A randomized trial of a home system to reduce nocturnal hypoglycemia in type 1 diabetes

Using Diabetes Technology in Hospitalized Patients

There is an estimated 350,000 persons wearing an insulin pump and 2.4 million wearing a continuous glucose monitor (CGM) sensor in the United States. The last few decades have ushered in advancements with the integration of insulin delivery and continuous glucose evaluations which offer a more precise tight insulin delivery and glycemic control. However, when hospital admissions are necessary, most desire to continue to wear their devices. The last several decades and during the pandemic, many agencies such as the Joint Commission, FDA, and diabetes organizations have generated position statements and guidelines to allow the most optimal diabetes treatment, even when hospitalized.

Unsupervised Retrospective Detection of Pressure Induced Failures in Continuous Glucose Monitoring Sensors for T1D Management

Continuous Glucose Monitoring sensors (CGMs) have revolutionized type 1 diabetes (T1D) management. In particular, in several cases, the retrospective analysis of CGM recordings allows clinicians to review and adjust patients' therapy. However, in this set-up, the artifacts that are often present in CGM data could lead to incorrect therapeutic actions. To mitigate this risk, we investigate how to detect one of the most common of these artifacts, the so-called pressure induced sensor attenuations, by means of anomaly detection algorithms. Specifically, these methods belong to the class of unsupervised techniques, which is particularly appealing since it does not require a labeled dataset, hardly available in practice. After having designed five features to highlight the anomalous state of the sensor, 8 different methods (e.g. Isolation Forest and Histogram-based Outlier Score) are assessed both in silico using the UVa/Padova Type 1 Diabetes Simulator and on real data of 36 subjects monitored for about 10 days. In the in silico scenario, the best results are achieved with Isolation Forest, which recognized the 74% of the failures generating on average only 2 false alerts during the whole monitoring time. In real data, Isolation Forest is confirmed to be effective in the detection of failures, achieving a recall of 55% and generating 3 false alarms in 10 days. By allowing to detect more than 50% of the artifacts while discarding only a few portions of correct data in several days of monitoring, the proposed approach could effectively improve the quality of CGM data used by clinicians to retrospectively evaluate and adjust T1D therapy.

Population-Specific Glucose Prediction in Diabetes Care With Transformer-Based Deep Learning on the Edge

Leveraging continuous glucose monitoring (CGM) systems, real-time blood glucose (BG) forecasting is essential for proactive interventions, playing a crucial role in enhancing the management of type 1 diabetes (T1D) and type 2 diabetes (T2D). However, developing a model generalized to a population and subsequently embedding it within a microchip of a wearable device presents significant technical challenges. Furthermore, the domain of BG prediction in T2D remains under-explored in the literature. In light of this, we propose a population-specific BG prediction model, leveraging the capabilities of the temporal fusion Transformer (TFT) to adjust predictions based on personal demographic data. Then the trained model is embedded within a system-on-chip, integral to our low-power and low-cost customized wearable device. This device seamlessly communicates with CGM systems through Bluetooth and provides timely BG predictions using edge computing. When evaluated on two publicly available clinical datasets with a total of 124 participants with T1D or T2D, the embedded TFT model consistently demonstrated superior performance, achieving the lowest prediction errors when compared with a range of machine learning baseline methods. Executing the TFT model on our wearable device requires minimal memory and power consumption, enabling continuous decision support for more than 51 days on a single Li-Poly battery charge. These findings demonstrate the significant potential of the proposed TFT model and wearable device in enhancing the quality of life for people with diabetes and effectively addressing real-world challenges.

Neonatal birth weight percentile following the use of sensor-augmented pump therapy in women with pre-gestational diabetes

AIMS

To assess the effect of using sensor-augmented pump therapy (SAP) during pregnancy on neonatal birth weight percentile and other neonatal and pregnancy outcomes.

METHODS

This retrospective cohort study included consecutive women with pregestational diabetes mellitus (PGDM) treated with an insulin pump and sensor that enabled the SAP feature during pregnancy. SAP use was defined as utilization of either low-glucose suspend (LGS) or predictive LGS technology. Utilization of SAP was according to physician discretion. Differences in neonatal birth weight percentile and in other neonatal and pregnancy outcomes were compared between those who did and not use SAP.

OUTCOMES

Of 142 women, 136 had type 1 diabetes, 5 type 2 diabetes and one diabetes due to pancreatectomy. 83 women used SAP and 59 did not. For the neonates of the mothers of the respective groups, the median birth weight percentiles were similar (79 and 80, pV = 0.96), as were the other neonatal outcomes assessed. The rate of cesarean section was higher in the SAP group. However, after adjusting for maternal age, BMI, and a history of severe hypoglycemic events before pregnancy, the relation between mode of delivery and the use of SAP was no longer statistically significant.

CONCLUSION

In women with PGDM treated with an insulin pump and sensor, SAP use during pregnancy was not associated with higher neonatal birth weight percentile or the occurrences of other adverse neonatal or pregnancy outcomes.

Current and future therapies to treat impaired awareness of hypoglycemia

In order to achieve optimal glycemic control, intensive insulin regimes are needed for individuals with Type 1 Diabetes (T1D) and insulin-dependent Type 2 Diabetes (T2D). Unfortunately, intensive glycemic control often results in insulin-induced hypoglycemia. Moreover, recurrent episodes of hypoglycemia result in both the loss of the characteristic warning symptoms associated with hypoglycemia and an attenuated counterregulatory hormone responses. The blunting of warning symptoms is known as impaired awareness of hypoglycemia (IAH). Together, IAH and the loss of the hormonal response is termed hypoglycemia associated autonomic failure (HAAF). IAH is prevalent in up to 25% in people with T1D and up to 10% in people with T2D. IAH and HAAF increase the risk of severe hypoglycemia 6-fold and 25-fold, respectively. To reduce this risk for severe hypoglycemia, multiple different therapeutic approaches are being explored that could improve awareness of hypoglycemia. Current therapies to improve awareness of hypoglycemia include patient education and psychoeducation, the use of novel glycemic control technology, pancreas/islet transplantation, and drug therapy. This review examines both existing therapies and potential therapies that are in pre-clinical testing. Novel treatments that improve awareness of hypoglycemia, via improving the counterregulatory hormone responses or improving hypoglycemic symptom recognition, would also shed light on the possible neurological mechanisms that lead to the development of IAH. To reduce the risk of severe hypoglycemia in people with diabetes, elucidating the mechanism behind IAH, as well as developing targeted therapies is currently an unmet need for those that suffer from IAH.

Diabetestechnologie bei Kindern und Jugendlichen mit Diabetes mellitus Typ 1

Die Behandlung des Diabetes mellitus Typ 1 (T1D) im Kindes- und Jugendalter ist komplex und stellt eine Herausforderung für die betroffenen Kinder und Jugendlichen, deren Familien und das ganze Umfeld (Schule/Kindergarten) dar. Das Ziel der Diabetestherapie besteht darin, eine möglichst normoglykämische Blutzuckerkontrolle zu erreichen, um akuten und chronischen Komplikationen vorzubeugen. Laut Registerstudien können die metabolischen Therapieziele derzeit noch nicht erreicht werden, weswegen ein Risiko für Akut- und Spätkomplikationen besteht. Weitere Therapieziele sind eine normale Entwicklung, Inklusion, Flexibilität im Alltag sowie eine hohe Lebensqualität. Abgesehen von neueren Insulinanaloga gingen auch die Entwicklungen in der Diabetestechnologie in den letzten Jahren mit großen Veränderungen und Verbesserungen in der Behandlung und Lebensqualität der betroffenen Familien einher. Die Insulinpumpentherapie, die kontinuierliche Glukosemessung sowie die automatische Insulindosierung (AID) führten zu einer signifikanten Verbesserung der metabolischen Einstellung sowie einer Reduktion der schweren Hypoglykämien und Ketoazidosen. Die Diabetestechnologie entwickelt sich ständig weiter und erfordert eine umfassende Schulung und Fortbildung der betroffenen Familien, der Betreuungseinrichtungen sowie auch des multidisziplinären Behandlungsteams. Ziel sind eine Reduktion der glykämischen Variabilität und damit ein besseres Langzeitoutcome der jungen Menschen mit T1D. Die AID ist zunehmend die Therapie der Wahl bei Kindern und Jugendlichen mit T1D. Mit weiteren Innovationen im Bereich der Diabetestechnologie ist in naher Zukunft zu rechnen.

Dead in bed - A systematic review of overnight deaths in type 1 diabetes

BACKGROUND

Type 1 diabetes is a significant, life-long condition which affects many people worldwide. One of the most feared causes of type 1 diabetes mortality, overnight mortality, often caused by the dead in bed syndrome, is largely underreported. A systematic literature search was undertaken to understand the frequency, risk factors, causes and impact that diabetes-related technologies have on overnight mortality, in this population.

METHODS

MEDLINE (Ovid), Embase (Ovid) and Cochrane were searched to June 2021, using defined inclusion and exclusion criteria. Quality appraisal was undertaken.

RESULTS

Overall, 26 records met the inclusion criteria. Large-scale cohort studies examined data up to 2013, and there were no studies published after 2018. The proportion of deaths attributable to the dead in bed syndrome was between 2 and 5% of deaths in children, adolescents, and young adults, with a slight decrease in proportion of dead in bed syndrome since 1991.

CONCLUSION

Overnight mortality is occurring for people with type 1 diabetes, reported as recently as in 2018. Living alone, alcohol and illicit substances consistently appear as risk factors, and the impact of technology on overnight mortality is not fully understood, with more recent data, from larger cohort studies being required.

Childhood diabetes and sleep

Sleep modulates glucose metabolism, both in healthy states and in disease. Alterations in sleep duration (insufficient and excessive) and obstructive sleep apnea may have reciprocal ties with obesity, insulin resistance and Type 2 diabetes, as demonstrated by emerging evidence in children and adolescents. Type 1 diabetes is also associated with sleep disturbances due to the influence of wide glycemic fluctuations upon sleep architecture, the need to treat nocturnal hypoglycemia, and the need for glucose monitoring and insulin delivery technologies. In this article, we provide an extensive and critical review on published pediatric literature regarding these topics, reviewing both epidemiologic and qualitative data, and provide an overview of the pathophysiology linking sleep with disorders of glucose homeostasis.

Data-Driven Supervised Compression Artifacts Detection on Continuous Glucose Sensors

Continuous Glucose Monitoring (CGM) sensors micro-invasively provide frequent glucose readings, improving the management of Type 1 diabetic patients' life and making available reach data-sets for retrospective analysis. Unlikely, CGM sensors are subject to failures, such as compression artifacts, that might impact on both real-time and respective CGM use. In this work is focused on retrospective detection of compression artifacts. An in-silico dataset is generated using the T1D UVa/Padova simulator and compression artifacts are subsequently added in known position, thus creating a dataset with perfectly accurate faulty/not-faulty labels. The problem of compression artifact detection is then faced with supervised data-driven techniques, in particular using Random Forest algorithm. The detection performance guaranteed by the method on in-silico data is satisfactory, opening the way for further analysis on real-data.

Letting the World See through Your Eyes: Using Photovoice to Explore the Role of Technology in Physical Activity for Adolescents Living with Type 1 Diabetes

This paper qualitatively explores how technologies and physical activity are experienced by adolescents with type 1 diabetes. Type 1 diabetes is a life-threatening autoimmune condition, which is highly prevalent in young children. Physical activity is underutilised as part of treatment goals due to multifactorial challenges and lack of education in both the family setting and across society as a whole. Using photovoice methodology, 29 participants (parents and adolescents), individually or as dyads, shared and described in reflective journal format examples of technology and physical activity in their lives. In total, 120 personal photographs with accompanying narratives were provided. The data were thematically coded by the researcher and then collaboratively with participants. Four key themes (and 12 subthemes) were generated including: (i) benefits of technology; (ii) complexity and difficulty; (iii) emotional impact; (iv) reliance and risk. Findings demonstrate that current technology does not address the complex needs of adolescents with type 1 diabetes to enable participation in physical activity without life risk. We conclude from our findings that future technologies for supporting engagement in physical activity as part of diabetes management need to be: more interoperable, personalised and integrated better with ongoing education and support.

Frequent scanning using flash glucose monitoring contributes to better glycemic control in children and adolescents with type 1 diabetes

AIMS/INTRODUCTION

We examined the impact of scanning frequency with flash glucose monitoring on glycemic control in children and adolescents with type 1 diabetes.

MATERIALS AND METHODS

The study included 85 patients, aged 14.0 ± 0.5 years, with type 1 diabetes. The median time in the target glucose range (TIR) and glycosylated hemoglobin (HbA1c) values were 50.0 ± 1.4% and 7.5 ± 0.1%, respectively.

RESULTS

The median scanning frequency using flash glucose monitoring was 12.0 ± 0.4 times/day. Scanning frequency showed a significant positive correlation with TIR and an inverse correlation with HbA1c. Scanning frequency was identified to be the determinant of TIR and HbA1c by using multivariate analysis. The participants whose scanning frequency was <12 times/day were categorized as the low-frequency group (n = 40), and those who carried out the scanning >12 times/day were categorized as the high-frequency group (n = 45). Patients in the high-frequency group were more likely to be treated with insulin pumps compared with those in the low-frequency group; however, this difference was not significant (21.3 vs 5.3%, P = 0.073). The high-frequency group showed significantly greater TIR than the low-frequency group (57 ± 1.6 vs 42 ± 1.7%, P = 0.002). Furthermore, the high-frequency group showed significantly lower HbA1c levels than the low-frequency group (6.8 ± 0.1 vs 8.0 ± 0.1%, P < 0.001).

CONCLUSIONS

These findings showed that patients with a higher scanning frequency had better glycemic control, with greater TIRs and lower HbA1c levels, compared with those with a lower scanning frequency. Scanning frequency of >12 times/day might contribute to better glycemic outcomes in real-world practice in children with type 1 diabetes.

Hybrid Close-Loop Systems Versus Predictive Low-Glucose Suspend and Sensor-Augmented Pump Therapy in Patients With Type 1 Diabetes: A Single-Center Cohort Study

INTRODUCTION

Predictive low-glucose suspend (PLGS) and hybrid closed-loop (HCL) systems may improve glucose control and quality of life in type 1 diabetic individuals. This is a cross-sectional, single-center study to compare the effect on metabolic control and glucose variability of PLGS and HCL systems as compared to standard sensor-augmented pump (SAP) therapy.

METHODS

We retrospectively analyzed 136 adults (men/women 69/67, mean age 47.3 ± 13.9 years) with T1D on insulin pump therapy, divided accordingly to type of insulin pump system (group 1: SAP, 24 subjects; group 2: PLGS, 49 subjects; group 3: HCL, 63 subjects). The groups were matched for age, gender, years of disease, years of CSII use, and CGM wear time.

RESULTS

The analysis of CGM metrics, in the three groups, showed a statistically significant different percentage of time within the target range, defined as 70-180 mg/dl, with a higher percentage in group 3 and significantly less time spent in the hypoglycemic range in groups 2 and 3. The three groups were statistically different also for the glucose management indicator and coefficient of variation percentage, which were progressively lower moving from group 1 to group 3. In the HCL group, 52.4% of subjects reached a percentage of time passed in the euglycemic range above 70%, as compared to 32.7% in those with PLGS and 20.2% in those with SAP. A positive correlation between the higher percentage of TIR and the use of auto-mode was evident in the HCL group. Finally, the three groups did not show any statistical differences regarding the quality-of-life questionnaire, but there was a significant negative correlation between CV and perceived CSII-use convenience (r = -0.207, p = 0.043).

CONCLUSION

HCL systems were more effective in improving glucose control and in reducing the risk of hypoglycemia in patients with type 1 diabetes, thereby mitigating risk for acute and chronic complications and positively affecting diabetes technologies' acceptance.

Current Advances of Artificial Pancreas Systems: A Comprehensive Review of the Clinical Evidence

Since Banting and Best isolated insulin in the 1920s, dramatic progress has been made in the treatment of type 1 diabetes mellitus (T1DM). However, dose titration and timely injection to maintain optimal glycemic control are often challenging for T1DM patients and their families because they require frequent blood glucose checks. In recent years, technological advances in insulin pumps and continuous glucose monitoring systems have created paradigm shifts in T1DM care that are being extended to develop artificial pancreas systems (APSs). Numerous studies that demonstrate the superiority of glycemic control offered by APSs over those offered by conventional treatment are still being published, and rapid commercialization and use in actual practice have already begun. Given this rapid development, keeping up with the latest knowledge in an organized way is confusing for both patients and medical staff. Herein, we explore the history, clinical evidence, and current state of APSs, focusing on various development groups and the commercialization status. We also discuss APS development in groups outside the usual T1DM patients and the administration of adjunct agents, such as amylin analogues, in APSs.

Clinically Serious Hypoglycemia Is Rare and Not Associated With Time-in-range in Youth With New-onset Type 1 Diabetes

CONTEXT

Early initiation of continuous glucose monitoring (CGM) is advocated for youth with type 1 diabetes (T1D). Data to guide CGM use on time-in-range (TIR), hypoglycemia, and the role of partial clinical remission (PCR) are limited.

OBJECTIVE

Our aims were to assess whether 1) an association between increased TIR and hypoglycemia exists, and 2) how time in hypoglycemia varies by PCR status.

METHODS

We analyzed 80 youth who were started on CGM shortly after T1D diagnosis and were followed for up to 1-year post diagnosis. TIR and hypoglycemia rates were determined by CGM data and retrospectively analyzed. PCR was defined as (visit glycated hemoglobin A1c) + (4*units/kg/day) less than 9.

RESULTS

Youth were started on CGM 8.0 (interquartile range, 6.0-13.0) days post diagnosis. Time spent at less than 70 mg/dL remained low despite changes in TIR (highest TIR 74.6 ± 16.7%, 2.4 ± 2.4% hypoglycemia at 1 month post diagnosis; lowest TIR 61.3 ± 20.3%, 2.1 ± 2.7% hypoglycemia at 12 months post diagnosis). No events of severe hypoglycemia occurred. Hypoglycemia was rare and there was minimal difference for PCR vs non-PCR youth (54-70 mg/dL: 1.8% vs 1.2%, P = .04; < 54mg/dL: 0.3% vs 0.3%, P = .55). Approximately 50% of the time spent in hypoglycemia was in the 65 to 70 mg/dL range.

CONCLUSION

As TIR gradually decreased over 12 months post diagnosis, hypoglycemia was limited with no episodes of severe hypoglycemia. Hypoglycemia rates did not vary in a clinically meaningful manner by PCR status. With CGM being started earlier, consideration needs to be given to modifying CGM hypoglycemia education, including alarm settings. These data support a trial in the year post diagnosis to determine alarm thresholds for youth who wear CGM.

Basal-IQ technology in the real world: satisfaction and reduction of diabetes burden in individuals with type 1 diabetes

AIM

To describe person-reported outcomes of the Basal-IQ predictive low-glucose-suspend system (Tandem Diabetes Care, San Diego, CA, USA) in real-world use.

METHODS

Adults with type 1 diabetes/caregivers of minors with type 1 diabetes completed the Diabetes Impact and Device Satisfaction questionnaire (11 items scored on 10-point Likert scales) prior to Basal-IQ system initiation, and at 2, 4 and 6 months post-initiation. Analysis was stratified by previous insulin treatment method. Beta mixed models were used to measure change in device satisfaction (e.g. trust, ease of use) and diabetes impact (e.g. hypoglycaemia fear, poor sleep) scores between time points, adjusting for baseline covariates.

RESULTS

A total of 967 adults and caregivers [54% women, mean (sd) age 36 (17) years, 57% Tandem pump users, 27% non-Tandem pump users, 17% multiple daily injection users] completed surveys. Device satisfaction significantly increased from baseline to 2 months in all groups (P<0.001 multiple daily injection and non-Tandem pump users; P=0.048 Tandem pump users), and was sustained from 2 to 6 months in all groups. Diabetes impact decreased significantly from baseline to 2 months in all groups (P<0.001 for all), was sustained from 2 to 6 months in multiple daily injection and Tandem pump users, and increased slightly at 4 months/decreased at 6 months in non-Tandem users.

CONCLUSION

The Basal-IQ system increased device satisfaction and reduced diabetes impact in all users in the first 2 months of use, and satisfaction was sustained over 6 months, with small fluctuations.

The effects of continuous glucose monitoring system on patient outcomes and associated costs in a real-world setting

AIMS

Continuous glucose monitoring system (CGMS) technologies may alert unaware hypoglycaemia or near hypoglycaemia events. However, costs are a significant concern in general CGMS use. This study describes the real-world effects of both clinical outcomes and associated costs in a major Health Maintenance Organization, 1 year following preauthorization of CGMS for each patient.

METHODS

Cohort study. Type 1 diabetes patients who were preauthorized CGMS were identified, and their medical records during the year before preauthorization were compared to the following year. Data were collected for glucose control, medical services utilization and related costs.

RESULTS

We identified 524 eligible patients, 57% males. Adherence to CGMS use was improved by age. The proportion of patients reaching HbA_1c  < 7.5% (58 mmol/mol) increased in the high-adherence group and decreased in the low-adherence group. There were no significant changes in outpatient medical services utilization. However, there was a decrease in emergency room visit rates (30%-19%, p < 0.01) and hospitalization rates (22%-12%, p < 0.01) with the highest decrease among the high-adherence group. Hospitalization duration also decreased. However, the total costs per patient were higher as CGMS adherence increased.

CONCLUSION

Continuous glucose monitoring system technologies have the potential of both improving blood glucose control and reducing inpatient utilization. However, CGMS technologies costs may put a significant burden on healthcare systems.

Fear of hypoglycemia in children with type 1 diabetes and their parents: Effect of pump therapy and continuous glucose monitoring with option of low glucose suspend in the CGM TIME trial

To determine if pump therapy with continuous glucose monitoring offering low glucose suspend (LGS) decreases fear of hypoglycemia among children with type 1 diabetes and their parents. The CGM TIME trial is a multicenter randomized controlled trial that enrolled 144 children with type 1 diabetes for at least 1 year (mean duration 3.4 ± 3.1 years) starting pump therapy (MiniMed™ Veo™, Medtronic Canada). CGM (MiniMed™ Enlite™ sensor) offering LGS was introduced simultaneously or delayed for 6 months. Hypoglycemia Fear Scale (HFS) was completed by children ≥10 years old and all parents, at study entry and 12 months later. Simultaneous and Delayed Group participants were combined for all analyses. Subscale scores were compared with paired t-tests, and individual items with paired Wilcoxon tests. Linear regression examined association with CGM adherence. 121/140 parents and 91/99 children ≥10 years had complete data. Mean Behavior subscale score decreased from 21.1 (SD 5.9) to 17.2 (SD 6.1) (p < .001) for children, and 20.7 (SD 7.5) to 17.4 (7.4) (p < .001) for parents. Mean Worry subscale score decreased from 17.9 (SD 11.9) to 11.9 (SD 11.4) (p < .001) for children, and 23.1 (SD 13.2) to 17.6 (SD 10.4) (p < .001) for parents. Median scores for 10/25 child items and 12/25 parent items were significantly lower at 12 months (p < .001). Linear regression found no association between HFS scores and CGM adherence. Insulin pump therapy with CGM offering LGS significantly reduced fear of hypoglycemia not related to CGM adherence in children with type 1 diabetes and their parents.

Association between scanning frequency of flash glucose monitoring and continuous glucose monitoring-derived glycemic makers in children and adolescents with type 1 diabetes

BACKGROUND

We assessed the association between scanning frequency of flash glucose monitoring (FGM) and continuous glucose monitoring (CGM)-derived glycemic markers in children and adolescents with type 1 diabetes.

METHODS

Subjects consisted of 85 children and adolescents with type 1 diabetes using FGM. We assessed the association between scanning frequencies of FGM- and CGM-derived metrics: Time in range (TIR) (70-180 mg/dL), time below range (TBR) (<70 mg/dL), time above range (>180 mg/dL), and other glycemic markers - laboratory-measured HbA1c and CGM-estimated glucose and HbA1c (eA1c) levels in the subjects.

RESULTS

The mean number of scans was 11.5 ± 3.5 (5-20) times per day, and scanning was most frequently conducted during a period of 18-24 h. Scanning frequency showed significant positive correlation with TIR (r = 0.719, P < 0.0001) and inverse correlation with time above range (r = -0.743, P < 0.0001), but did not correlate with TBR. There were also significant inverse correlations between scanning frequency and glucose, HbA1c, and eA1c levels (r = -0.765, -0.815, and -0.793, respectively, P < 0.0001).

CONCLUSIONS

Frequent glucose testing with FGM decreased hyperglycemia with increased TIR, but did not reduce TBR. Coping with a rapid fall of glucose and unexpected hypoglycemia with more advanced technology might contribute to a reduction in TBR.

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 < 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).

The efficacy and safety of insulin pump therapy with predictive low glucose suspend feature in decreasing hypoglycemia in children with type 1 diabetes mellitus: A systematic review and meta-analysis

BACKGROUND

Automated insulin delivery with predictive low glucose suspend (PLGS) feature has the potential to reduce risk of hypoglycemia in patients with type 1 diabetes mellitus (T1DM). We aim to systematically synthesize the evidence on the efficacy and safety of PLGS in children and adolescents with T1DM.

METHODS

We performed a systematic search through Ovid/MEDLINE, Ovid/Embase, and other search engines. We included randomized controlled trials (RCTs) evaluating the effect of sensor augmented pump (SAP) with PLGS feature compared to SAP or insulin pump therapy without SAP in decreasing hypoglycemia in children and adolescents aged 2 to 18 years with T1DM, with at least 2 weeks of follow-up. Two reviewers independently selected studies, extracted data, and evaluated the risk of bias (ROB).

RESULTS

Five RCTs with total sample size of 493 children aged 6 to 18 years met the inclusion criteria. The overall ROB of included studies was low. There is high quality evidence that PLGS is superior to SAP in decreasing time spent in hypoglycemia (sensor glucose [SG] <3.9 mmol/L [<70 mg/dL]/24 h) and nocturnal hypoglycemia (SG <3.9 mmol [<70 mg/dL]/L/night) with an absolute mean difference of 17.4 min/d (95% CI: -19.2, -15.5) and 26.3 min/night (95% CI: -35.5, -16.7), respectively, without increasing percentage of time spent in hyperglycemia or episodes of diabetic ketoacidosis (DKA). There was insufficient evidence for the impact of PLGS on health related quality of life (HRQL).

CONCLUSIONS

PLGS is superior to SAP in decreasing daytime and nocturnal hypoglycemia without increasing the risk of DKA or hyperglycemia. Future studies should address the impact of PLGS on children younger than 6-years-old and HRQL.

A clinical review of the t:slim X2 insulin pump

Insulin pumps are commonly used for intensive insulin therapy to treat type 1 diabetes in adults and youth. Insulin pump technologies have advanced dramatically in the last several years to integrate with continuous glucose monitors (CGM) and incorporate control algorithms. These control algorithms automate some insulin delivery in response to the glucose information received from the CGM to reduce the occurrence of hypoglycemia and hyperglycemia and improve overall glycemic control. The t:slim X2 insulin pump system became commercially available in 2016. It is an innovative insulin pump technology that can be updated remotely by the user to install new software onto the pump device as new technologies become available. Currently, the t:slim X2 pairs with the Dexcom G6 CGM and there are two advanced software options available: Basal-IQ, which is a predictive low glucose suspend (PLGS) technology, and Control-IQ, which is a Hybrid Closed Loop (HCL) technology. This paper will describe the different types of advanced insulin pump technologies, review how the t:slim X2 insulin pump works, and summarize the clinical studies leading to FDA approval and commercialization of the Basal-IQ and Control-IQ technologies.

Repeated measures random forests (RMRF): Identifying factors associated with nocturnal hypoglycemia

Nocturnal hypoglycemia is a common phenomenon among patients with diabetes and can lead to a broad range of adverse events and complications. Identifying factors associated with hypoglycemia can improve glucose control and patient care. We propose a repeated measures random forest (RMRF) algorithm that can handle nonlinear relationships and interactions and the correlated responses from patients evaluated over several nights. Simulation results show that our proposed algorithm captures the informative variable more often than naïvely assuming independence. RMRF also outperforms standard random forest and extremely randomized trees algorithms. We demonstrate scenarios where RMRF attains greater prediction accuracy than generalized linear models. We apply the RMRF algorithm to analyze a diabetes study with 2524 nights from 127 patients with type 1 diabetes. We find that nocturnal hypoglycemia is associated with HbA1c, bedtime blood glucose (BG), insulin on board, time system activated, exercise intensity, and daytime hypoglycemia. The RMRF can accurately classify nights at high risk of nocturnal hypoglycemia.

Predicting Nocturnal Hypoglycemia from Continuous Glucose Monitoring Data with Extended Prediction Horizon

Nocturnal hypoglycemia is a serious complication of insulin-treated diabetes, which commonly goes undetected. Continuous glucose monitoring (CGM) devices have enabled prediction of impending nocturnal hypoglycemia, however, prior efforts have been limited to a short prediction horizon (~ 30 minutes). To this end, a nocturnal hypoglycemia prediction model with a 6-hour horizon (midnight-6 am) was developed using a random forest machine- learning model based on data from 10,000 users with more than 1 million nights of CGM data. The model demonstrated an overall nighttime hypoglycemia prediction performance of ROC AUC = 0.84, with AUC = 0.90 for early night (midnight-3 am) and AUC = 0.75 for late night (prediction at midnight, looking at 3-6 am window). While instabilities and the absence of late-night blood glucose patterns introduce predictability challenges, this 6-hour horizon model demonstrates good performance in predicting nocturnal hypoglycemia. Additional study and specific patient-specific features will provide refinements that further ensure safe overnight management of glycemia.

How does a predictive low glucose suspend (PLGS) system tackle pediatric lifespan challenges in diabetes treatment? Real world data analysis

OBJECTIVES

The aim of the study was to assess the benefits of a predictive low glucose suspend (PLGS) system in real-life in children and adolescents with type 1 diabetes of different age and age-related clinical challenges.

METHODS

Real life retrospective and descriptive analysis included 44 children (26 girls) with type 1 diabetes who were introduced to PLGS system. We divided them in three age groups: I (3-6 years old, n = 12), II (7-10 y/o, n = 16), III (11-19 y/o, n = 16). All children and their caregivers received unified training in self-management during PLGS therapy. Patients' data included: age, HbA1C levels, sex. While from the CGM metric, we obtained: time of sensor use (SENSuse), time in range (TiR): in, below and over target range and average blood glycemia (AVG), insulin suspension time (INSsusp).

RESULTS

SENSuse was 93% in total, with 92%, 94%, and 87% in age groups I, II, III, respectively. In total the reduction of mean HbA1C from 7.61% to 6.88% (P < .05), while for the I, II, and III it was 7.46% to 6.72%, 6.91% to 6.41%, and 8.46 to 7.44%, respectively (P < .05). Although we observed a significant reduction of HbA1C, the time below target range was minimal. Specific findings included: group I-longest INSsusp (17%), group II-lowest glycemic variability (CV) (36%), and group III-highest AVG (169 mg/dL). There was a reverse correlation between suspend before low and age (-0.32, P < .05). In group I CV reduced TiR in target range (TiRin) (-0.82, P < .05), in group II use of complex boluses increased TiRin (0.52, P < .05). In group III higher CV increased HbA1C (0.64, P < .05) while reducing TiRin (-0.72, P < .05).

CONCLUSIONS

PLGS is a suitable and safe therapeutic option for children with diabetes of all age and it is effective in addressing age-specific challenges. PLGS improves glycemic control in children of all age, positively affecting its different parameters.

Automated Insulin Delivery in Children with Type 1 Diabetes

The advent of insulin pump therapy marked an important milestone in diabetes treatment in the past few decades and has become the tipping point for the development of automated insulin delivery systems (AID). Standalone insulin pump systems have evolved over the course of years and have been replaced by modern high-technology insulin pumps with continuous glucose monitor interface allowing real-time insulin dose adjustment to optimize treatment. This review summarizes evidence from AID studies conducted in children with type 1 diabetes and discusses the outlook for future generation AID systems from a pediatric treatment perspective.

Realizing a Closed-Loop (Artificial Pancreas) System for the Treatment of Type 1 Diabetes

Recent, rapid changes in the treatment of type 1 diabetes have allowed for commercialization of an "artificial pancreas" that is better described as a closed-loop controller of insulin delivery. This review presents the current state of closed-loop control systems and expected future developments with a discussion of the human factor issues in allowing automation of glucose control. The goal of these systems is to minimize or prevent both short-term and long-term complications from diabetes and to decrease the daily burden of managing diabetes. The closed-loop systems are generally very effective and safe at night, have allowed for improved sleep, and have decreased the burden of diabetes management overnight. However, there are still significant barriers to achieving excellent daytime glucose control while simultaneously decreasing the burden of daytime diabetes management. These systems use a subcutaneous continuous glucose sensor, an algorithm that accounts for the current glucose and rate of change of the glucose, and the amount of insulin that has already been delivered to safely deliver insulin to control hyperglycemia, while minimizing the risk of hypoglycemia. The future challenge will be to allow for full closed-loop control with minimal burden on the patient during the day, alleviating meal announcements, carbohydrate counting, alerts, and maintenance. The human factors involved with interfacing with a closed-loop system and allowing the system to take control of diabetes management are significant. It is important to find a balance between enthusiasm and realistic expectations and experiences with the closed-loop system.

A Review of Predictive Low Glucose Suspend and Its Effectiveness in Preventing Nocturnal Hypoglycemia

To evaluate the effectiveness of predictive low glucose suspend (PLGS) systems within sensor-augmented insulin infusion pumps at preventing nocturnal hypoglycemia in patients with type 1 diabetes (DM1), we performed a systematic review and meta-analysis of randomized crossover trials. Pubmed and Google Scholar were searched for randomized crossover trials, published between January 2013 and July 2018, in nonpregnant outpatients with DM1, which compared event rates during PLGS overnight periods and non-PLGS overnight periods. The primary outcome was the proportion of overnight periods with one or more hypoglycemic measurement. When available, individual patient data were used to assess the effect of clustering measurements within patients. Four studies (272 patients, 10,735 patient-nights: 5422 PLGS and 5313 non-PLGS) were included in the meta-analysis. Two studies reported patient-level data that permitted assessment of the effect of clustering measurements within patients. The effect on the risk difference was minimal. The proportion of overnight periods with one or more episodes of hypoglycemia was 19.6% for the PLGS periods and 27.8% for the non-PLGS periods. Based on the pooled estimate, PLGS overnight periods were associated with an 8.8% lower risk of hypoglycemia (risk difference -0.088; 95% CI -0.119 to -0.056, I² = 67.4%, τ² = 0.0006, 4 studies). PLGS systems can reduce nocturnal hypoglycemic events in patients with DM1.

The hypoglycemia-prevention effect of sensor-augmented pump therapy with predictive low glucose management in Japanese patients with type 1 diabetes mellitus: a short-term study

Aims/introduction

The predictive low glucose management (PLGM) system was introduced in March 2018 in Japan. Although there are some reports demonstrating the benefit of PLGM in preventing hypoglycemia, no data are currently available in Japanese patients with type 1 diabetes mellitus (T1DM). The aim of the present study is to evaluate the effect of PLGM with sensor-augmented pump therapy in the prevention of hypoglycemia in Japanese patients.

Materials and methods

We included 16 patients with T1DM who used the MiniMed^®640G system after switching from the MiniMed^®620G system. We retrospectively analysed the data of the continuous glucose monitoring system in 1 month after switching to MiniMed^®640G.

Results

The area under the curve (AUC) of hypoglycemia of < 70 mg/dL was lowered from 0.42 ± 0.43 mg/dL day to 0.18 ± 0.18 mg/dL day (P = 0.012). Correspondingly, the duration of severe hypoglycemia (< 54 mg/dL) was reduced significantly from 15.3 ± 21.7 min/day to 4.8 ± 6.9 min/day (P = 0.019). The duration of hypoglycemia was reduced, but the reduction was not significant. Regarding the AUC for hyperglycemia > 180 mg/dL and the duration of hyperglycemia did not change. With the PLGM function, 79.3% of the predicted hypoglycemic events were avoided.

Conclusions

The hypoglycemia avoidance rate was comparable to those in previous reports. In addition, we demonstrated that PLGM can markedly suppress severe hypoglycemia without deteriorating glycemic control in Japanese T1DM patients. It is necessary to further investigate the effective use of the PLGM feature such as establishing a lower limit and the timing of resumption.

A Clinical Overview of Insulin Pump Therapy for the Management of Diabetes: Past, Present, and Future of Intensive Therapy

IN BRIEF Insulin pump therapy is advancing rapidly. This article summarizes the variety of insulin pump technologies available to date and discusses important clinical considerations for each type of technology.

Combining continuous glucose monitoring and insulin pumps to automatically tune the basal insulin infusion in diabetes therapy: a review

For individuals affected by Type 1 diabetes (T1D), a chronic disease in which the pancreas does not produce any insulin, maintaining the blood glucose (BG) concentration as much as possible within the safety range (70–180 mg/dl) allows avoiding short- and long-term complications. The tuning of exogenous insulin infusion can be difficult, especially because of the inter- and intra-day variability of physiological and behavioral factors. Continuous glucose monitoring (CGM) sensors, which monitor glucose concentration in the subcutaneous tissue almost continuously, allowed improving the detection of critical hypo- and hyper-glycemic episodes. Moreover, their integration with insulin pumps for continuous subcutaneous insulin infusion allowed developing algorithms that automatically tune insulin dosing based on CGM measurements in order to mitigate the incidence of critical episodes. In this work, we aim at reviewing the literature on methods for CGM-based automatic attenuation or suspension of basal insulin with a focus on algorithms, their implementation in commercial devices and clinical evidence of their effectiveness and safety.

Nocturnal Hypoglycemic Alarm Based on Near-Infrared Spectroscopy: In Vivo Studies with a Rat Animal Model

A noninvasive method for detecting episodes of nocturnal hypoglycemia is demonstrated with in vivo measurements made with a rat animal model. Employing spectra collected from the near-infrared combination region of 4000-5000 cm^-1, piecewise linear discriminant analysis (PLDA) is used to classify spectra into alarm and nonalarm data classes on the basis of whether or not they correspond to glucose concentrations below a user-defined hypoglycemic threshold. A reference spectrum and corresponding glucose concentration are acquired at the start of the monitoring period, and spectra are then collected continuously and converted to absorbance units relative to the initial reference spectrum. The resulting differential spectra correspond to differential glucose concentrations that reflect the differences in concentration between each spectrum and the reference. Given an alarm threshold (e.g., 3.0 mM), a database of calibration differential spectra can be partitioned into two groups containing spectra above and below the threshold. A classification model is then computed with PLDA. The resulting model can be applied to the differential spectra collected during the monitoring period in order to identify spectra whose corresponding glucose concentrations lie in the hypoglycemic range. In this work, the alarm algorithm was tested in two single-day studies performed with anesthetized rats. Glucose concentrations spanned the range of 1.6 to 13.5 mM (29 to 244 mg/dL). For both rats, the alarm algorithm performed well. On average, 87.5% of alarm events were correctly detected, and the occurrence of false alarms was 7.2%. False alarms were restricted to times when the glucose concentrations were very close to the alarm threshold rather than at random times, thus demonstrating the potential of the approach for practical use.

The road from intermittently scanned glucose monitoring to hybrid closed-loop systems: Part A. Keys to success: subject profiles, choice of systems, education

Managing type 1 diabetes (T1DM) is challenging and requires intensive glucose monitoring and titration of insulin in order to reduce the risk of complications. The use of continuous glucose monitoring (CGM) systems, either flash or intermittently scanned glucose monitoring (isCGM) or real-time (RT) CGM, has positively affected the management of type 1 diabetes with the potential to lower HbA1c, enhance time spent in range, reduce frequency and time spent in hypoglycemia and hyperglycemia, lower glycemic variability, and improve quality of life. In recent years, both CGM and pump technology have advanced, with improved functional features and integration, including low glucose suspend (LGS), predictive low glucose suspend (PLGS), and hybrid closed-loop (HCL) systems. In this review, we highlight the benefits and limitations of use of isCGM/RT-CGM for open-loop control and recent progress in closed-loop control systems. We also discuss different subject profiles for the different systems, and focus on educational aspects that are key to successful use of the systems.

Impact of Sensor-Augmented Pump Therapy with Predictive Low-Glucose Suspend Function on Glycemic Control and Patient Satisfaction in Adults and Children with Type 1 Diabetes

AIMS

The aim was to evaluate the effectiveness of sensor-augmented pump therapy with predictive low-glucose suspend function (SAP-PLGS) in real-world use in children and adults with type 1 diabetes (T1D).

METHODS

Patients with T1D treated with the MiniMed 640G^® pump with PLGS function at three referral hospitals were retrospectively evaluated. Hb_A1c at baseline and at 6, 12, 18, and 24 months was analyzed. Two weeks of data from pumps, sensors, and/or glucose meters were downloaded. Patients completed satisfaction questionnaires at the last follow-up visit.

RESULTS

A total of 162 patients were included. Mean age was 32 ± 17 years, 28% were (n = 46) children, and 29% (n = 47) were with a history of severe hypoglycemia. Median follow-up was 12 months (6-18). Hb_A1c was reduced from 55 ± 9 to 54 ± 8 mmol/mol (7.2% ± 0.8% to 7.1% ± 0.7%) at 12 months (P < 0.03, n = 100). In patients with suboptimal control, there was a reduction in Hb_A1c from 66% ± 7% to 61 ± 10 mmol/mol (8.2% ± 0.6% to 7.7% ± 0.9%) at the end of follow-up (n = 26, P < 0.01). Three percent (n = 5) of the patients experienced severe hypoglycemia during follow-up. A reduction in the percentage of self-monitoring of blood glucose values <70 mg/dL was achieved (10% ± 7% to 6% ± 5%, P = 0.001, n = 144). Time in range 70-180 mg/dL was 67% ± 13% at the end of follow-up and predictors of a higher time in range were identified. The use of sensors was high (86%) and 73% of the patients showed high satisfaction. In patients using sensors at baseline (n = 54), the time spent at <54 and <70 mg/dL was reduced.

CONCLUSION

SAP-PLGS reduces hypoglycemia frequency while maintaining glycemic control in adults and children under real-life conditions.

Predictive Low-Glucose Suspend Reduces Hypoglycemia in Adults, Adolescents, and Children With Type 1 Diabetes in an At-Home Randomized Crossover Study: Results of the PROLOG Trial

OBJECTIVE

This study evaluated a new insulin delivery system designed to reduce insulin delivery when trends in continuous glucose monitoring (CGM) glucose concentrations predict future hypoglycemia.

RESEARCH DESIGN AND METHODS

Individuals with type 1 diabetes (n = 103, age 6-72 years, mean HbA_1c 7.3% [56 mmol/mol]) participated in a 6-week randomized crossover trial to evaluate the efficacy and safety of a Tandem Diabetes Care t:slim X2 pump with Basal-IQ integrated with a Dexcom G5 sensor and a predictive low-glucose suspend algorithm (PLGS) compared with sensor-augmented pump (SAP) therapy. The primary outcome was CGM-measured time <70 mg/dL.

RESULTS

Both study periods were completed by 99% of participants; median CGM usage exceeded 90% in both arms. Median time <70 mg/dL was reduced from 3.6% at baseline to 2.6% during the 3-week period in the PLGS arm compared with 3.2% in the SAP arm (difference [PLGS - SAP] = -0.8%, 95% CI -1.1 to -0.5, P < 0.001). The corresponding mean values were 4.4%, 3.1%, and 4.5%, respectively, represent-ing a 31% reduction in the time <70 mg/dL with PLGS. There was no increase in mean glucose concentration (159 vs. 159 mg/dL, P = 0.40) or percentage of time spent >180 mg/dL (32% vs. 33%, P = 0.12). One severe hypoglycemic event occurred in the SAP arm and none in the PLGS arm. Mean pump suspension time was 104 min/day.

CONCLUSIONS

The Tandem Diabetes Care Basal-IQ PLGS system significantly reduced hypoglycemia without rebound hyperglycemia, indicating that the system can benefit adults and youth with type 1 diabetes in improving glycemic control.

Analyzing the Potential of Advanced Insulin Dosing Strategies in Patients With Type 2 Diabetes: Results From a Hybrid In Silico Study

BACKGROUND

The ongoing improvement of continuous glucose monitoring (CGM) sensors and of insulin pumps are paving the way for a fast implementation of artificial pancreas (AP) for type 1 diabetes (T1D) patients. The case for type 2 diabetes (T2D) patients is less obvious since usually some residual beta cell function allows for simpler therapy approaches, and even multiple daily injections (MDI) therapy is not very widespread. However, the number of insulin dependent T2D patients is vastly increasing and therefore a need for understanding chances and challenges of an automated insulin therapy arises. Based on this background, this article analyzes conditions under which the use of more advanced therapeutic approaches, particularly AP, could bring a substantial improvement and should be considered as a viable therapy option.

METHOD

Data of 14 insulin-treated T2D patients on MDI wearing a CGM device and deviation analysis methods were used to estimate the expected improvements in the clinical outcome by using self-monitoring of blood glucose (SMBG) with advanced carbohydrate counting, a full AP or intermediate approaches, either CGM measurements with MDI therapy or SMBG with insulin pump. HbA1C and time in range (70-140 mg/dl, 70-180 mg/dl, respectively) were used as a performance measure. Outcome measures beyond glycemic control (eg, compliance, patient acceptance) have not been analyzed in this study.

RESULTS

AP has the potential to improve the condition of many poorly controlled insulin-treated T2D patients. However, as the interpatient variability is much higher than in T1D, a prescreening is recommended to select suitable patients.

CONCLUSIONS

Clinical criteria need to be developed for inclusion/exclusion of T2D patients for AP related therapies.

Technology in the management of type 1 diabetes mellitus - current status and future prospects

Type 1 diabetes mellitus (T1DM) represents 5-10% of diabetes cases worldwide. The incidence of T1DM is increasing, and there is no immediate prospect of a cure. As such, lifelong management is required, the burden of which is being eased by novel treatment modalities, particularly from the field of diabetes technologies. Continuous glucose monitoring has become the standard of care and includes factory-calibrated subcutaneous glucose monitoring and long-term implantable glucose sensing. In addition, considerable progress has been made in technology-enabled glucose-responsive insulin delivery. The first hybrid insulin-only closed-loop system has been commercialized, and other closed-loop systems are under development, including dual-hormone glucose control systems. This Review focuses on well-established diabetes technologies, including glucose sensing, pen-based insulin delivery, data management and data analytics. We also cover insulin pump therapy, threshold-based suspend, predictive low-glucose suspend and single-hormone and dual-hormone closed-loop systems. Clinical practice recommendations for insulin pump therapy and continuous glucose monitoring are presented, and ongoing research and future prospects are highlighted. We conclude that the management of T1DM is improved by diabetes technology for the benefit of the majority of people with T1DM, their caregivers and guardians and health-care professionals treating patients with T1DM.

Predictive hyperglycemia and hypoglycemia minimization: In-home double-blind randomized controlled evaluation in children and young adolescents

OBJECTIVE

The primary objective of this trial was to evaluate the feasibility, safety, and efficacy of a predictive hyperglycemia and hypoglycemia minimization (PHHM) system vs predictive low glucose suspension (PLGS) alone in optimizing overnight glucose control in children 6 to 14 years old.

RESEARCH DESIGN AND METHODS

Twenty-eight participants 6 to 14 years old with T1D duration ≥1 year with daily insulin therapy ≥12 months and on insulin pump therapy for ≥6 months were randomized per night into PHHM mode or PLGS-only mode for 42 nights. The primary outcome was percentage of time in sensor-measured range 70 to 180 mg/dL in the overnight period.

RESULTS

The addition of automated insulin delivery with PHHM increased time in target range (70-180 mg/dL) from 66 ± 11% during PLGS nights to 76 ± 9% during PHHM nights (P<.001), without increasing hypoglycemia as measured by time below various thresholds. Average morning blood glucose improved from 176 ± 28 mg/dL following PLGS nights to 154 ± 19 mg/dL following PHHM nights (P<.001).

CONCLUSIONS

The PHHM system was effective in optimizing overnight glycemic control, significantly increasing time in range, lowering mean glucose, and decreasing glycemic variability compared to PLGS alone in children 6 to 14 years old.

Diabetes in Childhood and Adolescence

BACKGROUND

The incidence of type 1 diabetes mellitus in childhood and adolescence is steadily rising and now stands at 22.9 new cases per year per 100 000 persons up to age 15.

METHODS

This review is based on pertinent publications retrieved by a selective literature search, with special attention to the current German S3 guideline on diabetes in childhood and adolescence.

RESULTS

Polydipsia, polyuria, and weight loss are the characteristic presenting symptoms of diabetes mellitus. The acutely presenting patient needs immediate stabilization because of the danger of rapid metabolic decompensation (risk of keto - acidosis, 21.1%). Long-term insulin therapy can be delivered either by subcutaneous injection or by an insulin pump. The goals of treatment are the near-normalization of glucose metabolism (HbA1c <7.5%), the avoidance of acute complications (hypoglycemia and ketoacidosis), the reduction of diabetes-specific sequelae (retinopathy, nephropathy, neuropathy, hypertension, and hyperlipidemia), unrestricted participation in age-appropriate everyday activities, and normal physical and psychosocial development. Children and adolescents with diabetes need individualized treatment with frequent adjustments and holistic overall care so that these goals can be effectively met.

CONCLUSION

Every physician must be able to diagnose the initial presentation of diabetes and to initiate the first steps in its management. The patient should be referred as soon as possible to a diabetes team that has experience in the treatment of children and adolescents.

Reduction in Hypoglycemia With the Predictive Low-Glucose Management System: A Long-term Randomized Controlled Trial in Adolescents With Type 1 Diabetes

OBJECTIVE

Short-term studies with automated systems that suspend basal insulin when hypoglycemia is predicted have shown a reduction in hypoglycemia; however, efficacy and safety have not been established in long-term trials.

RESEARCH DESIGN AND METHODS

We conducted a 6-month, multicenter, randomized controlled trial in children and adolescents with type 1 diabetes using the Medtronic MiniMed 640G pump with Suspend before low (predictive low-glucose management [PLGM]) compared with sensor-augmented pump therapy (SAPT) alone. The primary outcome was percentage time in hypoglycemia with sensor glucose (SG) <3.5 mmol/L (63 mg/dL).

RESULTS

In an intent-to-treat analysis of 154 subjects, 74 subjects were randomized to SAPT and 80 subjects to PLGM. At baseline, the time with SG <3.5 mmol/L was 3.0% and 2.8% in the SAPT and PLGM groups, respectively. During the study, PLGM was associated with a reduction in hypoglycemia compared with SAPT (% time SG <3.5 mmol/L: SAPT vs. PLGM, 2.6 vs. 1.5, P < 0.0001). A similar effect was also noted in time with SG <3 mmol/L (P < 0.0001). This reduction was seen both during day and night (P < 0.0001). Hypoglycemic events (SG <3.5 mmol/L for >20 min) also declined with PLGM (SAPT vs. PLGM: events/patient-year 227 vs. 139, P < 0.001). There was no difference in glycated hemoglobin (HbA_1c) at 6 months (SAPT 7.6 ± 1.0% vs. PLGM 7.8 ± 0.8%, P = 0.35). No change in quality of life measures was reported by participants/parents in either group. There were no PLGM-related serious adverse events.

CONCLUSIONS

In children and adolescents with type 1 diabetes, PLGM reduced hypoglycemia without deterioration in glycemic control.

Glucose-responsive insulin delivery for type 1 diabetes: The artificial pancreas story

Insulin replacement therapy is integral to the management of type 1 diabetes, which is characterised by absolute insulin deficiency. Optimal glycaemic control, as assessed by glycated haemoglobin, and avoidance of hyper- and hypoglycaemic excursions have been shown to prevent diabetes-related complications. Insulin pump use has increased considerably over the past decade with beneficial effects on glycaemic control, quality of life and treatment satisfaction. The advent and progress of ambulatory glucose sensor technology has enabled continuous glucose monitoring based on real-time glucose levels to be integrated with insulin therapy. Low glucose and predictive low glucose suspend systems are currently used in clinical practice to mitigate against hypoglycaemia, and provide the first step towards feedback glucose control. The more advanced technology approach, an artificial pancreas or a closed-loop system, gradually increases and decreases insulin delivery in a glucose-responsive fashion to mitigate against hyper- and hypoglycaemia. Randomised outpatient clinical trials over the past 5 years have demonstrated the feasibility, safety and efficacy of the approach, and the recent FDA approval of the first single hormone closed-loop system establishes a new standard of care for people with type 1 diabetes.

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.