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

Glucose sensor with predictive alarm for hypoglycaemia: Improved glycaemic control in adolescents with type 1 diabetes

AIM

Hypoglycaemic events are linked to microvascular and macrovascular complications in people with type 1 diabetes. We aimed to evaluate the efficacy of glucose sensor [real-time continuous glucose monitoring (RT-CGM)] with predictive alarm (PA) in reducing the time spent below the range (%TBR <70 mg/dl) in a group of adolescents with type 1 diabetes (AwD).

MATERIALS AND METHODS

This was a crossover, monocentric and randomized study. RT-CGM was set with Alarm on Threshold (AoT) at 70 mg/dl) or PA for hypoglycaemia (20 m before threshold). Twenty AwD were enrolled and randomized to either a PA/AoT or AoT/PA treatment sequence, in a 1:1 ratio. The two groups (PA vs. AoT) were compared using two-way repeated measures ANOVA taking account of the carryover effect.

RESULTS

AwD using PA for hypoglycaemia spent less time in severe hypoglycaemia (%TBR2 <54 mg/dl; 0.32 ± 0.31 vs. 0.91 ± 0.90; p < .02) and hypoglycaemia (%TBR <70 mg/dl; 1.68 ± 1.06 vs. 2.90 ± 2.05; p < .02), with better glycaemia risk index (51.3 ± 11.0 vs. 61.5 ± 12.6; p ≤ .01).

CONCLUSION

The use of RT-CGM with PA for hypoglycaemia technology in AwD using multiple daily insulin injection treatment could significantly reduce the risk of having hypoglycaemic events resulting in an improved quality of glucose control.

CLINICAL TRIAL REGISTRATION NUMBER

NCT05574023.

Safety, Metabolic and Psychological Outcomes of Medtronic MiniMed 780G™ in Children, Adolescents and Young Adults: A Systematic Review

The MiniMed™ 780G is a second-generation automated insulin delivery system that implements a modified proportional-integral-derivative algorithm with some features of an MD-Logic artificial pancreas algorithm. The system may deliver automatic correction boluses up to every 5 min, and it allows the user to choose between three glucose target setpoints (100, 110 and 120 mg/dL). We aimed to review the current evidence on this device in children, adolescents, and young adults living with type 1 diabetes. We screened 783 papers, but only 31 manuscripts were included in this review. Data on metabolic outcomes show that this system is safe as regards severe hypoglycaemia and diabetic ketoacidosis. The glycated haemoglobin may drop to levels about 7%, with CGM reports showing a time in range of 75-80%. The time above range and the time below range are within the recommended target in most of the subjects. Few studies evaluated the psychological outcomes. This system seems to be more effective than the first-generation automated insulin delivery systems. The MiniMed™ 780G has been associated with an improvement in sleep quality in subjects living with diabetes and their caregivers, along with an improvement in treatment satisfaction. Psychological distress is as reduced as the glucose control is improved. We also discuss some case reports describing particular situations in clinical practice. Finally, we think that data show that this system is a further step towards the improvement of the treatment of diabetes as concerns both metabolic and psychological outcomes.

Evidence from clinical trials on high-risk medical devices in children: a scoping review

BACKGROUND

Meeting increased regulatory requirements for clinical evaluation of medical devices marketed in Europe in accordance with the Medical Device Regulation (EU 2017/745) is challenging, particularly for high-risk devices used in children.

METHODS

Within the CORE-MD project, we performed a scoping review on evidence from clinical trials investigating high-risk paediatric medical devices used in paediatric cardiology, diabetology, orthopaedics and surgery, in patients aged 0-21 years. We searched Medline and Embase from 1st January 2017 to 9th November 2022.

RESULTS

From 1692 records screened, 99 trials were included. Most were multicentre studies performed in North America and Europe that mainly had evaluated medical devices from the specialty of diabetology. Most had enrolled adolescents and 39% of trials included both children and adults. Randomized controlled trials accounted for 38% of the sample. Other frequently used designs were before-after studies (21%) and crossover trials (20%). Included trials were mainly small, with a sample size <100 participants in 64% of the studies. Most frequently assessed outcomes were efficacy and effectiveness as well as safety.

CONCLUSION

Within the assessed sample, clinical trials on high-risk medical devices in children were of various designs, often lacked a concurrent control group, and recruited few infants and young children.

IMPACT

In the assessed sample, clinical trials on high-risk medical devices in children were mainly small, with variable study designs (often without concurrent control), and they mostly enrolled adolescents. We provide a systematic summary of methodologies applied in clinical trials of medical devices in the paediatric population, reflecting obstacles in this research area that make it challenging to conduct adequately powered randomized controlled trials. In view of changing European regulations and related concerns about shortages of high-risk medical devices for children, our findings may assist competent authorities in setting realistic requirements for the evidence level to support device conformity certification.

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.

Levothyroxine personalized treatment: is it still a dream?

Levothyroxine is a milestone in the treatment of all causes of hypothyroidism. From 19th century till today, Levothyroxine experienced a great advancement, from hypodermic injections of an extract of the thyroid gland of a sheep to novel formulations, known to circumvent malabsorption issue. However, the rate of patients on suboptimal therapy is still high. Current Guidelines are clear, daily Levothyroxine dosage should be calculated based on body weight. However, we are still far away from the possibility to administer the right dosage to the right patient, for several reasons. We retrace the history of treatment with levothyroxine, pointing out strengths and weaknesses of different formulations, with particular attention to what keeps us away from tailored therapy. In the age of digitalization, the pharmaceutical industry has been giving rising importance to Digital therapeutics, that are known to be effective in reaching target therapies. By combining current knowledge of hypothyroidism therapy with cutting-edge technology, we also hypothesized what could be the future strategies to be developed in this field.

Utility and precision evidence of technology in the treatment of type 1 diabetes: a systematic review

BACKGROUND

The greatest change in the treatment of people living with type 1 diabetes in the last decade has been the explosion of technology assisting in all aspects of diabetes therapy, from glucose monitoring to insulin delivery and decision making. As such, the aim of our systematic review was to assess the utility of these technologies as well as identify any precision medicine-directed findings to personalize care.

METHODS

Screening of 835 peer-reviewed articles was followed by systematic review of 70 of them (focusing on randomized trials and extension studies with ≥50 participants from the past 10 years).

RESULTS

We find that novel technologies, ranging from continuous glucose monitoring systems, insulin pumps and decision support tools to the most advanced hybrid closed loop systems, improve important measures like HbA1c, time in range, and glycemic variability, while reducing hypoglycemia risk. Several studies included person-reported outcomes, allowing assessment of the burden or benefit of the technology in the lives of those with type 1 diabetes, demonstrating positive results or, at a minimum, no increase in self-care burden compared with standard care. Important limitations of the trials to date are their small size, the scarcity of pre-planned or powered analyses in sub-populations such as children, racial/ethnic minorities, people with advanced complications, and variations in baseline glycemic levels. In addition, confounders including education with device initiation, concomitant behavioral modifications, and frequent contact with the healthcare team are rarely described in enough detail to assess their impact.

CONCLUSIONS

Our review highlights the potential of technology in the treatment of people living with type 1 diabetes and provides suggestions for optimization of outcomes and areas of further study for precision medicine-directed technology use in type 1 diabetes.

Glycometabolic outcomes in adult type 1 diabetic patients switching to closed-loop systems

OBJECTIVE

This study aimed to evaluate glycometabolic outcomes in AID technology-naïve T1D patients after switching to Hybrid Closed Loop (HCL) and Advanced Hybrid Closed Loop (AHCL) systems.

RESEARCH DESIGN AND METHODS

This was a 12-month, prospective, observational, two-center study on 54 type 1 diabetes (T1D) patients aged 19-65 years managed with multiple daily injections (MDI) or Continuous Subcutaneous Insulin Infusion (CSII) in open-loop to evaluate the superiority in terms of effectiveness and safety of Automated Insulin Delivery (AID) systems.

RESULTS

HbA1c levels significantly improved at the end of the study. Time spent with glucose levels in target range (TIR70-180 mg/dL, 3.9-10 mmol/L) increased from 50.5 ± 15.6% at baseline to 73.6 ± 8.0% at 12 months (p < 0.001); time spent above range (TAR180-250 mg/dL, 10-13.9 mmol/L and TAR≥250 mg/dL, 13.9 mmol/L) decreased from 30.6 ± 9.0% and 14.2 ± 10.2 at baseline to 19.3 ± 5.3% and 4.8 ± 3.3% at 12 months (p < 0.001 for both), respectively; time spent below range (TBR54-69 mg/dL, 3-3.8 mmol/L and TBR<54 mg/dL, 3.0 mmol/L) decreased from 3.5 ± 2.6% and 1.2 ± 1.4% at baseline to 1.9 ± 1.5% and 0.4 ± 0.7% at the end of the study (p < 0.001 for both); coefficient of variation (CV) decreased from 35.9 ± 7.8% at baseline to 33.0 ± 5.3% (p < 0.05). Satisfaction with the new technology was scored as high.

CONCLUSION

AID-naïve T1D patients switching to HCL/AHCL systems have significantly and safely improved their glycometabolic outcomes with their high satisfaction with the new type of treatment.

Real-life data of hypoglycemic events in children and adolescents with type 1 diabetes

INTRODUCTION

Hypoglycemia composes an always present risk in the treatment of type 1 diabetes (T1D) and can be a fatal complication. Many studies on hypoglycemic events are based on self-reported data or focused on the aggregated time below range. We have processed continuous glucose monitoring (CGM) data in children and adolescents with T1D in order to examine all occurring hypoglycemic events.

RESEARCH DESIGN AND METHODS

CGM data (mean 168±3 days) from 214 children and adolescents with T1D were analyzed using computer-based algorithms. Patients were divided into three groups based on estimated HbA1c (eHbA1c): (1) ≤48 mmol/mol (n=58); (2) 49-64 mmol/mol (n=113); (3) ≥65 mmol/mol (n=43). The groups were compared concerning descriptive data and CGM metrics with emphasis on the frequency of hypoglycemic events.

RESULTS

Only one self-reported event of severe hypoglycemia was registered, while 54 390 hypoglycemic events (<3.9 mmol/L (<70 mg/dL)) were identified from CGM data out of which 11 740 were serious (<3.0 mmol/L (<54 mg/dL)). On average there were 1.5±0.1 hypoglycemic events per 24 hours out of which 1.2±0.1 were mild (3.0-3.9 mmol/L) and 0.3±0.02 serious. Group 1 had a higher frequency of both total and mild hypoglycemic events compared with both groups 2 and 3. However, the frequency of serious hypoglycemic events was similar in all groups. A negative correlation was observed for eHbA1c and total daily and mild hypoglycemic events (r=-0.57 and r=-0.66, respectively, p<0.0001), whereas for serious hypoglycemic events there was only a borderline significance (r=-0.13, p=0.05).

CONCLUSIONS

This study shows that hypoglycemic events are a frequent phenomenon in children and adolescents with T1D, occurring regardless of overall metabolic control. Although patients with an HbA1c ≤48 mmol/mol had a higher frequency of mild hypoglycemic events there was no increase in serious hypoglycemic events.

Current Technologies for Managing Type 1 Diabetes Mellitus and Their Impact on Quality of Life-A Narrative Review

Type 1 diabetes mellitus is a chronic autoimmune disease that affects millions of people and generates high healthcare costs due to frequent complications when inappropriately managed. Our paper aimed to review the latest technologies used in T1DM management for better glycemic control and their impact on daily life for people with diabetes. Continuous glucose monitoring systems provide a better understanding of daily glycemic variations for children and adults and can be easily used. These systems diminish diabetes distress and improve diabetes control by decreasing hypoglycemia. Continuous subcutaneous insulin infusions have proven their benefits in selected patients. There is a tendency to use more complex systems, such as hybrid closed-loop systems that can modulate insulin infusion based on glycemic readings and artificial intelligence-based algorithms. It can help people manage the burdens associated with T1DM management, such as fear of hypoglycemia, exercising, and long-term complications. The future is promising and aims to develop more complex ways of automated control of glycemic levels to diminish the distress of individuals living with diabetes.

Management of type 1 diabetes in pregnancy: update on lifestyle, pharmacological treatment, and novel technologies for achieving glycaemic targets

Glucose concentrations within target, appropriate gestational weight gain, adequate lifestyle, and, if necessary, antihypertensive treatment and low-dose aspirin reduces the risk of pre-eclampsia, preterm delivery, and other adverse pregnancy and neonatal outcomes in pregnancies complicated by type 1 diabetes. Despite the increasing use of diabetes technology (ie, continuous glucose monitoring and insulin pumps), the target of more than 70% time in range in pregnancy (TIRp 3·5-7·8 mmol/L) is often reached only in the final weeks of pregnancy, which is too late for beneficial effects on pregnancy outcomes. Hybrid closed-loop (HCL) insulin delivery systems are emerging as promising treatment options in pregnancy. In this Review, we discuss the latest evidence on pre-pregnancy care, management of diabetes-related complications, lifestyle recommendations, gestational weight gain, antihypertensive treatment, aspirin prophylaxis, and the use of novel technologies for achieving and maintaining glycaemic targets during pregnancy in women with type 1 diabetes. In addition, the importance of effective clinical and psychosocial support for pregnant women with type 1 diabetes is also highlighted. We also discuss the contemporary studies examining HCL systems in type 1 diabetes during pregnancies.

The Medtronic 780G advanced hybrid closed-loop system achieves and maintains good glycaemic control in type 1 diabetes adults despite previous treatment

INTRODUCTION

Improvements in continuous glucose monitoring (CGM) in recent years have changed the treatment of type 1 diabetes (T1D) by permitting the automation of glucose control. The Minimed 780G advanced hybrid closed-loop (ACHL) system adapts basal infusion rates and delivers auto-correction boluses in order to achieve a user-decided glucose target (100, 110 or 120mg/dL). This study set out to evaluate the effectiveness of the Medtronic 780G system in real-life conditions over 6 months.

MATERIALS AND METHODS

Prospective study that included T1D subjects previously treated with insulin pump without CGM (pump group) or with sensor-augmented pump with predictive low-glucose suspend (SAP-PLGS group) who started with the Minimed 780G system. Sensor and pump data from baseline, and at 1, 3 and 6 months were downloaded and HbA1c was recorded at baseline and at 6 months.

RESULTS

Fifty T1D subjects were included; 25 were previous SAP-PLGS 640G users and 25 used 640G without CGM. 66% were female, 48.6 (40-57) years of age with 20 (12-31.5) years of diabetes duration. Time in range (TIR) improved in the total cohort from baseline to 6 months (69% (57.7-76) vs. 74% (70-82); p=0.01 as did HbA1c (7.6% (7.1-7.8) vs. 7.0% (6.8-7.5); p<0.001), with improvement in times <54, >180 and >250mg/dL. Outcomes at 6 months did not differ between groups, although the SAP-PLGS subjects were prone to hypoglycaemia and the pump group mainly presented suboptimal metabolic control.

CONCLUSION

The AHCL Medtronic Minimed 780G system achieves and maintains good glycaemic control over 6 months in real-life conditions in different profiles of T1D subjects.

The Advanced Diabetes Technologies for Reduction of the Frequency of Hypoglycemia and Minimizing the Occurrence of Severe Hypoglycemia in Children and Adolescents with Type 1 Diabetes

Hypoglycemia is an often-observed acute complication in the management of children and adolescents with type 1 diabetes. It causes inappropriate glycemic outcomes and may impair the quality of life in the patients. Severe hypoglycemia with cognitive impairment, such as a convulsion and coma, is a lethal condition and is associated with later-onset cognitive impairment and brain-structural abnormalities, especially in young children. Therefore, reducing the frequency of hypoglycemia and minimizing the occurrence of severe hypoglycemia are critical issues in the management of children and adolescents with type 1 diabetes. Advanced diabetes technologies, including continuous glucose monitoring and sensor-augmented insulin pumps with low-glucose suspension systems, can reduce the frequency of hypoglycemia and the occurrence of severe hypoglycemia without aggravating glycemic control. The hybrid closed-loop system, an automated insulin delivery system, must be the most promising means to achieve appropriate glycemic control with preventing severe hypoglycemia. The use of these advanced diabetes technologies could improve glycemic outcomes and the quality of life in children and adolescents with type 1 diabetes.

Improved Glycemia with Hybrid Closed-Loop Versus Continuous Subcutaneous Insulin Infusion Therapy: Results from a Randomized Controlled Trial

Objective: To evaluate safety and effectiveness of MiniMed™ 670G hybrid closed loop (HCL) in comparison with continuous subcutaneous insulin infusion (CSII) therapy for 6 months in persons with type 1 diabetes (T1D). Methods: Adults (aged 18-80 years), adolescents, and children (aged 2-17 years) with T1D who were using CSII therapy were enrolled and randomized (1:1) to 6 months of HCL intervention (n = 151, mean age of 39.9 ± 19.8 years) or CSII without continuous glucose monitoring (n = 151, 35.7 ± 18.4 years). Primary effectiveness endpoints included change in A1C for Group 1 (baseline A1C >8.0%), from baseline to the end of study, and difference in the end of study percentage of time spent below 70 mg/dL (%TBR <70 mg/dL) for Group 2 (baseline A1C ≤8.0%), to show superiority of HCL intervention versus control. Secondary effectiveness endpoints were change in A1C and %TBR <70 mg/dL for Group 2 and Group 1, respectively, to show noninferiority of HCL intervention versus control. Primary safety endpoints were rates of severe hypoglycemia and diabetic ketoacidosis (DKA). Results: Change in A1C and difference in %TBR <70 mg/dL for the overall group were significantly improved, in favor of HCL intervention. In addition, a significant mean (95% confidence interval) change in A1C was observed for both Group 1 (-0.8% [-1.1% to -0.4%], P < 0.0001) and Group 2 (-0.3% [-0.5% to -0.1%], P < 0.0001), in favor of HCL intervention. The same was observed for difference in %TBR <70 mg/dL for Group 1 (-2.2% [-3.6% to -0.9%]) and Group 2 (-4.9% [-6.3% to -3.6%]) (P < 0.0001 for both). There was one DKA event during run-in and six severe hypoglycemic events: two during run-in and four during study (HCL: n = 0 and CSII: n = 4 [6.08 per 100 patient-years]). Conclusions: This RCT demonstrates that the MiniMed 670G HCL safely and significantly improved A1C and %TBR <70 mg/dL compared with CSII control in persons with T1D, irrespective of baseline A1C level.

Managing Severe Hypoglycaemia in Patients with Diabetes: Current Challenges and Emerging Therapies

Hypoglycaemia is common in patients with diabetes mellitus and is a limiting factor for achieving adequate glycaemic control. In the vast majority of cases, hypoglycaemia develops due to the imbalance between food intake and insulin injections. As recurrent hypoglycaemia leads to significant morbidity and mortality, the recognition and immediate treatment of hypoglycaemia in diabetic patients is thus important. In the last 20 years, the introduction of improved insulin analogues, insulin pump therapy, continuous glucose monitoring (CGM), and sensor-augmented pump therapy have all made significant improvements in helping to reduce and prevent hypoglycaemia. In terms of treatment, the American Diabetes Association recommends oral glucose as the first-line treatment option for all conscious patients with hypoglycaemia. The second line of treatment (or first line in unconscious patients) is the use of glucagon. Novel formulations of glucagon include the nasal form, the Gvoke HypoPen which is a ready-to-deliver auto-injector packaged formulation and finally a glucagon analogue, Dasiglucagon. The Dasiglucagon formulation has recently been approved for the treatment of severe hypoglycaemia. It is a ready-to-use, similar to endogenous glucagon and its potency is also the same as native glucagon. It does not require reconstitution before injection and therefore ensures better compliance. Thus, significant improvements including development of newer insulin analogues, insulin pump therapy, continuous glucose monitoring (CGM), sensor-augmented pump therapy and novel formulations of glucagon have all contributed to reducing and preventing hypoglycaemia in diabetic individuals. However, considerable challenges remain as not all patients have access to diabetes technologies and to the newer glucagon formulations to help reduce and prevent hypoglycaemia.

Continuous Glucose Monitor, Insulin Pump, and Automated Insulin Delivery Therapies for Type 1 Diabetes: An Update on Potential for Cardiovascular Benefits

PURPOSE OF REVIEW

The incidence of type 1 diabetes (T1D) is rising in all age groups. T1D is associated with chronic microvascular and macrovascular complications but improving glycemic trends can delay the onset and slow the progression of these complications. Utilization of technological devices for diabetes management, such as continuous glucose monitors (CGM) and insulin pumps, is increasing, and these devices are associated with improvements in glycemic trends. Thus, device use may be associated with long-term prevention of T1D complications, yet few studies have investigated the direct impacts of devices on chronic complications in T1D. This review will describe common diabetes devices and combination systems, as well as review relationships between device use and cardiovascular outcomes in T1D.

RECENT FINDINGS

Findings from existing cohort and national registry studies suggest that pump use may aid in improving cardiovascular risk factors such as hypertension and dyslipidemia. Furthermore, pump users have been shown to have lower arterial stiffness and better measures of myocardial function. In registry and case-control longitudinal data, pump use has been associated with fewer cardiovascular events and reduction of cardiovascular disease (CVD) and all-cause mortality. CVD is the leading cause of morbidity and mortality in T1D. Consistent use of diabetes devices may protect against the development and progression of macrovascular complications such as CVD through improvement in glycemic trends. Existing literature is limited, but findings suggest that pump use may reduce acute cardiovascular risk factors as well as chronic cardiovascular complications and overall mortality in T1D.

Long-term efficacy of sensor-augmented pump therapy (Minimed 640G system) combined with a telemedicine follow-up in patients with type 1 diabetes: A real life study

Objective

Evaluate the efficacy of a new modality of insulin therapy associating both the sensor-augmented pump therapy with predictive low-glucose management (SAP-PLGM) and a telemedicine follow-up in patients with Type 1 diabetes (T1D) in a real-life setting.

Methods

T1D adults under Minimed 640G system with a telemedicine follow-up for glucose management were included in a retrospective study. The primary endpoint was HbA1c while continuous glucose monitoring parameters (CGM) and treatment compliance were the secondary endpoints. These parameters were analyzed according to the therapeutic indication, HbA1c ≥ 8 % (Group A) or severe hypoglycemic events (Group B) and in patients switched to SAP-PLGM therapy.

Results

62 patients were analyzed with a 28 ± 12 months of follow-up. In Group A, HbA1c decreased from 8.3 ± 0.4 % to 7.7 ± 0.7 % (p < 0.05) and to 7.9 ± 0.3 % (p < 0.05) after 2 and 3 years, respectively. In patients switched to SAP-PLGM therapy, HbA1c decreased from 7.7 ± 0.7 % to 7.2 ± 0.8 % (p < 0.05) at 2 years. After 6 months, the time-below-range (<70 mg/dL) decreased from 2.1 % [0.6-4] to 1.1 % [0.3-2.6] (p < 0.05). Severe hypoglycemic events decreased from 1.62 to 0.5 events/patient/year in Group B (p < 0.05). At 3 years, treatment compliance was 92 % [70-97] in the total population.

Conclusions

Long-term real-life treatment with the SAP-PLGM therapy combined with telemedicine was associated with improved glycemic control in T1D, along with high treatment compliance.

Open-Source Automated Insulin Delivery in Type 1 Diabetes

BACKGROUND

Open-source automated insulin delivery (AID) systems are used by many patients with type 1 diabetes. Data are needed on the efficacy and safety of an open-source AID system.

METHODS

In this multicenter, open-label, randomized, controlled trial, we assigned patients with type 1 diabetes in a 1:1 ratio to use an open-source AID system or a sensor-augmented insulin pump (control). The patients included both children (defined as 7 to 15 years of age) and adults (defined as 16 to 70 years of age). The AID system was a modified version of AndroidAPS 2.8 (with a standard OpenAPS 0.7.0 algorithm) paired with a preproduction DANA-i insulin pump and Dexcom G6 CGM, which has an Android smartphone application as the user interface. The primary outcome was the percentage of time in the target glucose range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter) between days 155 and 168 (the final 2 weeks of the trial).

RESULTS

A total of 97 patients (48 children and 49 adults) underwent randomization (44 to open-source AID and 53 to the control group). At 24 weeks, the mean (±SD) time in the target range increased from 61.2±12.3% to 71.2±12.1% in the AID group and decreased from 57.7±14.3% to 54.5±16.0% in the control group (adjusted difference, 14 percentage points; 95% confidence interval, 9.2 to 18.8; P<0.001), with no treatment effect according to age (P = 0.56). Patients in the AID group spent 3 hours 21 minutes more in the target range per day than those in the control group. No severe hypoglycemia or diabetic ketoacidosis occurred in either group. Two patients in the AID group withdrew from the trial owing to connectivity issues.

CONCLUSIONS

In children and adults with type 1 diabetes, the use of an open-source AID system resulted in a significantly higher percentage of time in the target glucose range than the use of a sensor-augmented insulin pump at 24 weeks. (Supported by the Health Research Council of New Zealand; Australian New Zealand Clinical Trials Registry number, ACTRN12620000034932.).

Sensor-Augmented Insulin Pump with Predictive Low-Glucose Suspend (PLGS): Determining Optimal Settings of Pump and Sensor in a Multicenter Cohort of Patients with Type 1 Diabetes

INTRODUCTION

The use of predictive low-glucose suspend (PLGS) sensor-augmented pumps has been shown to lead to a significant reduction in hypoglycemic episodes in patients with type 1 diabetes (T1D), but their effects on hyperglycemia exposure are heterogeneous. The aim of this study was to determine the settings of the Medtronic 640G system to obtain the optimal balance between occurrence of both hypoglycemia and hyperglycemia.

METHODS

The hypo- and hyperglycemia area under the curve (AUC), as well as system settings [hypoglycemic threshold, mean insulin total daily dose (TDD), mean basal insulin percentage, and mean daily duration of PLGS] were collected between 2 and 12 times during 1 year in patients from four university hospital centers. Univariate/multivariate analyses and receiver operating characteristics (ROC) curves were performed to determine factors associated with hyper- and hypoglycemia AUC.

RESULTS

A total of 864 observations were analyzed from 110 patients with T1D. Two preselected settings predictive of low hyperglycemia AUC were a basal insulin percentage < 52.0% [sensitivity (Se) = 0.66 and specificity (Sp) = 0.53] and a PLGS duration > 157.5 min/day (Se = 0.47 and Sp = 0.73). The preselected setting predictive of a low hypoglycemia AUC was a PLGS duration ≤ 174.4 min (Se = 0.83 and Sp = 0.51). Between-visit variation of PLGS and TDD was positively correlated (r = 0.61; p < 0.0001).

CONCLUSION

The most important Medtronic 640G setting was the mean daily PLGS duration, where a value between 157.5 and 174.4 min/day was associated with the best reduction in both hypo- and hyperglycemia AUC. In this study, we showed that PLGS duration could be indirectly modified through total daily insulin dose adaptation.

TRIAL REGISTRATION

This study is registered in clinicaltrials.gov (NCT03047486).

One-Year Real-World Study on Comparison among Different Continuous Subcutaneous Insulin Infusion Devices for the Management of Pediatric Patients with Type 1 Diabetes: The Supremacy of Hybrid Closed-Loop Systems

Since their advent in daily clinical practice, continuous subcutaneous insulin infusion (CSII) systems have been increasingly improved, leading to a high percentage of both adult and pediatric patients with diabetes now using insulin pumps. Different types of CSII systems are currently available, which are characterized by different settings and technical features. This longitudinal observational study aims to evaluate real-word glycemic outcomes in children and adolescents with type 1 diabetes using three different CSII devices: hybrid closed-loop (HCL) systems, predictive low glucose (PLGS) systems, and non-automated insulin pumps. The secondary objective was to identify clinical variables that may significantly influence the achievement of therapeutic goals in our study cohort. One-hundred-and-one patients on CSII therapy attending our pediatric diabetes center were enrolled. When compared with the non-automated group, patients using HCL systems showed higher levels of time in target glucose range (p = 0.003) and lower glucose variability (p = 0.008). Similarly, we found significantly better glucose metrics in HCL users in comparison to PLGS patients (time in range p = 0.008; coefficient of variation p = 0.009; time above 250 mg/dL p = 0.007). Multiple linear regression models showed that HCL systems (time in range p < 0.001) and high daily percentage of glycemic sensor use (time in range p = 0.031) are predictors for good glycemic control. The introduction and increasing availability of novel technologies for diabetes represent a promising strategy to improve glycemic control and quality of life in pediatric patients with type 1 diabetes. Our real-world data confirm the superiority of HCL systems in terms of improvement of time spent in the target glucose range, prevention of hypoglycemia, and reduction of glycemic variability.

Spanish Translation and Linguistic Validation of the Glucose Monitoring Experiences Questionnaire (GME-Q) in Continuous Glucose Monitoring Users

BACKGROUND AND AIMS

The use of continuous glucose monitoring (CGM) has become standard practice in people with type 1 diabetes. The evaluation of user satisfaction is crucial. The Glucose Monitoring Experiences questionnaire (GME-Q) includes 23 items with a 5-point Likert scale to produce a total satisfaction score and three subscale scores. The study aimed to translate the GME-Q from English into Spanish and to validate its use in Spanish-speaking CGM users with type 1 diabetes.

METHODS

The linguistic translation and validation process of the GME-Q was established. T1D CGM users were asked to complete the produced Spanish version of the GME-Q and interviewed about difficulties or misunderstandings. Total satisfaction, effectiveness, convenience and intrusiveness subscales and internal consistency reliability were computed.

RESULTS

Forward and backward translations and cognitive debriefing produced a final version of the GME-Q in Spanish. Ninety-eight subjects with type 1 diabetes were selected (age: 40 ± 12 years, 63% females, Hb1c: 7.2 ± 0.9% (55 ± 10 mmol/l), pump users: 78%, CGM use: 3.7 ± 2.6 years). The completion rate was 99% and the Cronbach's alpha coefficient was 0.8. The total satisfaction score was 3.9 ± 0.4 (effectiveness: 4.1 ± 0.6, convenience: 3.8 ± 0.6, intrusiveness: 2.2 ± 0.7).

CONCLUSION

The GME-Q was translated into Spanish and validated for Spanish-speaking CGM users with type 1 diabetes.

Real-world evidence on clinical outcomes of people with type 1 diabetes using open-source and commercial automated insulin dosing systems: A systematic review

AIMS

Several commercial and open-source automated insulin dosing (AID) systems have recently been developed and are now used by an increasing number of people with diabetes (PwD). This systematic review explored the current status of real-world evidence on the latest available AID systems in helping to understand their safety and effectiveness.

METHODS

A systematic review of real-world studies on the effect of commercial and open-source AID system use on clinical outcomes was conducted employing a devised protocol (PROSPERO ID 257354).

RESULTS

Of 441 initially identified studies, 21 published 2018-2021 were included: 12 for Medtronic 670G; one for Tandem Control-IQ; one for Diabeloop DBLG1; two for AndroidAPS; one for OpenAPS; one for Loop; three comparing various types of AID systems. These studies found that several types of AID systems improve Time-in-Range and haemoglobin A_1c (HbA_1c ) with minimal concerns around severe hypoglycaemia. These improvements were observed in open-source and commercially developed AID systems alike.

CONCLUSIONS

Commercially developed and open-source AID systems represent effective and safe treatment options for PwD of several age groups and genders. Alongside evidence from randomized clinical trials, real-world studies on AID systems and their effects on glycaemic outcomes are a helpful method for evaluating their safety and effectiveness.

Cost-Effectiveness Analysis of an Advanced Hybrid Closed-Loop Insulin Delivery System in People with Type 1 Diabetes in Greece

AbstractIntroduction: Usage of automated insulin delivery systems is increasing for the treatment of people with type 1 diabetes (T1D). This study compared long-term cost-effectiveness of the Advanced Hybrid Closed Loop MiniMed 780G (AHCL) system versus sensor augmented pump (SAP) system with predictive low glucose management (PLGM) or multiple daily injections (MDI) plus intermittently scanned continuous glucose monitoring (isCGM) in people with T1D in Greece. Methods: Analyses were performed using the IQVIA CORE Diabetes Model, with clinical input data sourced from various studies. In the AHCL versus SAP plus PLGM analysis, patients were assumed to have 7.5% baseline glycated hemoglobin (HbA1c), when comparing AHCL with MDI plus isCGM baseline HbA1c was assumed to be 7.8%. HbA1c was reduced to 7.0% following AHCL treatment initiation but remained at baseline levels in the comparator arms. Analyses were performed from a societal perspective over a lifetime time horizon. Future costs and clinical outcomes were discounted at 1.5% per annum. Results: AHCL was associated with increased quality-adjusted life expectancy of 0.284 quality-adjusted life years (QALYs) and EUR 10,173 lower mean total lifetime costs with SAP plus PLGM. Compared with MDI plus isCGM, AHCL was associated with increased quality-adjusted life expectancy of 2.708 QALYs, EUR 76,396 higher mean total lifetime costs, and an incremental cost-effectiveness ratio of EUR 29,869 per QALY. Extensive sensitivity analysis confirmed the robustness of results. Conclusions: Over patient lifetime, the MiniMed 780G system is likely to be cost saving compared with the SAP plus PLGM system and cost-effective compared with MDI plus isCGM in people with T1D in Greece.

Switching from predictive low glucose suspend to advanced hybrid closed loop control: Effects on glucose control and patient reported outcomes

AIMS

Automated insulin delivery improves glucose control. Aim of this study was to compare in real life the effects on glucose control and patient reported outcomes of an advanced hybrid closed loop system (Control-IQ), versus a simpler system with predictive low glucose suspend function (Basal-IQ).

METHODS

Thirty-one type 1 diabetic subjects were studied during Basal-IQ and after switching to Control-IQ. Variables analyzed were time spent in range (70-180 mg/dL), in tight range (70-140 mg/dL), above range (>180 mg/dL), below range (<70 mg/dL), mean glucose, coefficient of variation and glycated hemoglobin. Questionnaires were administered regarding therapy satisfaction (Diabetes Treatment Satisfaction Questionnaire in status/change form), fear of hypoglycemia (Hypoglycemia Fear Survey), quality of sleep (Pittsburgh Sleep Quality Index).

RESULTS

After 12 weeks of Control-IQ, time in range increased from 62.7 to 74.0%, p < 0.0001, time in tight range increased from 37.1 to 44.6 %, p < 0.001, time above range decreased from 35.6 to 24.4% p < 0.0001. Improvements were observed in mean glucose and glucose variability. Glycated hemoglobin decreased from 7.0% (53 mmol/mol) to 6.6% (49 mmol/mol), p < 0.0001. Subjects using Control-IQ manifested greater satisfaction and less fear of hypoglycemia.

CONCLUSION

Compared to Basal-IQ, Control-IQ improves glucose control and therapy satisfaction.

Effect of nationwide reimbursement of real-time continuous glucose monitoring on HbA1c, hypoglycemia and quality of life in a pediatric type 1 diabetes population: The RESCUE-pediatrics study

OBJECTIVE

Real-time continuous glucose monitoring (RT-CGM) can improve metabolic control and quality of life (QoL), but long-term real-world data in children with type 1 diabetes (T1D) are scarce. Over a period of 24 months, we assessed the impact of RT-CGM reimbursement on glycemic control and QoL in children/adolescents with T1D treated with insulin pumps.

RESEARCH DESIGN AND METHODS

We conducted a multicenter prospective observational study. Primary endpoint was the change in HbA1c. Secondary endpoints included change in time in hypoglycemia, QoL, hospitalizations for hypoglycemia and/or ketoacidosis and absenteeism (school for children, work for parents).

RESULTS

Between December 2014 and February 2019, 75 children/adolescents were followed for 12 (n = 62) and 24 months (n = 50). Baseline HbA1c was 7.2 ± 0.7% (55 ± 8mmol/mol) compared to 7.1 ± 0.8% (54 ± 9mmol/mol) at 24 months (p = 1.0). Participants with a baseline HbA1c ≥ 7.5% (n = 27, mean 8.0 ± 0.3%; 64 ± 3mmol/mol) showed an improvement at 4 months (7.6 ± 0.7%; 60 ± 8mmol/mol; p = 0.009) and at 8 months (7.5 ± 0.6%; 58 ± 7mmol/mol; p = 0.006), but not anymore thereafter (endpoint 24 months: 7.7 ± 0.9%; 61 ± 10mmol/mol; p = 0.2). Time in hypoglycemia did not change over time. QoL for parents and children remained stable. Need for assistance by ambulance due to hypoglycemia reduced from 8 to zero times per 100 patient-years (p = 0.02) and work absenteeism for parents decreased from 411 to 214 days per 100 patient-years (p = 0.03), after 24 months.

CONCLUSION

RT-CGM in pump-treated children/adolescents with T1D showed a temporary improvement in HbA1c in participants with a baseline HbA1c ≥ 7.5%, without increasing time in hypoglycemia. QoL was not affected. Importantly, RT-CGM reduced the need for assistance by ambulance due to hypoglycemia and reduced work absenteeism for parents after 24 months.

CLINICAL TRIAL REGISTRATION

[ClinicalTrials.gov], identifier [NCT02601729].

Risk for ketonaemia in type 1 diabetes pregnancies with sensor-augmented pump therapy with predictive low glucose suspend compared with low glucose suspend: a crossover RCT

AIMS

To determine the frequency of ketonaemia in pregnant women with type 1 diabetes treated with a sensor-augmented pump (SAP) in predictive low glucose suspend (PLGS) mode compared with low glucose suspend (LGS) mode.

METHODS

An open-label crossover pilot RCT in ten women with type 1 diabetes treated with a 640 Medtronic insulin pump, with inclusion between 12-30 weeks of pregnancy. Participants were 1/1 randomly assigned (allocation by statistician using a permuted block size of 2) to either 2 weeks with an SAP in PLGS mode or 2 weeks in LGS mode. After the first 2 weeks, participants were switched to the other mode. Ketones in the participants' serum were measured three times daily (fasting, midday and evening) during the 4 weeks. The primary endpoint was the frequency of blood ketones > 0.6 mmol/l. Participants and healthcare providers were not blinded to group assignment for assessment of outcomes.

RESULTS

The median gestational week at inclusion was 12.5 weeks (12.0-15.0), participants had a median age of 31.5 years (24.0-33.0), BMI of 26.6 kg/m² (24.5-31.8), baseline HbA_1c of 41 mmol/mol (40-43; 5.9% [5.8-6.1]) and baseline time in range (TIR, 3.5-7.8 mmol/l) of 64.6% (55.6-68.7). Comparing the LGS mode with the PLGS mode, insulin suspension time per day was 2.0 h (1.3-2.3) vs 3.5 h (3.3-5.0; p = 0.002), ketonaemia > 0.6 mmol/l was 0% vs 0.5% (p = 1.000) and no participants had ketonaemia > 1 mmol/l. TIR on LGS was 64.7% (58.0-68.7) vs 61.1% (56.5-67.5) on PLGS (p = 0.492), time < 3.5 mmol/l was higher on LGS at 7.5% (4.6-8.3) vs 4.2% (2.4-6.9) on PLGS (p = 0.014). Treatment satisfaction and fear for hypoglycaemia were similar whether using LGS or PLGS mode.

CONCLUSIONS/INTERPRETATION

Despite longer time periods with suspended insulin delivery, pregnant women using an SAP in PLGS mode were not at higher risk of developing ketonaemia compared with those in LGS mode. Women with an SAP in PLGS mode had similar TIR with less time in hypoglycaemia.

TRIAL REGISTRATION

Clinical Trials NCT04292509 FUNDING: This research received no specific grant from any funding agency in the public, commercial or not-for-profit sectors.

Hybrid Closed-Loop Systems for the Treatment of Type 1 Diabetes: A Collaborative, Expert Group Position Statement for Clinical Use in Central and Eastern Europe

In both pediatric and adult populations with type 1 diabetes (T1D), technologies such as continuous subcutaneous insulin infusion (CSII), continuous glucose monitoring (CGM), or sensor-augmented pumps (SAP) can consistently improve glycemic control [measured as glycated hemoglobin (HbA1c) and time in range (TIR)] while reducing the risk of hypoglycemia. Use of technologies can thereby improve quality of life and reduce the burden of diabetes management compared with self-injection of multiple daily insulin doses (MDI). Novel hybrid closed-loop (HCL) systems represent the latest treatment modality for T1D, combining modern glucose sensors and insulin pumps with a linked control algorithm to offer automated insulin delivery in response to blood glucose levels and trends. HCL systems have been associated with increased TIR, improved HbA1c, and fewer hypoglycemic events compared with CSII, SAP, and MDI, thereby potentially improving quality of life for people with diabetes (PwD) while reducing the costs of treating short- and long-term diabetes-related complications. However, many barriers to their use and regional inequalities remain in Central and Eastern Europe (CEE). Published data suggest that access to diabetes technologies is hindered by lack of funding, underdeveloped health technology assessment (HTA) bodies and guidelines, unfamiliarity with novel therapies, and inadequacies in healthcare system capacities. To optimize the use of diabetes technologies in CEE, an international meeting comprising experts in the field of diabetes was held to map the current regional access, to present the current national reimbursement guidelines, and to recommend solutions to overcome uptake barriers. Recommendations included regional and national development of HTA bodies, efficient allocation of resources, and structured education programs for healthcare professionals and PwD. The responsibility of the healthcare community to ensure that all individuals with T1D gain access to modern technologies in a timely and economically responsible manner, thereby improving health outcomes, was emphasized, particularly for interventions that are cost-effective.

Real-world outcomes of two different sensor-augmented insulin pumps with predictive low glucose suspend function in type 1 diabetes patients

AIM

To analyse the real-life outcomes of two sensor-augmented pumps (SAP) with predictive low glucose suspend (PLGS) function, Medtronic Minimed 640G™ with SmartGuard (MM640G) and Tandem T Slim X2™ with Basal-IQ™ (TTSX2), in Type 1 Diabetes Mellitus (T1DM) patients.

METHODS

Observational cross-sectional study using data obtained from computerized clinical records. All T1DM patients on TTSX2 therapy were compared (1:1) with MM640G treated patients selected through stratified sampling. Primary efficacy outcome was to describe time in rage (TIR, 70-180 mg/dL, 3.9-10 mmol/L) interstitial glucose differences according to a non-inferiority hypothesis with TTSX2 compared to MM640G.

RESULTS

Forty-four patients were analyzed (female 66%). Mean age was 38.9 yrs. (range 23-59 yrs.) and mean diabetes duration was 23.4 ± 9.2 yrs. Patients treated with TTSX2 showed a numerically slightly lower, but non-statistically significantly different, TIR from the MM640G pump group (64.9 ± 16.4% vs. 72.4 ± 17.0%, P = 0.108). Similarly, we did no find differences in HbA1c between T1D patients treated with TTSX2 and MM640G (6.8 ± 1.0% vs. 7.0 ± 0.9%, 51 ± 11 mmol/mol vs. 53 ± 10 mmol/mol, P = 0.312). Moreover, rest of evaluated glycemic outcomes were similar between both treatment groups.

CONCLUSIONS

Patients using two different SAP with PLGS automatic function showed similar glycaemic control in a real-world scenario. NCT04741685.

The Cost-Effectiveness of an Advanced Hybrid Closed-Loop System in People with Type 1 Diabetes: a Health Economic Analysis in Sweden

INTRODUCTION

Swedish National Diabetes Registry data show a correlation of improved glycemic control in people with type 1 diabetes (T1D) with increased use of diabetes technologies over the past 25 years. However, novel technologies are often associated with a high initial outlay. The aim of the present study was to evaluate the long-term cost-effectiveness of the advanced hybrid closed-loop (AHCL) MiniMed 780G system versus intermittently scanned continuous glucose monitoring (isCGM) plus self-injection of multiple daily insulin (MDI) or continuous subcutaneous insulin infusion (CSII) in people with T1D in Sweden.

METHODS

Outcomes were projected over patients' lifetimes using the IQVIA CORE Diabetes Model (v9.0). Clinical data, including changes in glycated hemoglobin (HbA1c) and hypoglycemia rates, were sourced from observational studies and a randomized crossover trial. Modeled patients were assumed to receive the treatments for their lifetimes, with HbA1c kept constant following the application of treatment effects. Costs were accounted from a societal perspective and expressed in Swedish krona (SEK). Utilities and days off work estimates were taken from published sources.

RESULTS

The MiniMed 780G system was associated with an improvement in life expectancy of 0.16 years and an improvement in quality-adjusted life expectancy of 1.95 quality-adjusted life years (QALYs) versus isCGM plus MDI or CSII. These clinical benefits were due to a reduced incidence and a delayed time to onset of diabetes-related complications. Combined costs were estimated to be SEK 727,408 (EUR 72,741) higher with MiniMed 780G, with treatment costs partially offset by direct cost savings from the avoidance of diabetes-related complications and indirect cost savings from the avoidance of lost workplace productivity. The MiniMed 780G system was associated with an incremental cost-effectiveness ratio of SEK 373,700 per QALY gained.

CONCLUSIONS

Based on a willingness-to-pay threshold of SEK 500,000 per QALY gained, the MiniMed 780G system was projected to be cost-effective versus isCGM plus MDI or CSII for the treatment of T1D in Sweden.

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.

Newest Diabetes-Related Technologies for Pediatric Type 1 Diabetes and Its Impact on Routine Care: a Narrative Synthesis of the Literature

Purpose of Review

This review aims to address the actual state of the most advanced diabetes devices, as follows: continuous subcutaneous insulin infusions (CSII), continuous glucose monitoring systems (CGM), hybrid-closed loop (HCL) systems, and “Do-it-yourself” Artificial Pancreas Systems (DIYAPS) in children, adolescents, and young adults. This review has also the objective to assess the use of telemedicine for diabetes care across three different areas: education, social media, and daily care.

Recent Findings

Recent advances in diabetes technology after integration of CSII with CGM have increased the popularity of this treatment modality in pediatric age and shifted the standard diabetes management in many countries. We found an impressive transition from the use of CSII and/or CGM only to integrative devices with automated delivery systems. Although much has changed over the past 5 years, including a pandemic period that precipitated a broader use of telemedicine in diabetes care, some advances in technology may still be an additional burden of care for providers, patients, and caregivers. The extent of a higher rate of “auto-mode” use in diabetes devices while using the HCL/DIYAPS is essential to reduce the burden of diabetes treatment.

Summary

More studies including higher-risk populations are needed, and efforts should be taken to ensure proper access to cost-effective advanced technology on diabetes care.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40124-021-00248-7.

Management of glucose profile throughout strict COVID-19 lockdown by patients with type 1 diabetes prone to hypoglycaemia using sensor-augmented pump

AIMS

Spain has been one of the worst affected countries by the COVID-19 pandemic. A very strict lockdown at home was imposed with a tough restriction of mobility. We aimed to evaluate the impact of this exceptional scenario on glucose profile of patients with type 1 diabetes (T1D) prone to hypoglycaemia using sensor-augmented pump (SAP).

METHODS

Patients with T1D prone to hypoglycaemia using SAP (640G Medtronic-Minimed^®) for at least 6 months under the funding of a National Health Service were included in an observational, retrospective study. Data were collected in two periods: pre-lockdown (PL), February 23rd-March 7th and within lockdown (WL), April 1st to 14th 2020. The primary outcome was the difference in the proportion of time in target glucose range of 70-180 mg/dL (TIR). Additional glucometric data and total daily insulin were also analysed.

RESULTS

Fifty-nine patients were included: 33 women, age 46.17 ± 13.0 years and disease duration of 30.2 ± 12.0 years. TIR 70-180 mg/dL (67.6 ± 11.8 vs. 69.8 ± 12.0%), time > 180 (28.1 ± 13.6 vs. 25.5 ± 13.1%), time > 250 (6.9 ± 6.1 vs. 5.1 ± 4.8) and estimated HbA_1c (6.94 ± 0.8 vs. 6.75 ± 0.7%) significantly improved (PL vs. WL, respectively, p < 0.05). Time in hypoglycaemia, coefficient of variation, sensor usage and total daily insulin dose remained unchanged.

CONCLUSIONS

Lockdown conditions imposed by the COVID-19 pandemic may be managed successfully in terms of glycaemia control by population with DT1 prone to hypoglycaemia using SAP. The strict daily routine at home could probably explain the improvement in the time in glycemic target without increasing the time hypoglycaemia.

A multi-level hypoglycemia early alarm system based on sequence pattern mining

Background

Early alarm of hypoglycemia, detection of asymptomatic hypoglycemia, and effective control of blood glucose fluctuation make a great contribution to diabetic treatment. In this study, we designed a multi-level hypoglycemia early alarm system to mine potential information in Continuous Glucose Monitoring (CGM) time series and improve the overall alarm performance for different clinical situations.

Methods

Through symbolizing the historical CGM records, the Prefix Span was adopted to obtain the early alarm/non-alarm frequent sequence libraries of hypoglycemia events. The longest common subsequence was used to remove the common frequent sequence for achieving the hypoglycemia early alarm in different clinical situations. Then, the frequent sequence pattern libraries with different risk thresholds were designed as the core module of the proposed multi-level hypoglycemia early alarm system.

Results

The model was able to predict hypoglycemia events in the clinical dataset of level-I (sensitivity 85.90%, false-positive 23.86%, miss alarm rate 14.10%, average early alarm time 20.61 min), level-II (sensitivity 80.36%, false-positive 17.37%, miss alarm rate 19.63%, average early alarm time 27.66 min), and level-III (sensitivity 78.07%, false-positive 13.59%, miss alarm rate 21.93%, average early alarm time 33.80 min), respectively.

Conclusions

The proposed approach could effectively predict hypoglycemia events based on different risk thresholds to meet different prevention and treatment requirements. Moreover, the experimental results confirm the practicality and prospects of the proposed early alarm system, which reflects further significance in personalized medicine for hypoglycemia prevention.

Time in range centered diabetes care

Optimal glycemic control remains challenging and elusive for many people with diabetes. With the comprehensive clinical evidence on safety and efficiency in large populations, and with broader reimbursement, the adoption of continuous glucose monitoring (CGM) is rapidly increasing. Standardized visual reporting and interpretation of CGM data and clear and understandable clinical targets will help professionals and individuals with diabetes use diabetes technology more efficiently, and finally improve long-term outcomes with less everyday disease burden. For the majority of people with type 1 or type 2 diabetes, time in range (between 70 and 180 mg/dL, or 3.9 and 10 mmol/L) target of more than 70% is recommended, with each incremental increase of 5% towards this target being clinically meaningful. At the same time, the goal is to minimize glycemic excursions: a recommended target for a time below range (< 70 mg/dL or < 3.9 mmol/L) is less than 4%, and time above range (> 180 mg/dL or 10 mmol/L) less than 25%, with less stringent goals for older individuals or those at increased risk. These targets should be individualized: the personal use of CGM with the standardized data presentation provides all necessary means to accurately tailor diabetes management to the needs of each individual with diabetes.

Improved Real-World Glycemic Control With Continuous Glucose Monitoring System Predictive Alerts

BACKGROUND

Most standalone real-time continuous glucose monitoring (RT-CGM) systems provide predictive low and high sensor glucose (SG) threshold alerts. The durations and risk of low and high SG excursions following Guardian™ Connect CGM system predictive threshold alerts were evaluated.

METHODS

Continuous glucose monitoring system data uploaded between January 2, 2017 and May 22, 2018 by 3133 individuals using multiple daily injections (MDIs) or continuous subcutaneous insulin infusion (CSII) therapy were deidentified and retrospectively analyzed. Glucose excursions were defined as SG values that went beyond a preset low or high SG threshold for ≥15 minutes. For a control group, thresholds were based on the median of the low SG threshold limit (70 mg/dL) and the high SG threshold limit (210 mg/dL) preset by all system users. During periods when alerts were not enabled, timestamps were identified when a predictive alert would have been triggered. The time before low horizon was 17.5 minutes and the time before high horizon was 15 minutes, of all users who enabled alerts. Excursions occurring after a low SG or high SG predictive alert were segmented into prevented, ≤20, 20-60, and >60 minutes.

RESULTS

Excursions were prevented after 59% and 39% of low and high SG predictive alerts, respectively. The risk of a low or high excursion occurring was 1.9 (P < 0.001, 95% CI, 1.88-1.93) and 3.3 (P < 0.001, 95% CI, 3.20-3.30) times greater, respectively, when alerts were not enabled.

CONCLUSIONS

The predictive alerts of the RT-CGM system under study can help individuals living with diabetes prevent some real-world low and high SG excursions. This can be especially important for those unable to reach or maintain glycemic control with basic RT-CGM or CSII therapy.

Identification of Patient Perceptions That Can Affect the Uptake of Interventions Using Biometric Monitoring Devices: Systematic Review of Randomized Controlled Trials

Background

Biometric monitoring devices (BMDs) are wearable or environmental trackers and devices with embedded sensors that can remotely collect high-frequency objective data on patients’ physiological, biological, behavioral, and environmental contexts (for example, fitness trackers with accelerometer). The real-world effectiveness of interventions using biometric monitoring devices depends on patients’ perceptions of these interventions.

Objective

We aimed to systematically review whether and how recent randomized controlled trials (RCTs) evaluating interventions using BMDs assessed patients’ perceptions toward the intervention.

Methods

We systematically searched PubMed (MEDLINE) from January 1, 2017, to December 31, 2018, for RCTs evaluating interventions using BMDs. Two independent investigators extracted the following information: (1) whether the RCT collected information on patient perceptions toward the intervention using BMDs and (2) if so, what precisely was collected, based on items from questionnaires used and/or themes and subthemes identified from qualitative assessments. The two investigators then synthesized their findings in a schema of patient perceptions of interventions using BMDs.

Results

A total of 58 RCTs including 10,071 participants were included in the review (the median number of randomized participants was 60, IQR 37-133). BMDs used in interventions were accelerometers/pedometers (n=35, 60%), electrochemical biosensors (eg, continuous glucose monitoring; n=18, 31%), or ecological momentary assessment devices (eg, carbon monoxide monitors for smoking cessation; n=5, 9%). Overall, 26 (45%) trials collected information on patient perceptions toward the intervention using BMDs and allowed the identification of 76 unique aspects of patient perceptions that could affect the uptake of these interventions (eg, relevance of the information provided, alarm burden, privacy and data handling, impact on health outcomes, independence, interference with daily life). Patient perceptions were unevenly collected in trials. For example, only 5% (n=3) of trials assessed how patients felt about privacy and data handling aspects of the intervention using BMDs.

Conclusions

Our review showed that less than half of RCTs evaluating interventions using BMDs assessed patients’ perceptions toward interventions using BMDs. Trials that did assess perceptions often only assessed a fraction of them. This limits the extrapolation of the results of these RCTs to the real world. We thus provide a comprehensive schema of aspects of patient perceptions that may affect the uptake of interventions using BMDs and which should be considered in future trials.

Trial Registration

PROSPERO CRD42018115522; https://tinyurl.com/y5h8fjgx

Glycemic Outcomes of Use of CLC Versus PLGS in Type 1 Diabetes: A Randomized Controlled Trial

OBJECTIVE

Limited information is available about glycemic outcomes with a closed-loop control (CLC) system compared with a predictive low-glucose suspend (PLGS) system.

RESEARCH DESIGN AND METHODS

After 6 months of use of a CLC system in a randomized trial, 109 participants with type 1 diabetes (age range, 14-72 years; mean HbA_1c, 7.1% [54 mmol/mol]) were randomly assigned to CLC (N = 54, Control-IQ) or PLGS (N = 55, Basal-IQ) groups for 3 months. The primary outcome was continuous glucose monitor (CGM)-measured time in range (TIR) for 70-180 mg/dL. Baseline CGM metrics were computed from the last 3 months of the preceding study.

RESULTS

All 109 participants completed the study. Mean ± SD TIR was 71.1 ± 11.2% at baseline and 67.6 ± 12.6% using intention-to-treat analysis (69.1 ± 12.2% using per-protocol analysis excluding periods of study-wide suspension of device use) over 13 weeks on CLC vs. 70.0 ± 13.6% and 60.4 ± 17.1% on PLGS (difference = 5.9%; 95% CI 3.6%, 8.3%; P < 0.001). Time >180 mg/dL was lower in the CLC group than PLGS group (difference = -6.0%; 95% CI -8.4%, -3.7%; P < 0.001) while time <54 mg/dL was similar (0.04%; 95% CI -0.05%, 0.13%; P = 0.41). HbA_1c after 13 weeks was lower on CLC than PLGS (7.2% [55 mmol/mol] vs. 7.5% [56 mmol/mol], difference -0.34% [-3.7 mmol/mol]; 95% CI -0.57% [-6.2 mmol/mol], -0.11% [1.2 mmol/mol]; P = 0.0035).

CONCLUSIONS

Following 6 months of CLC, switching to PLGS reduced TIR and increased HbA_1c toward their pre-CLC values, while hypoglycemia remained similarly reduced with both CLC and PLGS.

Effect of real-life insulin pump with predictive low-glucose management use for 3 months: Analysis of the patients treated in a Japanese center

Aims/Introduction

In Japan, an insulin pump with predictive low‐glucose management (PLGM) was launched in 2018. It automatically suspends insulin delivery when the sensor detects or predicts low glucose values. The aim of this study was to analyze the safety and efficacy of PLGM in patients treated in a Japanese center.

Materials and Methods

We carried out a retrospective observational analysis of 16 patients with type 1 diabetes mellitus and one patient after pancreatectomy. They switched from the MiniMed 620G device to the 640G device with PLGM. The primary outcome was the change in the percentage of time in hypoglycemia. The secondary outcome was the change in HbA1c (%) over a period of 3 months. We also explored the presence of “post‐suspend hyperglycemia” with the 640G device.

Results

After changing to the 640G device, the percentage of time in hypoglycemia (glucose <50 mg/dL) significantly decreased from 0.39% (0–1.51%) to 0% (0–0.44%; P = 0.0407). The percentage of time in hyperglycemia (glucose >180 mg/dL) significantly increased from 25.53% (15.78–44.14%) to 32.9% (24.71–45.49%; P = 0.0373). HbA1c significantly increased from 7.6 ± 1.0% to 7.8 ± 1.1% (P = 0.0161). From 1.5 to 4.5 h after the resumption of insulin delivery, the percentage of time in hyperglycemia was 32.23% (24.2–53.75%), but it was significantly lower, 2.78% (0–21.6%), when patients manually restarted the pump within 30 min compared with automatic resumption 31.2% (20–61.66%; P = 0.0063).

Conclusions

Predictive low‐glucose management is an effective tool for reducing hypoglycemia, but possibly elicits “post‐suspend hyperglycemia.” This information is useful for achieving better blood glucose control in the patients treated with PLGM.

Effects of Continuous Glucose Monitoring on Metrics of Glycemic Control in Diabetes: A Systematic Review With Meta-analysis of Randomized Controlled Trials

BACKGROUND

Continuous glucose monitoring (CGM) provides important information to aid in achieving glycemic targets in people with diabetes.

PURPOSE

We performed a meta-analysis of randomized controlled trials (RCTs) comparing CGM with usual care for parameters of glycemic control in both type 1 and type 2 diabetes.

DATA SOURCES

Many electronic databases were searched for articles published from inception until 30 June 2019.

STUDY SELECTION

We selected RCTs that assessed both changes in HbA_1c and time in target range (TIR), together with time below range (TBR), time above range (TAR), and glucose variability expressed as coefficient of variation (CV).

DATA EXTRACTION

Data were extracted from each trial by two investigators.

DATA SYNTHESIS

All results were analyzed by a random effects model to calculate the weighted mean difference (WMD) with the 95% CI. We identified 15 RCTs, lasting 12-36 weeks and involving 2,461 patients. Compared with the usual care (overall data), CGM was associated with modest reduction in HbA_1c (WMD -0.17%, 95% CI -0.29 to -0.06, I ² = 96.2%), increase in TIR (WMD 70.74 min, 95% CI 46.73-94.76, I ² = 66.3%), and lower TAR, TBR, and CV, with heterogeneity between studies. The increase in TIR was significant and robust independently of diabetes type, method of insulin delivery, and reason for CGM use. In preplanned subgroup analyses, real-time CGM led to the higher improvement in mean HbA_1c (WMD -0.23%, 95% CI -0.36 to -0.10, P < 0.001), TIR (WMD 83.49 min, 95% CI 52.68-114.30, P < 0.001), and TAR, whereas both intermittently scanned CGM and sensor-augmented pump were associated with the greater decline in TBR.

LIMITATIONS

Heterogeneity was high for most of the study outcomes; all studies were sponsored by industry, had short duration, and used an open-label design.

CONCLUSIONS

CGM improves glycemic control by expanding TIR and decreasing TBR, TAR, and glucose variability in both type 1 and type 2 diabetes.

Effect of frequency of sensor use on glycaemic control in individuals on sensor-augmented pump therapy with and without Predictive Low Glucose Management System

Improved frequency of sensor use improves glycaemic control. Furthermore, there is no deterioration of glycaemic control with increased sensor use in individuals on Predictive Low Glucose Management (PLGM) system. Younger children are more likely to have better sensor uptake than older children.

Different Effects of Structured Education on Glycemic Control and Psychological Outcomes in Adolescent and Adult Patients with Type 1 Diabetes: A Systematic Review and Meta-Analysis

AIM

This systematic review aimed at investigating the effectiveness of structured education (SE) in improving glycemic control and psychological outcomes in adolescent and adult patients with type 1 diabetes.

METHODS

Electronic databases (EMBASE, Medline, PubMed, and the Cochrane Library) and the reference lists of included studies were searched from the beginning of the database through April 2019. Randomized controlled trials comparing SE with a control condition and reporting a change in glycosylated hemoglobin (HbA1c) level were included. The primary outcome was glycemic control measured by HbA1c. Secondary outcomes were diabetes-related distress, well-being, depression, and quality of life.

RESULTS

Eighteen studies representing 2759 patients were included. Twelve studies targeted adolescents and six targeted adults. Adolescent patients who were randomized to the intervention group did not show significant improvement of HbA1c in the short (SMD = -0.04; 95% CI: -0.14 to 0.06; P=0.41), medium (SMD = -0.03; 95% CI: -0.13 to 0.07; P=0.41), medium (SMD = -0.03; 95% CI: -0.13 to 0.07; P=0.41), medium (SMD = -0.03; 95% CI: -0.13 to 0.07; P=0.41), medium (SMD = -0.03; 95% CI: -0.13 to 0.07; P=0.41), medium (SMD = -0.03; 95% CI: -0.13 to 0.07.

CONCLUSIONS

Development of more efficient SE programs according to the patients' personal characteristics is needed.

Severe Hypoglycemia: Is It Still a Threat for Children and Adolescents With Type 1 Diabetes?

Severe hypoglycemia is defined as a condition with serious cognitive dysfunction, such as a convulsion and coma, requiring external help from other persons. This condition is still lethal and is reported to be the cause of death in 4-10% in children and adolescents with type 1 diabetes. The incidence of severe hypoglycemia in the pediatric population was previously reported as high as more than 50-100 patient-years; however, there was a decline in the frequency of severe hypoglycemia during the past decades, and relationship with glycemic control became weaker than previously reported. A lot of studies have shown the neurological sequelae with severe hypoglycemia as cognitive dysfunction and abnormalities in brain structure. This serious condition also provides negative psychosocial outcomes and undesirable compensatory behaviors. Various possible factors, such as younger age, recurrent hypoglycemia, nocturnal hypoglycemia, and impaired awareness of hypoglycemia, are possible risk factors for developing severe hypoglycemia. A low HbA_1c level is not a predictable value for severe hypoglycemia. Prevention of severe hypoglycemia remains one of the most critical issues in the management of pediatric patients with type 1 diabetes. Advanced technologies, such as continuous glucose monitoring (CGM), intermittently scanned CGM, and sensor-augmented pump therapy with low-glucose suspend system, potentially minimize the occurrence of severe hypoglycemia without worsening overall glycemic control. Hybrid closed-loop system must be the most promising tool for achieving optimal glycemic control with preventing the occurrence of severe hypoglycemia in pediatric patients with type 1 diabetes.

Glycemic-aware metrics and oversampling techniques for predicting blood glucose levels using machine learning

Techniques using machine learning for short term blood glucose level prediction in patients with Type 1 Diabetes are investigated. This problem is significant for the development of effective artificial pancreas technology so accurate alerts (e.g. hypoglycemia alarms) and other forecasts can be generated. It is shown that two factors must be considered when selecting the best machine learning technique for blood glucose level regression: (i) the regression model performance metrics being used to select the model, and (ii) the preprocessing techniques required to account for the imbalanced time spent by patients in different portions of the glycemic range. Using standard benchmark data, it is demonstrated that different regression model/preprocessing technique combinations exhibit different accuracies depending on the glycemic subrange under consideration. Therefore technique selection depends on the type of alert required. Specific findings are that a linear Support Vector Regression-based model, trained with normal as well as polynomial features, is best for blood glucose level forecasting in the normal and hyperglycemic ranges while a Multilayer Perceptron trained on oversampled data is ideal for predictions in the hypoglycemic range.

One Year Clinical Experience of the First Commercial Hybrid Closed-Loop System

OBJECTIVE

In September 2016, the U.S. Food and Drug Administration approved the Medtronic 670G "hybrid" closed-loop system. In Auto Mode, this system automatically controls basal insulin delivery based on continuous glucose monitoring data but requires users to enter carbohydrates and blood glucose for boluses. To track real-world experience with this first commercial closed-loop device, we prospectively followed pediatric and adult patients starting the 670G system.

RESEARCH DESIGN AND METHODS

This was a 1-year prospective observational study of patients with type 1 diabetes starting the 670G system between May 2017 and May 2018 in clinic.

RESULTS

Of the total of 84 patients who received 670G and consented, 5 never returned for follow-up, with 79 (aged 9-61 years) providing data at 1 week and 3, 6, 9, and/or 12 months after Auto Mode initiation. For the 86% (68 out of 79) with 1-week data, 99% (67 out of 68) successfully started. By 3 months, at least 28% (22 out of 79) had stopped using Auto Mode; at 6 months, 34% (27 out of 79); at 9 months, 35% (28 out of 79); and by 12 months, 33% (26 out of 79). The primary reason for continuing Auto Mode was desire for increased time in range. Reasons for discontinuation included sensor issues in 62% (16 out of 26), problems obtaining supplies in 12% (3 out of 26), hypoglycemia fear in 12% (3 out of 26), multiple daily injection preference in 8% (2 out of 26), and sports in 8% (2 out of 26). At all visits, there was a significant correlation between hemoglobin A_1c (HbA_1c) and Auto Mode utilization.

CONCLUSIONS

While Auto Mode utilization correlates with improved glycemic control, a focus on usability and human factors is necessary to ensure use of Auto Mode. Alarms and sensor calibration are a major patient concern, which future technology should alleviate.

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.

Six-Month Randomized, Multicenter Trial of Closed-Loop Control in Type 1 Diabetes

BACKGROUND

Closed-loop systems that automate insulin delivery may improve glycemic outcomes in patients with type 1 diabetes.

METHODS

In this 6-month randomized, multicenter trial, patients with type 1 diabetes were assigned in a 2:1 ratio to receive treatment with a closed-loop system (closed-loop group) or a sensor-augmented pump (control group). The primary outcome was the percentage of time that the blood glucose level was within the target range of 70 to 180 mg per deciliter (3.9 to 10.0 mmol per liter), as measured by continuous glucose monitoring.

RESULTS

A total of 168 patients underwent randomization; 112 were assigned to the closed-loop group, and 56 were assigned to the control group. The age range of the patients was 14 to 71 years, and the glycated hemoglobin level ranged from 5.4 to 10.6%. All 168 patients completed the trial. The mean (±SD) percentage of time that the glucose level was within the target range increased in the closed-loop group from 61±17% at baseline to 71±12% during the 6 months and remained unchanged at 59±14% in the control group (mean adjusted difference, 11 percentage points; 95% confidence interval [CI], 9 to 14; P<0.001). The results with regard to the main secondary outcomes (percentage of time that the glucose level was >180 mg per deciliter, mean glucose level, glycated hemoglobin level, and percentage of time that the glucose level was <70 mg per deciliter or <54 mg per deciliter [3.0 mmol per liter]) all met the prespecified hierarchical criterion for significance, favoring the closed-loop system. The mean difference (closed loop minus control) in the percentage of time that the blood glucose level was lower than 70 mg per deciliter was -0.88 percentage points (95% CI, -1.19 to -0.57; P<0.001). The mean adjusted difference in glycated hemoglobin level after 6 months was -0.33 percentage points (95% CI, -0.53 to -0.13; P = 0.001). In the closed-loop group, the median percentage of time that the system was in closed-loop mode was 90% over 6 months. No serious hypoglycemic events occurred in either group; one episode of diabetic ketoacidosis occurred in the closed-loop group.

CONCLUSIONS

In this 6-month trial involving patients with type 1 diabetes, the use of a closed-loop system was associated with a greater percentage of time spent in a target glycemic range than the use of a sensor-augmented insulin pump. (Funded by the National Institute of Diabetes and Digestive and Kidney Diseases; iDCL ClinicalTrials.gov number, NCT03563313.).

Advances in technology for management of type 1 diabetes

Technological advances have had a major effect on the management of type 1 diabetes. In addition to blood glucose meters, devices used by people with type 1 diabetes include insulin pumps, continuous glucose monitors, and, most recently, systems that combine both a pump and a monitor for algorithm-driven automation of insulin delivery. In the next 5 years, as many advances are expected in technology for the management of diabetes as there have been in the past 5 years, with improvements in continuous glucose monitoring and more available choices of systems that automate insulin delivery. Expansion of the use of technology will be needed beyond endocrinology practices to primary-care settings and broader populations of patients. Tools to support decision making will also need to be developed to help patients and health-care providers to use the output of these devices to optimise diabetes management.

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.