; or (2) CGM Share (n = 15): women with iPhone, iPad, or iPod Touch and followers with devices compatible for data viewing. Linear mixed models were used to compare indices of glycemic control and glycemic variability over time between groups.

RESULTS

Participants using CGM Share had lower estimated HbA1c levels over time (p = .028), glucose management index (p = .041), and fewer glucose excursions >200 mg/dL in each trimester (p = .022) compared to those using CGM Alone. Participants using CGM Alone had higher high blood glucose index (p = .020), mean area under the curve (p = .026), and standard deviation (p = .046) compared to those using CGM Share. Other measures of glycemic variability did not differ between groups.

CONCLUSION

In this non-randomized pilot study, use of CGM Share was associated with improvements in several indices of glycemic control and glycemic variability.

Perspectives on Remote Glucose Monitoring in Youth With Type 1 Diabetes

OBJECTIVE

Continuous glucose monitoring (CGM) has become increasingly popular among youth with type 1 diabetes (T1D). Used with CGM, remote monitoring (RM) gives caregivers real-time access to patients' glucose values. Whereas RM may safeguard against hypo- and hyperglycemic events, little is known about how older children and adolescents, who are striving for independence, and their parents view the RM aspect of CGM. The goal of this study was to describe and explore parent and youth perceptions of RM.

METHODS

Youth with T1D and their parents participated separately in semi-structured interviews 2 months after starting CGM. Questions focused on decisions to use and experiences with RM.

RESULTS

Analysis of 43 parents and 41 youth (13.79 years ± 2.82) interviews revealed four themes, with 10 subthemes. Seven subthemes emerged in parent and youth interviews, and three emerged exclusively in parent interviews. The overarching themes included the impact of RM on (1) peace-of-mind, (2) parental anxiety, (3) communication; and addressed (4) technological limitations that prevented some from using RM. Regardless of youth age, youth and parents found comfort in parental knowledge of glucose values and parental abilities to assist youth (e.g., giving reminders to eat). Whereas RM could lead to conflicts due to excessive communication (e.g., texting), conflicts could be resolved through iterative parent-youth conversations.

CONCLUSION

RM may facilitate youth independence by providing a way for them to stay connected to their support system while acquiring developmentally appropriate skills. However, families should have iterative discussions about boundaries to mitigate parental over-involvement.

Association between attendance at an American diabetes camp and improvements in glycaemic control and treatment satisfaction

Introduction

Few studies have evaluated glycaemic control using continuous glucose monitoring (CGM) in individuals before and after attendance at a diabetes camp or by comparing control groups at home to control groups at camp.

Methods

Youth (6–17 years) with T1D and receiving insulin therapy were enrolled at a week‐long diabetes camp. They participated in three clinic visits: at the start of a week at home, by initiating a Dexcom G6 CGM system; at the start of a week at camp, where the home week G6 was removed and a camp week G6 was inserted; and after camp, where the camp week G6 was removed. We administered Problem Areas in Diabetes (PAID) surveys at the second and third visits. Participants with <80% CGM data coverage or who did not complete all PAID surveys were excluded from analysis. We compared glycaemic control and PAID scores between the week at home and week at camp.

Results

Of 76 enrolled campers, 69 completed the study and 52 had results that qualified for analysis. The mean participant age was 12.5 ± 2.2 years. Camp was associated with significantly improved treatment satisfaction, time in desired glucose range and insulin sensitivity. Time in hyperglycaemia and basal insulin requirements decreased significantly.

Conclusions

Diabetes camp is associated with significant improvements in diabetes treatment satisfaction and glycaemic control compared to home care.

Continuous glucose monitor use with and without remote monitoring in pregnant women with type 1 diabetes: A pilot study

BACKGROUND

To examine whether continuous glucose monitoring (CGM) with remote monitoring by followers (family/friends) changes glucose management, follower interventions, and health outcomes compared to CGM alone in pregnant women with diabetes.

METHODS

We prospectively stratified first trimester pregnant women with Type 1 Diabetes to CGM Share (remote monitoring) or CGM Alone. We enrolled a main follower per woman. We retrospectively acquired data for pregnant women who did not use CGM (no CGM). We compared hemoglobin A1c (HbA1c) between groups. We compared sensor glucose, follower interventions, and gestational outcomes between CGM Alone and CGM Share. Longitudinal mixed effects models were used for analyses of changes in outcomes over time.

RESULTS

HbA1c decreased in all groups throughout pregnancy and was significantly lower over time in women using CGM Share (n = 15) compared to CGM Alone (n = 13) or no CGM (n = 8) (p = 0.0042). CGM Share users had lower median sensor glucose levels (p = 0.0331) and percent time spent >180 mg/dL (p = 0.0228) across pregnancy. There were no significant differences in maternal and fetal outcomes between groups. CGM Share followers had more alerts for hypoglycemia, but did fewer interventions.

CONCLUSIONS

In this small pilot study, use of CGM with remote monitoring improved some glycemic metrics in pregnant women with diabetes.

Use of a do-it-yourself artificial pancreas system is associated with better glucose management and higher quality of life among adults with type 1 diabetes

BACKGROUND

Previous studies show that the use of do-it-yourself artificial pancreas system (DIYAPS) may be associated with better glycemic control characterized by improved estimated hemoglobin A1c (eHbA1c) and time in range among adults with type 1 diabetes (T1D). However, few studies have demonstrated the changes in laboratory-measured HbA1c, which is a more accepted index for glycemic control, after using a DIYAPS.

METHODS

This is a retrospective before-after study approaching patients who reported self-use of AndroidAPS. The main inclusion criteria included: T1D; aged ⩾18 years; having complete record of ⩾3 months of continuous AndroidAPS use; with laboratory-measured HbA1c and quality of life scale data before and after 3 months of AndroidAPS use; and not pregnant. The primary outcome was the change in HbA1c between baseline and 3 months after initiation of AndroidAPS use.

RESULTS

Overall, 15 patients (10 females) were included; the median age was 32.2 years (range: 19.2-69.4), median diabetes duration was 9.7 years (range: 1.8-23.7) and median baseline HbA1c was 7.3% (range: 6.4-10.1). The 3 months of AndroidAPS use was associated with substantial reductions in HbA1c [6.79% (SD: 1.29) versus 7.63% (SD: 1.06), p = 0.002] and glycemic variability when compared with sensor-augmented pump therapy. A lower level of fear of hypoglycemia [22.13 points (SD: 6.87) versus 26.27 points (SD: 5.82), p = 0.010] was also observed after using AndroidAPS.

CONCLUSIONS

The 3 months of AndroidAPS use was associated with significant improvements in glucose management and quality of life among adults with T1D.

Diabetes Technology: Monitoring, Analytics, and Optimal Control

Over the past 50 years, the diabetes technology field progressed remarkably through self-monitoring of blood glucose (SMBG), continuous subcutaneous insulin infusion (CSII), risk and variability analysis, mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). This review follows these developments, beginning with an overview of the functioning of the human metabolic system in health and in diabetes and of its detailed quantitative network modeling. The review continues with a brief account of the first AP studies that used intravenous glucose monitoring and insulin infusion, and with notes about CSII and CGM-the technologies that made possible the development of contemporary AP systems. In conclusion, engineering lessons learned from AP research, and the clinical need for AP systems to prove their safety and efficacy in large-scale clinical trials, are outlined.

Successful At-Home Use of the Tandem Control-IQ Artificial Pancreas System in Young Children During a Randomized Controlled Trial

OBJECTIVE

Hybrid closed-loop (HCL) artificial pancreas (AP) systems are now moving from research settings to widespread clinical use. In this study, the inControl algorithm developed by TypeZero Technologies was embedded to a commercial Tandem t:slim X2 insulin pump, now called Control-IQ, paired with a Dexcom G6 continuous glucose monitor and tested for superiority against sensor augmented pump (SAP) therapy. Both groups were physician-monitored throughout the clinical trial.

RESEARCH DESIGN AND METHODS

In a randomized controlled trial, 24 school-aged children (6-12 years) with type 1 diabetes (T1D) participated in a 3-day home-use trial at two sites: Stanford University and the Barbara Davis Center (50% girls, 9.6 ± 1.9 years of age, 4.5 ± 1.9 years of T1D, baseline hemoglobin A1c 7.35% ± 0.68%). Study subjects were randomized 1:1 at each site to either HCL AP therapy with the Control-IQ system or SAP therapy with remote monitoring.

RESULTS

The primary outcome, time in target range 70-180 mg/dL, using Control-IQ significantly improved (71.0% ± 6.6% vs. 52.8% ± 13.5%; P = 0.001) and mean sensor glucose (153.6 ± 13.5 vs. 180.2 ± 23.1 mg/dL; P = 0.003) without increasing hypoglycemia time <70 mg/dL (1.7% [1.3%-2.1%] vs. 0.9% [0.3%-2.7%]; not significant). The HCL system was active for 94.4% of the study period. Subjects reported that use of the system was associated with less time thinking about diabetes, decreased worry about blood sugars, and decreased burden in managing diabetes.

CONCLUSIONS

The use of the Tandem t:slim X2 with Control-IQ HCL AP system significantly improved time in range and mean glycemic control without increasing hypoglycemia in school-aged children with T1D during remote monitored home use.

Real-Time Sharing and Following of Continuous Glucose Monitoring Data in Youth

BACKGROUND

Those caring for children and adolescents with diabetes often use glucose concentration and trending information in management decisions. Some continuous glucose monitoring (CGM) systems offer real-time sharing and monitoring capabilities through mobile apps carried by the person with diabetes and the caregiver(s), respectively. Few large studies have explored real-world associations between sharing and following, CGM utilization, and glycemic outcomes.

METHODS

We performed a retrospective evaluation of device usage and glycemic control in 15,000 youth ranging in age from 2 to 18 years by analyzing anonymized data that had been uploaded with a mobile app that provides optional sharing. The presence or absence of a real-time monitor (a "Follower") was established on 15 June 2018. Each day with ≥ 1 uploaded glucose values was counted as a day of device usage. Between-group glucose comparisons were made with two-sided Welch's t tests.

RESULTS

Overall, 94.8% of the population used the sharing feature and had at least one Follower. The mean numbers of Followers for patients aged 2-5, 6-12, and 13-18 years were 2.8, 2.8, and 2.4, respectively. In all three age categories, the presence of at least one Follower was associated with lower mean glucose values, more glucose values in the 70- to 180-mg/dL range, correspondingly fewer glucose values representing hypoglycemia and hyperglycemia, and significantly more device utilization.

CONCLUSION

Real-time sharing and following of CGM data are associated with improved device utilization and glycemic parameters. The observed association suggests either more timely interventions or higher levels of engagement among the caregivers or the youth with diabetes.

FUNDING

Dexcom, Inc.

Remote Patient Monitoring and Telemedicine in Neonatal and Pediatric Settings: Scoping Literature Review

Background

Telemedicine and telehealth solutions are emerging rapidly in health care and have the potential to decrease costs for insurers, providers, and patients in various settings. Pediatric populations that require specialty care are disadvantaged socially or economically or have chronic health conditions that will greatly benefit from results of studies utilizing telemedicine technologies. This paper examines the emerging trends in pediatric populations as part of a systematic literature review and provides a scoping review of the type, extent, and quantity of research available.

Objective

This paper aims to examine the role of remote patient monitoring (RPM) and telemedicine in neonatal and pediatric settings. Findings can be used to identify strengths, weaknesses, and gaps in the field. The identification of gaps will allow for interventions or research to improve health care quality and costs.

Methods

A systematic literature review is being conducted to gather an adequate amount of relevant research for telehealth in pediatric populations. The fields of RPM and telemedicine are not yet very well established by the health care services sector, and definitions vary across health care systems; thus, the terms are not always defined similarly throughout the literature. Three databases were scoped for information for this specific review, and 56 papers were included for review.

Results

Three major telemedicine trends emerged from the review of 45 relevant papers—RPM, teleconsultation, and monitoring patients within the hospital, but without contact—thus, decreasing the likelihood of infection or other adverse health effects.

Conclusions

While the current telemedicine approaches show promise, limited studied conditions and small sample sizes affect generalizability, therefore, warranting further research. The information presented can inform health care providers of the most widely implemented, studied, and effective forms of telemedicine for patients and their families and the telemedicine initiatives that are most cost efficient for health systems. While the focus of this review is to summarize some telehealth applications in pediatrics, we have also presented research studies that can inform providers about the importance of data sharing of remote monitoring data between hospitals. Further reports will be developed to inform health systems as the systematic literature review continues.

The Use of Continuous Glucose Monitoring With Remote Monitoring Improves Psychosocial Measures in Parents of Children With Type 1 Diabetes: A Randomized Crossover Trial

OBJECTIVE

This study aimed to explore the effect of continuous glucose monitors with remote monitoring on psychosocial outcomes in parents of children with type 1 diabetes.

RESEARCH DESIGN AND METHODS

Children with type 1 diabetes, aged 2-12 years, along with their parents, were studied in a randomized crossover study. They participated in two 3-month periods using conventional blood glucose monitoring (control) or the Dexcom G5 Mobile continuous glucose monitoring (CGM) system with remote monitoring (intervention). The primary outcome was parental fear of hypoglycemia score assessed by the Hypoglycemia Fear Survey.

RESULTS

Parental Hypoglycemia Fear Survey scores were lower while the child was using CGM with remote monitoring (P < 0.001). Furthermore, parental health-related quality of life and family functioning, stress, anxiety, and sleep measures also improved significantly after intervention.

CONCLUSIONS

CGM with remote monitoring was found to improve multiple measures of quality of life, reduce family stress, and improve parental sleep.

Automated closed-loop control of diabetes: the artificial pancreas

The incidence of Diabetes Mellitus is on the rise worldwide, which exerts enormous health toll on the population and enormous pressure on the healthcare systems. Now, almost hundred years after the discovery of insulin in 1921, the optimization problem of diabetes is well formulated as maintenance of strict glycemic control without increasing the risk for hypoglycemia. External insulin administration is mandatory for people with type 1 diabetes; various medications, as well as basal and prandial insulin, are included in the daily treatment of type 2 diabetes. This review follows the development of the Diabetes Technology field which, since the 1970s, progressed remarkably through continuous subcutaneous insulin infusion (CSII), mathematical models and computer simulation of the human metabolic system, real-time continuous glucose monitoring (CGM), and control algorithms driving closed-loop control systems known as the "artificial pancreas" (AP). All of these developments included significant engineering advances and substantial bioelectronics progress in the sensing of blood glucose levels, insulin delivery, and control design. The key technologies that enabled contemporary AP systems are CSII and CGM, both of which became available and sufficiently portable in the beginning of this century. This powered the quest for wearable home-use AP, which is now under way with prototypes tested in outpatient studies during the past 6 years. Pivotal trials of new AP technologies are ongoing, and the first hybrid closed-loop system has been approved by the FDA for clinical use. Thus, the closed-loop AP is well on its way to become the digital-age treatment of diabetes.

Customization of home closed-loop insulin delivery in adult patients with type 1 diabetes, assisted with structured remote monitoring: the pilot WP7 Diabeloop study

AIMS

Improvement in closed-loop insulin delivery systems could result from customization of settings to individual needs and remote monitoring. This pilot home study evaluated the efficacy and relevance of this approach.

METHODS

A bicentric clinical trial was conducted for 3 weeks, using an MPC-based algorithm (Diabeloop Artificial Pancreas system) featuring five settings designed to modulate the reactivity of regulation. Remote monitoring was ensured by expert nurses with a web platform generating automatic Secured Information Messages (SIMs) and with a structured procedure. Endpoints were glucose metrics and description of impact of monitoring on regulation parameters.

RESULTS

Eight patients with type 1 diabetes (six men, age 41.8 ± 11.4 years, HbA1c 7.7 ± 1.0%) were included. Time spent in the 70-180 mg/dl range was 70.2% [67.5; 76.9]. Time in hypoglycemia < 70 mg/dl was 2.9% [2.1; 3.4]. Eleven SIMs led to phone intervention. Original default settings were modified in all patients by the intervention of the nurses.

CONCLUSION

This pilot trial suggests that the Diabeloop closed-loop system could be efficient regarding metabolic outcomes, whereas its telemedical monitoring feature could contribute to enhanced efficacy and safety. This study is registered at ClinicalTrials.gov with trial registration number NCT02987556.

The risks of nocturnal hypoglycaemia in insulin-treated diabetes

Over half of all episodes of severe hypoglycaemia (requiring external help) occur during sleep, but nocturnal hypoglycaemia is often asymptomatic and unrecognised. The precise incidence of nocturnal hypoglycaemia is difficult to determine with no agreed definition, but continuous glucose monitoring has shown that it occurs frequently in people taking insulin. Attenuation of the counter-regulatory responses to hypoglycaemia during sleep may explain why some episodes are undetected and more prolonged, and modifies cardiovascular responses. The morbidity and mortality associated with nocturnal hypoglycaemia is probably much greater than realised, causing seizures, coma and cardiovascular events and affecting quality of life, mood and work performance the following day. It may induce impaired awareness of hypoglycaemia. Cardiac arrhythmias that occur during nocturnal hypoglycaemia include bradycardia and ectopics that may provoke dangerous arrhythmias. Treatment strategies are discussed that may help to minimise the frequency of nocturnal hypoglycaemia.

mHealth Application Areas and Technology Combinations*. A Comparison of Literature from High and Low/Middle Income Countries

BACKGROUND

With the continuous and enormous spread of mobile technologies, mHealth has evolved as a new subfield of eHealth. While eHealth is broadly focused on information and communication technologies, mHealth seeks to explore more into mobile devices and wireless communication. Since mobile phone penetration has exceeded other infrastructure in low and middle-income countries (LMICs), mHealth is seen as a promising component to provide pervasive and patient-centered care.

OBJECTIVES

The aim of our research work for this paper is to examine the mHealth literature to identify application areas, target diseases, and mHealth service and technology types that are most appropriate for LMICs.

METHODS

Based on the 2011 WHO mHealth report, a combination of search terms, all including the word "mHealth", was identified. A literature review was conducted by searching the PubMed and IEEE Xplore databases. Articles were included if they were published in English, covered an mHealth solution/ intervention, involved the use of a mobile communication device, and included a pilot evaluation study. Articles were excluded if they did not provide sufficient detail on the solution covered or did not focus on clinical efficacy/effectiveness. Cross-referencing was also performed on included articles.

RESULTS

842 articles were retrieved and analyzed, 255 of which met the inclusion criteria. North America had the highest number of applications (n=74) followed by Europe (n=50), Asia (n=44), Africa (n=25), and Australia (n=9). The Middle East (n=5) and South America (n=3) had the least number of studies. The majority of solutions addressed diabetes (n=51), obesity (n=25), CVDs (n=24), HIV (n=18), mental health (n=16), health behaviors (n=16), and maternal and child's health (MCH) (n=11). Fewer solutions addressed asthma (n=7), cancer (n=5), family health planning (n=5), TB (n=3), malaria (n=2), chronic obtrusive pulmonary disease (COPD) (n=2), vision care (n=2), and dermatology (n=2). Other solutions targeted stroke, dental health, hepatitis vaccination, cold and flu, ED prescribed antibiotics, iodine deficiency, and liver transplantation (n=1 each). The remainder of solutions (n=14) did not focus on a certain disease. Most applications fell in the areas of health monitoring and surveillance (n=93) and health promotion and raising awareness (n=88). Fewer solutions addressed the areas of communication and reporting (n=11), data collection (n=6), telemedicine (n=5), emergency medical care (n=3), point of care support (n=2), and decision support (n=2). The majority of solutions used SMS messaging (n=94) or mobile apps (n=71). Fewer used IVR/phone calls (n=8), mobile website/email (n=5), videoconferencing (n=2), MMS (n=2), or video (n=1) or voice messages (n=1). Studies were mostly RCTs, with the majority suffering from small sample sizes and short study durations. Problems addressed by solutions included travel distance for reporting, self-management and disease monitoring, and treatment/medication adherence.

CONCLUSIONS

SMS and app solutions are the most common forms of mHealth applications. SMS solutions are prevalent in both high and LMICs while app solutions are mostly used in high income countries. Common application areas include health promotion and raising awareness using SMS and health monitoring and surveillance using mobile apps. Remaining application areas are rarely addressed. Diabetes is the most commonly targeted medical condition, yet remains deficient in LMICs.

CGM, Pregnancy, and Remote Monitoring

The glycemic goals of pregnancy are very narrow to reduce excess risks for numerous maternal and fetal complications. Continuous glucose monitors (CGMs) may help women achieve glucose goals and reduce hypoglycemia. CGM use has been found to be safe and effective in pregnancies associated with diabetes. CGM use can accurately identify glycemic patterns among women with and without diabetes in pregnancy. The data on the effects of CGM use on maternal and fetal outcomes are conflicting. Using CGMs in conjunction with continuous subcutaneous insulin infusion therapy in pregnancies complicated by diabetes may improve outcomes. There are limitations of CGM use that affect patients in and outside of pregnancy, as well as specific barriers that only affect pregnant women. Of importance, CGM use does not replace standard clinical care, but may be used an adjunctive tool in pregnancy. CGM remote monitoring in pregnancy is an understudied field. In this study, we review the studies on CGM use in pregnancy.

Telemedicine for the Management of Glycemic Control and Clinical Outcomes of Type 1 Diabetes Mellitus: A Systematic Review and Meta-Analysis of Randomized Controlled Studies

Importance: Telemedicine has been shown to be an efficient and effective means of providing care to patients with chronic disease especially in remote and undeserved regions, by improving access to care and reduce healthcare cost. However, the evidence surrounding its applicability in type 1 diabetes remains scarce and conflicting.

Objective: To synthesize evidence and quantify the effectiveness of telemedicine interventions for the management of glycemic and clinical outcomes in type 1 diabetes patients, relative to comparator conditions.

Data Sources: MEDLINE, EMBASE, Cochrane Library, Web of Science, PsycINFO, and CINAHL were searched for published articles since inception until December 2016.

Study Selection: Original articles reporting the results of randomized controlled studies on the effectiveness of telemedicine in people with type 1 diabetes were included.

Data Extraction and Synthesis: Two reviewers independently extracted data, assessed quality, and strength of evidence. Interventions were categorized based upon the telemedicine focus (monitoring, education, consultation, case-management, and peer mentoring).

Main Outcome and Measure: Absolute change in glycosylated hemoglobin A1c (HbA1c) from baseline to follow-up assessment.

Results: A total of 38 studies described in 41 articles were identified. Positive effects on glycemic control were noted with studies examining telemedicine, with a mean reduction of 0.18% at the end of intervention. Studies with longer duration (>6 months) who had recruited patients with a higher baseline HbA1c (≥9%) were associated with larger effects. Telemedicine interventions that involve individualized assessments, audit with feedback and skill building were also more effective in improving glycemic control. However, no benefits were observed on blood pressure, lipids, weight, quality of life, and adverse events.

Conclusions and Relevance: There is insufficient evidence to support telemedicine use for glycemic control and other clinically relevant outcome among patients with type 1 diabetes.

MD-Logic overnight type 1 diabetes control in home settings: A multicentre, multinational, single blind randomized trial

AIMS

To evaluate the safety, efficacy and need for remote monitoring of the MD-Logic closed-loop system during short-term overnight use at home.

METHODS

Seventy-five patients (38 male; aged 10-54 years; average A1c, 7.8% ± 0.7%, 61.8 ± 7.2 mmol/mol) were enrolled from 3 clinical sites. Patients were randomly assigned to participate in 2 overnight crossover periods, each including 4 consecutive nights, 1 under closed-loop control and 1 under sensor-augmented pump (SAP) therapy in the patient's home. Both study arms were supervised using a remote-monitoring system in a blinded manner. Primary endpoints were time spent with glucose levels below 70 mg/dL and percentage of nights in which mean overnight glucose levels were within 90 to 140 mg/dL.

RESULTS

The median [interquartile range] percentage of time spent in hypoglycaemia was significantly lower on nights when MD-Logic was used, compared to SAP therapy (2.07 [0, 4.78] and 2.6 [0, 10.34], respectively; P = .004) and the percentage of individual nights with a mean overnight glucose level in target was significantly greater (75 [42, 75] and 50 [25,75], respectively; P = .008). The time spent in target range was increased by a median of 28% (P = .001), with the same amount of insulin (10.69 [7.28, 13.94] and 10.41[6.9, 14.07], respectively; P = .087). The remote monitoring triggered calls for hypoglycaemia at twice the rate during SAP therapy compared to closed-loop control (62 and 29, respectively; P = .002).

CONCLUSIONS

The MD-Logic system demonstrated a safe and efficient profile during overnight use by children, adolescents and adults with type 1 diabetes and, therefore, provides an effective means of mitigating the risk of nocturnal hypoglycaemia.

Camp for Youth With Type 1 Diabetes

Camps for youth with type 1 diabetes (T1D) have grown in size and scope since they first emerged in the 1920s. Anecdotal evidence suggests that attending camp with other youth with T1D is beneficial, largely attributed to sharing fun, active experiences and removing the isolation of living with diabetes. However, few studies have evaluated the psychosocial and medical impacts of T1D camp attendance during and after camp sessions. In addition, T1D camps have been a setting for numerous studies on a variety of T1D-related research questions not related to camp itself, such as testing novel diabetes management technologies in an active, non-laboratory setting. This paper reviews the evidence of psychosocial and medical outcomes associated with T1D camp attendance across the globe, provides an overview of other research conducted at camp, and offers recommendations for future research conducted at T1D camp.

Multinational Home Use of Closed-Loop Control Is Safe and Effective

OBJECTIVE

To evaluate the efficacy of a portable, wearable, wireless artificial pancreas system (the Diabetes Assistant [DiAs] running the Unified Safety System) on glucose control at home in overnight-only and 24/7 closed-loop control (CLC) modes in patients with type 1 diabetes.

RESEARCH DESIGN AND METHODS

At six clinical centers in four countries, 30 participants 18-66 years old with type 1 diabetes (43% female, 96% non-Hispanic white, median type 1 diabetes duration 19 years, median A1C 7.3%) completed the study. The protocol included a 2-week baseline sensor-augmented pump (SAP) period followed by 2 weeks of overnight-only CLC and 2 weeks of 24/7 CLC at home. Glucose control during CLC was compared with the baseline SAP.

RESULTS

Glycemic control parameters for overnight-only CLC were improved during the nighttime period compared with baseline for hypoglycemia (time <70 mg/dL, primary end point median 1.1% vs. 3.0%; P < 0.001), time in target (70-180 mg/dL: 75% vs. 61%; P < 0.001), and glucose variability (coefficient of variation: 30% vs. 36%; P < 0.001). Similar improvements for day/night combined were observed with 24/7 CLC compared with baseline: 1.7% vs. 4.1%, P < 0.001; 73% vs. 65%, P < 0.001; and 34% vs. 38%, P < 0.001, respectively.

CONCLUSIONS

CLC running on a smartphone (DiAs) in the home environment was safe and effective. Overnight-only CLC reduced hypoglycemia and increased time in range overnight and increased time in range during the day; 24/7 CLC reduced hypoglycemia and increased time in range both overnight and during the day. Compared with overnight-only CLC, 24/7 CLC provided additional hypoglycemia protection during the day.

Biphasic insulin Aspart 30 vs. NPH plus regular human insulin in type 2 diabetes patients; a cost-effectiveness study

BACKGROUND

The aim of this study was to compare the efficacy, safety, costs, and cost-effectiveness of biphasic insulin aspart 30 (BIAsp 30) with NPH plus regular human insulin (NPH/Reg) in patients with type 2 diabetes mellitus (T2DM).

METHODS

It was a Single-center, parallel-group, randomized, clinical trial (Trial Registration: NCT01889095). One hundred and seventy four T2DM patients with poorly controlled diabetes (HbA1c ≥ 8 % (63.9 mmol/mol)) were randomly assigned to trial arms (BIAsp 30 and NPH/Reg) and were followed up for 48 weeks. BIAsp 30 was started at an initial dose of 0.2-0.6 IU/Kg in two divided doses and was titrated according to the glycemic status of the patient. Similarly, NPH/Reg insulin was initiated at a dose of 0.2-0.6 IU/Kg with a 2:1 ratio and was subsequently titrated. Level of glycemic control, hypoglycemic events, direct and indirect costs, quality adjusted life year (QALY) and incremental cost-effectiveness ratio have been assessed.

RESULTS

HbA1c, Fasting plasma glucose (FPG), and two-hour post-prandial glucose (PPG) were improved in both groups during the study (P < 0.05 for all analyses). Lower frequencies of minor, major, and nocturnal hypoglycemic episodes were observed with BIAsp 30 (P < 0.05). Additionally, BIAsp 30 was associated with less weight gain and also higher QALYs (P < 0.05). Total medical and non-medical costs were significantly lower with BIAsp 30 as compared with NPH/Reg (930.55 ± 81.43 USD vs. 1101.24 ± 165.49 USD, P = 0.004). Moreover, BIAsp 30 showed lower ICER as a dominant alternative.

CONCLUSIONS

Despite being more expensive, BIAsp 30 offers the same glycemic control as to NPH/Reg dose-dependently and also appears to cause fewer hypoglycemic events and to be more cost-effective in Iranian patients with type 2 diabetes.

Automated Overnight Closed-Loop Control Using a Proportional-Integral-Derivative Algorithm with Insulin Feedback in Children and Adolescents with Type 1 Diabetes at Diabetes Camp

OBJECTIVE

This study determined the feasibility and efficacy of an automated proportional-integral-derivative with insulin feedback (PID-IFB) controller in overnight closed-loop (OCL) control of children and adolescents with type 1 diabetes over multiple days in a diabetes camp setting.

RESEARCH DESIGN AND METHODS

The Medtronic (Northridge, CA) Android™ (Google, Mountain View, CA)-based PID-IFB system consists of the Medtronic Minimed Revel™ 2.0 pump and Enlite™ sensor, a control algorithm residing on an Android phone, a translator, and remote monitoring capabilities. An inpatient study was completed for 16 participants to determine feasibility. For the camp study, subjects with type 1 diabetes were randomized to either OCL or sensor-augmented pump therapy (control conditions) per night for up to 6 nights at diabetes camp.

RESULTS

During the camp study, 21 subjects completed 50 OCL nights and 52 control nights. Based on intention to treat, the median time spent in range, from 70 to 150 mg/dL, was greater during OCL at 66.4% (n = 55) versus 50.6% (n = 52) during the control period (P = 0.004). A per-protocol analysis allowed for assessment of algorithm performance with the median percentage time in range, 70-150 mg/dL, being 75.5% (n = 37) for OCL versus 47.6% (n = 32) for the control period (P < 0.001). There was less time spent in the hypoglycemic ranges <60 mg/dL and <70 mg/dL during OCL compared with the control period (P = 0.003 and P < 0.001, respectively).

CONCLUSIONS

The PID-IFB controller is effective in improving time spent in range as well as reducing nocturnal hypoglycemia during the overnight period in children and adolescents with type 1 diabetes in a diabetes camp setting.

Real-Time Model-Based Fault Detection of Continuous Glucose Sensor Measurements

OBJECTIVE

Faults in subcutaneous glucose concentration readings with a continuous glucose monitoring (CGM) may affect the computation of insulin infusion rates that can lead to hypoglycemia or hyperglycemia in artificial pancreas control systems for patients with type 1 diabetes (T1D).

METHODS

Multivariable statistical monitoring methods are proposed for detection of faults in glucose concentration values reported by a subcutaneous glucose sensor. A nonlinear first principle glucose/insulin/meal dynamic model is developed. An unscented Kalman filter is used for state and parameter estimation of the nonlinear model. Principal component analysis models are developed and used for detection of dynamic changes. K-nearest neighbor classification algorithm is used for diagnosis of faults. Data from 51 subjects are used to assess the performance of the algorithm.

RESULTS

The results indicate that the proposed algorithm works successfully with 84.2% sensitivity. Overall, 155 (out of 184) of the CGM failures are detected with a 2.8-min average detection time.

CONCLUSION

A novel algorithm that integrates data-driven and model-based methods is developed. The proposed method is able to detect CGM failures with a high rate of success.

SIGNIFICANCE

The proposed fault detection algorithm can decrease the effects of faults on insulin infusion rates and reduce the potential for hypo- or hyperglycemia for patients with T1D.

Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review

BACKGROUND

Adherence to chronic disease management is critical to achieving improved health outcomes, quality of life, and cost-effective health care. As the burden of chronic diseases continues to grow globally, so does the impact of non-adherence. Mobile technologies are increasingly being used in health care and public health practice (mHealth) for patient communication, monitoring, and education, and to facilitate adherence to chronic diseases management.

OBJECTIVE

We conducted a systematic review of the literature to evaluate the effectiveness of mHealth in supporting the adherence of patients to chronic diseases management ("mAdherence"), and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among patients and health care providers.

METHODS

We searched PubMed, Embase, and EBSCO databases for studies that assessed the role of mAdherence in chronic disease management of diabetes mellitus, cardiovascular disease, and chronic lung diseases from 1980 through May 2014. Outcomes of interest included effect of mHealth on patient adherence to chronic diseases management, disease-specific clinical outcomes after intervention, and the usability, feasibility, and acceptability of mAdherence tools and platforms in chronic disease management among target end-users.

RESULTS

In all, 107 articles met all inclusion criteria. Short message service was the most commonly used mAdherence tool in 40.2% (43/107) of studies. Usability, feasibility, and acceptability or patient preferences for mAdherence interventions were assessed in 57.9% (62/107) of studies and found to be generally high. A total of 27 studies employed randomized controlled trial (RCT) methods to assess impact on adherence behaviors, and significant improvements were observed in 15 of those studies (56%). Of the 41 RCTs that measured effects on disease-specific clinical outcomes, significant improvements between groups were reported in 16 studies (39%).

CONCLUSIONS

There is potential for mHealth tools to better facilitate adherence to chronic disease management, but the evidence supporting its current effectiveness is mixed. Further research should focus on understanding and improving how mHealth tools can overcome specific barriers to adherence.

Overnight glucose control with an automated, unified safety system in children and adolescents with type 1 diabetes at diabetes camp

OBJECTIVE

To determine the safety and efficacy of an automated unified safety system (USS) in providing overnight closed-loop (OCL) control in children and adolescents with type 1 diabetes attending diabetes summer camps.

RESEARCH DESIGN AND METHODS

The Diabetes Assistant (DIAS) USS used the Dexcom G4 Platinum glucose sensor (Dexcom) and t:slim insulin pump (Tandem Diabetes Care). An initial inpatient study was completed for 12 participants to evaluate safety. For the main camp study, 20 participants with type 1 diabetes were randomized to either OCL or sensor-augmented therapy (control conditions) per night over the course of a 5- to 6-day diabetes camp.

RESULTS

Subjects completed 54 OCL nights and 52 control nights. On an intention-to-treat basis, with glucose data analyzed regardless of system status, the median percent time in range, from 70-150 mg/dL, was 62% (29, 87) for OCL nights versus 55% (25, 80) for sensor-augmented pump therapy (P = 0.233). A per-protocol analysis allowed for assessment of algorithm performance. The median percent time in range, from 70-150 mg/dL, was 73% (50, 89) for OCL nights (n = 41) versus 52% (24, 83) for control conditions (n = 39) (P = 0.037). There was less time spent in the hypoglycemic range <50, <60, and <70 mg/dL during OCL compared with the control period (P = 0.019, P = 0.009, and P = 0.023, respectively).

CONCLUSIONS

The DIAS USS algorithm is effective in improving time spent in range as well as reducing nocturnal hypoglycemia during the overnight period in children and adolescents with type 1 diabetes in a diabetes camp setting.

Cell based metabolic barriers to glucose diffusion: macrophages and continuous glucose monitoring

It is assumed that MQ are central to glucose sensor bio-fouling and therefore have a major negative impact on continuous glucose monitoring (CGM) performance in vivo. However to our knowledge there is no data in the literature to directly support or refute this assumption. Since glucose and oxygen (O2) are key to glucose sensor function in vivo, understanding and controlling glucose and O2 metabolic activity of MQ is likely key to successful glucose sensor performance. We hypothesized that the accumulation of MQ at the glucose sensor-tissue interface will act as "Cell Based Metabolic Barriers" (CBMB) to glucose diffusing from the interstitial tissue compartment to the implanted glucose sensor and as such creating an artificially low sensor output, thereby compromising sensor function and CGM. Our studies demonstrated that 1) direct injections of MQ at in vivo sensor implantation sites dramatically decreased sensor output (measured in nA), 2) addition of MQ to glucose sensors in vitro resulted in a rapid and dramatic fall in sensor output and 3) lymphocytes did not affect sensor function in vitro or in vivo. These data support our hypothesis that MQ can act as metabolic barriers to glucose and O2 diffusion in vivo and in vitro.