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Background We assessed whether a sustained period of intensive glucose control with hybrid closed-loop for 12 months following diagnosis of type 1 diabetes in children and adolescents can preserve C-peptide secretion compared to standard insulin therapy. Methods In an open-label, multicentre, randomised, parallel trial, youth aged 10–16.9 years were randomised within 21 days of type 1 diabetes diagnosis to hybrid closed-loop or standard insulin therapy (control). Primary end point was the difference in mixed-meal C-peptide area under the curve 12 months post diagnosis. Key secondary end points included time spent in target glucose range, glycated haemoglobin and time spent below target glucose range at 12 months. Analysis was by intention to treat. The Closed Loop from Onset in Type 1 Diabetes consortium secured external funding for participants to continue on beyond 12 months, but the funding by National Institute for Health and Care Research and the results reported here refer only to the 12 months follow-up. Results We randomised 97 participants (mean ± standard deviation age 12 ± 2 years), 51 to closed-loop and 46 to control therapy. There was no difference in C-peptide area under the curve at 12 months between groups [geometric mean (interquartile range) closed-loop (n = 46): 0.35 pmol/ml (0.16, 0.49) vs. control (n = 37): 0.46 pmol/ml (0.22, 0.69); mean adjusted difference –0.06 (95% confidence interval –0.14 to 0.03); p = 0.19]. The proportion of time in target range 3.9–10.0 mmol/l based on 14-day masked LibrePro (Abbott Diabetes Care, Maidenhead, UK) sensor glucose data at 12 months was 10 percentage points (95% confidence interval 2 to 17) higher in the closed-loop group (64 ± 14%) compared to control group (54 ± 23%). Arithmetic mean glycated haemoglobin A1c was lower in the closed-loop group by 4 mmol/mol (0.4%) [95% confidence interval 0 to 8 mmol/mol (0.0% to 0.7%)] at 12 months. The mean difference in time spent 10.0 mmol/l was 11 percentage points (95% CI 3 to 19 percentage points) lower in the CL group compared to the control group at 12 months. Glucose variability measured by standard deviation (SD) was similar between CL and control groups, while coefficient of variation of glucose was 4 percentage points higher in the CL group at 12 months (95% CI 1 to 8 percentage points). The primary end point was similar in a per-protocol analysis using data from randomised participants in the CL group with at least 60% CL use and those in the control group who did not start insulin pump therapy. Total daily insulin dose was similar between treatment groups, but there was a greater proportion of basal insulin (mean ± SD closed-loop 0.52 ± 0.31 U/kg/day, control 0.37 ± 0.26 U/kg/day) to bolus insulin (mean ± SD closed-loop 0.44 ± 0.22 U/kg/day, control 0.46 ± 0.23 U/kg/day) in the CL group at 12 months. Blood pressure, lipid profile and BMI percentile were similar between treatment groups. In the CL group, median CL use was 66% (IQR 44–80) over the 12-month period. In the control group, 10% of participants (n = 4) were using insulin pump therapy and 57% (n = 21) were using a flash or real-time continuous glucose sensor at 12 months post diagnosis. Three severe hypoglycaemic events occurred in the CL group (two participants), and one in the control group; one DKA occurred in the CL group and none in the control group. The number of other AEs (CL group 34, control group 37) and SAEs (CL group 2, control group 4) was similar between groups. Responses to the Pediatric Quality of Life Inventory (PedsQL), hypoglycaemia fear survey (HFS), problem areas in diabetes (PAID) and Strengths and Difficulties Questionnaires (SDQs) were similar between treatment groups in both children and parents at 12 months. Scores for the INSPIRE (INsulin Dosing Systems: Perceptions, Ideas, Reflections and Expectations) questionnaire were high in children, teenagers and parents, suggesting positive expectancies regarding automated insulin delivery in this population. In-depth interviews of 18 youths and 21 parents with ≥ 12 months’ experience of using CL technology were undertaken. Interviews explored the impact of using CL systems on diabetes management practices and everyday family life. As reported by Lawton et al. Participants reported very few disruptions to their lives when using a closed-loop system. Reports of family conflict were minimal as the closed-loop enabled dietary flexibility and glucose levels to be checked effortlessly. Adolescents described doing ‘normal’ activities without worrying about high or low glucose, and parents reported allowing them to do so unsupervised because the closed-loop would regulate their glucose and keep them safe. Some adolescents expressed concerns about the visibility of components and, to avoid stigma, described curtailing activities such as swimming. Participants described how the closed-loop enabled adolescents to be in control of, or create distance from, their diabetes. Lawton J, Kimbell B, Rankin D, Ashcroft NL, Varghese L, Allen JM, et al.; CLOuD Consortium. Health professionals’ views about who would benefit from using a closed-loop system: a qualitative study. Diabet Med: J Br Diabet Assoc 2020;37(6):1030–7. Interviews of multidisciplinary healthcare professionals (n = 22) providing support to trial participants explored the benefits, issues and challenges arising from introducing and using CL systems to support diabetes self-management. Lawton et al. reported that interviewees described how, compared with other insulin regimens, teaching and supporting individuals to use a closed-loop system could be initially more time-consuming. However, they also noted that after an initial adjustment period, users had less need for initiating contact with the clinical team compared with people using pumps or multiple daily injections. Interviewees highlighted how a lessened need for ad hoc clinical input could result in new challenges; specifically, they had fewer opportunities to reinforce users’ diabetes knowledge and skills and detect potential psychosocial problems. Lawton et al. (2020) We explored health professionals’ views about who would benefit from using a CL system. Interviewees described holding strong assumptions about the types of people who would use the technology effectively prior to the trial. Interviewees described changing their views as a result of observing individuals engaging with the CL system in ways they had not anticipated. This included educated, technologically competent individuals who over-interacted with the system in ways which could compromise glycaemic control. Other individuals, who health professionals assumed would struggle to understand and use the technology, were reported to have benefited from it because they stood back and allowed the system to operate without interference. Interviewees concluded that individual, family and psychological attributes cannot be used as pre-selection criteria and ideally all individuals should be given the chance to try the technology. Conclusions The CLOuD study demonstrates that CL glucose control over a period of 12 months does not slow the decline in C-peptide secretion in children and adolescents with new-onset type 1 diabetes. Mean time in range was 10 percentage points higher and mean HbA1c was 0.4% (4 mmol/mol) lower in the CL group compared with the control group at 12 months, but these end points did not reach the pre-specified significance thresholds and it is possible that a greater improvement in glucose control with attainment of normoglycaemia could prevent the decline in C-peptide secretion. Further work may be needed to definitively rule out a role of glycaemic burden in the decline of C-peptide secretion. Total daily exogenous insulin requirements, a surrogate marker of residual insulin secretion, were similar between groups at all time points after diagnosis. This comparison may be hampered by any between-group differences in glycaemic control. It is likely that factors other than glycaemic control, such as autoimmune response, determine the rate of C-peptide decline following diagnosis of type 1 diabetes. It is possible that other factors act in concert with dysglycaemia on C-peptide secretion. The present study demonstrates that hybrid CL is effective in new-onset type 1 diabetes in youth and can safely accommodate the variability in exogenous insulin requirements which occur with beta-cell recovery post diagnosis. Glycaemic control was sustained over 12 months in the CL group, whereas glycaemic control started to deteriorate in the control group at 6 to 9 months after diagnosis. At 12 months post diagnosis, only 56% of youth in the control group (78% in the CL group) were able to achieve a HbA1c of

Background There are over 2000 pregnancies annually in women with type 1 diabetes in the UK. Despite recent improvements in diabetes technology, most women cannot achieve and maintain the recommended pregnancy glucose targets. Thus, one in two babies experience complications requiring neonatal care unit admission. Recent studies demonstrate that hybrid closed-loop therapy, in which algorithms adjust insulin delivery according to continuous glucose measurements, is effective for managing type 1 diabetes outside of pregnancy, but efficacy during pregnancy is unclear. Objective To examine the clinical efficacy of hybrid closed-loop compared to standard insulin therapy in pregnant women with type 1 diabetes. Design A multicentre, parallel-group, open-label, randomised, controlled trial in pregnant women with type 1 diabetes. Setting Nine antenatal diabetes clinics in England, Scotland and Northern Ireland. Participants Pregnant women with type 1 diabetes and above-target glucose levels, defined as glycated haemoglobin A1c of ≥ 48 mmol/mol (6.5%) in early pregnancy. Interventions A hybrid closed-loop system compared to standard insulin delivery (via insulin pump or multiple daily injections) with continuous glucose monitoring. Outcome measures The primary outcome is the difference between the intervention and control groups in percentage time spent in the pregnancy glucose target range (3.5–7.8 mmol/l) as measured by continuous glucose monitoring from 16 weeks’ gestation until delivery. Secondary outcomes include overnight time in range, time above range (> 7.8 mmol/l), glycated haemoglobin A1c, safety outcomes (diabetic ketoacidosis, severe hypoglycaemia, adverse device events), psychosocial functioning obstetric and neonatal outcomes. Results The percentage of time that maternal glucose levels were within target range was higher with closed-loop than standard insulin therapy: 68.2 ± 10.5 in closed-loop and 55.6 ± 12.5 in the control group (mean‑adjusted difference 10.5 percentage points, 95% confidence interval 7.0 to 14.0; p < 0.001). Results were consistent in secondary outcomes, with less time above range (−10.2%, 95% confidence interval −13.8 to −6.6%; p < 0.001), higher overnight time in range (12.3%, 95% confidence interval 8.3 to 16.2%; p < 0.001) and lower glycated haemoglobin A1c (−0.31%, 95% confidence interval −0.50 to −0.12%; p < 0.002) all favouring closed-loop. The treatment effect was apparent from early pregnancy and consistent across clinical sites, maternal glycated haemoglobin A1c categories and previous insulin regimen. Maternal glucose improvements were achieved with 3.7 kg less gestational weight gain and without additional hypoglycaemia or total daily insulin dose. There were no unanticipated safety problems (six vs. five severe hypoglycaemia cases, one diabetic ketoacidosis per group) and seven device-related adverse events associated with closed-loop. There were no between-group differences in patient-reported outcomes. There was one shoulder dystocia in the closed-loop group and four serious birth injuries, including one neonatal death in the standard care group. Limitations Our results cannot be extrapolated to closed-loop systems with higher glucose targets, and our sample size did not provide definitive data on maternal and neonatal outcomes. Conclusions Hybrid closed-loop therapy significantly improved maternal glycaemia during type 1 diabetes pregnancy. Our results support National Institute for Health and Care Excellence guideline recommendations that hybrid closed-loop therapy should be offered to all pregnant women with type 1 diabetes. Future work Future trials should examine the effectiveness of hybrid closed-loop started before pregnancy, or as soon as possible after pregnancy confirmation. Trial registration This trial is registered as ISRCTN56898625. Funding This award was funded by the National Institute of Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 16/35/01) and is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 7. See the NIHR Funding and Awards website for further award information. Dexcom supplied the continuous glucose monitoring systems used by AiDAPT intervention- and control-arm participants at reduced cost. Plain language summary Pregnancy in women with type 1 diabetes is associated with complications for both mother and baby. Recent improvements in diabetes technology have not been sufficient to help most women achieve and maintain recommended pregnancy glucose targets. Hybrid closed-loop technology (an insulin pump, smartphone app and continuous glucose monitor), which automatically adjusts insulin doses according to glucose measurements, is effective in managing type 1 diabetes outside of pregnancy, but its effectiveness during pregnancy was unclear. To examine the effectiveness of hybrid closed-loop therapy compared to standard insulin therapy in pregnant women with type 1 diabetes, we conducted a randomised controlled trial in nine maternity clinics in England, Scotland and Northern Ireland. We enrolled pregnant women with type 1 diabetes and above-target glucose levels, defined as glycated haemoglobin A1c of ≥ 48 mmol/mol, in early pregnancy. Women were randomly assigned to either a hybrid closed-loop system or standard insulin delivery (insulin pump or multiple daily injections) with continuous glucose monitoring. This study found that hybrid closed-loop therapy improved maternal glucose levels during type 1 diabetes pregnancy, resulting in higher time spent in the target glucose range and less time above range. Mothers in the closed-loop group had less weight gain during pregnancy, without additional hypoglycaemia or insulin dose. The benefits of closed-loop were consistent across maternity clinics, maternal glucose levels and previous insulin pump or injection therapy. There were no unanticipated safety problems associated with using closed-loop. However, the study was too small to provide definite information on pregnancy outcomes, and the results cannot be inferred to other closed-loop systems with higher glucose targets. Future trials should examine the effectiveness of closed-loop started before pregnancy or as soon as possible after pregnancy confirmation. Our results support National Institute for Health and Care Excellence guideline recommendations that hybrid closed-loop therapy should be offered to all pregnant women with type 1 diabetes. Scientific summary Background There are over 2000 pregnancies annually in women with type 1 diabetes. These pregnancies are complicated by high and increasing rates of preterm births, large for gestational age birthweight babies and neonatal care unit admissions. Obstetric and neonatal complications are lowest in mothers who achieve target glucose levels, which requires unrelenting attention to diabetes self-management and insulin dose adjustment throughout pregnancy. Despite improvements in diabetes technology, including continuous glucose monitoring (CGM) and insulin pumps, most pregnant women with type 1 diabetes cannot achieve or maintain the pregnancy glucose targets. National audit data confirm that only 15% of women enter pregnancy with the recommended glycated haemoglobin A1c (HbA1c) target of 10 mmol/l). The primary outcome was the percentage of time spent with CGM glucose levels between 3.5 and 7.8 mmol/l between 16 weeks’ gestation and delivery. Safety outcomes included the number and severity of diabetic ketoacidosis (DKA), severe hypoglycaemia (SH) and adverse device events. Patient-reported outcomes were reported at around 34–36 weeks’ gestation using the following validated questionnaires: Insulin Delivery Systems: Perspectives, Ideas, Reflections and Expectations (INSPIRE); EuroQol-5 Dimensions health-related quality-of-life questionnaire (EQ-5D), Diabetes Distress Scale (DDS), hypoglycaemia fear survey II (HFS – worry scale only) and Pittsburgh Sleep Quality Index (PSQI). Maternal and neonatal outcomes were documented at hospital discharge following delivery. Protocol amendments implemented during the COVID-19 pandemic allowed participants the option to continue using CGM with standard or closed-loop insulin delivery as per their initial randomisation for up to 6 months post partum. Outcomes for those who participated in the observational post-partum extension study will be reported separately. Details of the clinical study protocol are published. Primary outcome analysis was by intention-to-treat using a linear mixed-effects regression model adjusted for baseline CGM TIR, insulin delivery and clinical site. Missing primary end-point data were handled using multiple imputation (Rubins and direct likelihood methods) with all randomised participants included. For secondary outcomes, analyses were similar to the primary analysis, without imputation. False discovery rate (FDR)-adjusted p-values were calculated for selected secondary outcomes (overall, overnight, and by-trimester sensor glucose metrics, HbA1c, insulin doses, subgroup analyses, questionnaires) using Benjamini–Hochberg methods. For attainment of sensor glucose targets, a mixed-effects logistic regression model was fitted adjusting for baseline TIR, insulin delivery and clinical site as a random effect. All p-values are two-tailed. Analyses were performed using SAS® 9.4 (SAS Institute Inc., Cary, NC, USA; SAS and all other SAS Institute Inc. product or service names are registered trademarks or trademarks of SAS Institute Inc. in the USA and other countries.® indicates USA registration). Results Participants Between September 2019 and May 2022, 334 participants were assessed for eligibility, with 126 enrolled and 124 randomised: 61 to the closed-loop intervention group and 63 to the standard care control group. Participants were from nine NHS maternity clinics and spanned a range of maternal age, body weight and glycaemic categories. Almost all (98%) were using CGM and approximately half were using insulin pump therapy at enrolment. Participants in the closed-loop group had more previous pregnancies, while those in the standard care group reported more previous DKA events. Two participants switched from their randomised allocation group: one intervention participant for whom lockdown restrictions prevented closed-loop training and one standard care participant who procured closed-loop (CamAPS FX) outside of the trial. Seven participants in each group discontinued their allocated treatment. Despite the impact of the COVID-19 pandemic, the proportion of completed study visits was high (approximately 95%). Participants in the standard care group had more additional clinic visits (1.5 vs. 1.1) and more unscheduled contacts (9.6 vs. 6.1), mostly for pregnancy and diabetes-related reasons. The frequency of sensor use was consistently high: median 97% across both treatment groups. The frequency of closed-loop use was high (median 96%) and remained > 95% throughout pregnancy. Primary efficacy end point The mean (± standard deviation) percentage of time that maternal glucose levels were within the pregnancy target range increased from 47.8 ± 16.4% to 68.2 ± 10.5% in the closed-loop group and from 44.5 ± 14.4% to 55.6 ± 12.5% in the control group [mean‑adjusted difference 10.5 percentage points, 95% confidence interval (CI) 7.0 to 14.0 percentage points; p < 0.001]. Adjustment for potential confounding variables, including previous pregnancies and DKA episodes, did not change the treatment difference. There were no variations in the treatment effect between trial sites and no differential effects across maternal age, HbA1c or insulin delivery categories. The large treatment difference was consistent between intention-to-treat and per-protocol analyses and using multiple imputation methods. Secondary glycaemic outcomes Participants randomised to closed-loop spent less time with glucose levels above target range (mean difference −10.2%, 95% CI −13.8% to −6.6%; p < 0.001). This was accompanied by decreased hyperglycaemia across milder (> 6.7 mmol/l) and more pronounced (> 10.0 mmol/l) categories, as well as lower mean glucose and lower HbA1c (mean difference −0.31%, 95% CI −0.50% to −0.12%; p < 0.002). These changes are notable since participants in both groups spent approximately 70% of time in the near-optimal glucose range of 3.5–10.0 mmol/l at enrolment. Furthermore, in those who started closed-loop therapy during the first trimester, a 5% higher TIR was observed by the end of 12 weeks’ gestation. The effects of the intervention during the overnight period (23.00–07.00) closely followed the 24-hour results (12.3% higher TIR, 95% CI 8.3% to 16.2%; p < 0.001). This was accompanied by less nocturnal hypoglycaemia and fewer nocturnal hypoglycaemic events. Attainment of the sensor glucose target of > 70% time (16 hours 48 minutes) within the pregnancy-specific range was achieved by 28 (47%) closed-loop and 7 (11%) standard care participants. Attainment of the sensor glucose target of 95%) throughout pregnancy, and without apparent safety problems, including among those new to insulin pump therapy. Indeed, participants who continued standard care had more clinic visits and more unscheduled contacts, suggesting that beyond initial training, closed-loop use did not require additional healthcare professional input. Recent trials have demonstrated the benefits of CamAPS FX to those with newly diagnosed type 1 diabetes and young children, and these results further extend the evidence for closed-loop therapy to pregnant women. During pregnancy, women in the closed-loop group increased the percentage of time with near-target glucose levels (3.5–10.0 mmol/l) from 71 to 87%. This is, to the best of our knowledge, the tightest glycaemic control yet achieved through use of closed-loop therapy. Alongside women’s motivation to minimise pregnancy complications, closed-loop use facilitated attainment of 70% time in pregnancy-specific target range throughout gestation. This suggests that tighter glycaemic control could also be feasible outside of pregnancy, when clinically warranted. Given the rapid increases in TIR observed within 1 week of therapy initiation in this trial, and within 1 day in a recent trial, we speculate that further benefits may be obtained from starting closed-loop before pregnancy, or as soon as possible, after pregnancy is confirmed. The current trial participants gained an additional 10% TIR above and beyond the 10% increment achieved by CGM and standard insulin therapy across pregnancy. Previous studies demonstrated that every 5% increased TIR is associated with improved obstetric and neonatal outcomes. Our trial was not powered for pregnancy outcomes, but we infer that this additional 10% time in the pregnancy target range would be expected to have additional health benefits for mothers and their babies. The strengths of our trial include its parallel-group, randomised controlled design, generalisability of our patient population, including those naive to insulin pump therapy and a large proportion who initiated therapy during the first trimester, and a flexible pragmatic trial protocol that facilitated virtual or in-person visits. There was no evidence of increased clinical contacts, frequently observed in investigational device trials. This trial had certain limitations. We did not undertake a health economic evaluation and the current sample size did not provide definitive data on maternal and neonatal health outcomes. Furthermore, our data are applicable only to the CamAPS FX closed-loop system and cannot be extrapolated to systems with higher glucose targets. Closed-loop therapy was effective in type 1 diabetes pregnancy, safely accommodating the marked gestational changes in insulin doses across a range of maternal body weight and glycaemic categories. It gave additional clinical advantage above and beyond that which can be achieved by CGM and standard insulin therapy, supporting NICE guideline recommendations that hybrid closed-loop therapy should be offered to all pregnant women with type 1 diabetes. Trial registration This trial is registered as ISRCTN56898625. Funding This award was funded by the National Institute of Health and Care Research (NIHR) Efficacy and Mechanism Evaluation (EME) programme (NIHR award ref: 16/35/01) and is published in full in Efficacy and Mechanism Evaluation; Vol. 11, No. 7. See the NIHR Funding and Awards website for further award information. Dexcom supplied the continuous glucose monitoring systems used by AiDAPT intervention- and control-arm participants at reduced cost.

Automated insulin delivery systems, also known as closed-loop o r ‘artificial pancreas’ systems, are transforming the management of type 1 diabetes. These systems consist of an algorithm which responds to real-time glucose sensor levels by automatically modulating insulin delivery through an insulin pump. We review the rapidly changing landscape of automated insulin-delivery systems over recent decades, from initial prototypes to the different hybrid closed-loop systems commercially available today. We discuss the growing body of clinical trials and real-world evidence demonst rating their glycaemic and psychosocial benefits. We also address future directions in auto mated insulin delivery such as dual-hormone systems and adjunct therapy as well as the chal lenges around ensuring equitable access to closed-loop technology.

Introduction Medical devices, including high-risk medical devices, have greatly contributed to recent improvements in the management of diabetes. However, the clinical evidence that is submitted for regulatory approval is not transparent, and thus a comprehensive summary of the evidence for high-risk devices approved for managing diabetes in Europe is lacking. In the framework of the Coordinating Research and Evidence for Medical Devices group, we will, therefore, perform a systematic review and meta-analysis, which will evaluate the efficacy, safety and usability of high-risk medical devices for the management of diabetes.Method and analysis This study has been reported according to the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols. We will search Embase (Elsevier), Medline All (Ovid), Cochrane Library (Wiley), Science Citation Index Expanded and Emerging Sources Citation Index (Web of Science) to identify interventional and observational studies that evaluate the efficacy and/or safety and/or usability of high-risk medical devices for the management of diabetes. No language or publication dates’ limits will be applied. Animal studies will be excluded. In accordance with the Medical Device Regulation in European Union, high-risk medical devices are those in classes IIb and III. The following medical devices for diabetes management are considered as having a high risk: implantable continuous glucose monitoring systems, implantable pumps and automated insulin delivery devices. Selection of studies, data extraction and quality of evidence assessment will be performed independently by two researchers. Sensitivity analysis will be performed to identify and explain potential heterogeneity.Ethics and dissemination No ethical approval is needed for this systematic review, as it is based in already published data. Our findings will be published in a peer-reviewed journal.PROSPERO registration number CRD42022366871.

Abstract Background Pregnant women with type 1 diabetes strive for tight glucose targets (3.5-7.8 mmol/L) to minimise the risks of obstetric and neonatal complications. Despite using diabetes technologies including continuous glucose monitoring (CGM), insulin pumps and contemporary insulin analogues, most women struggle to achieve and maintain the recommended pregnancy glucose targets. This study aims to evaluate whether the use of automated closed-loop insulin delivery improves antenatal glucose levels in pregnant women with type 1 diabetes. Methods/design A multicentre, open label, randomized, controlled trial of pregnant women with type 1 diabetes and a HbA1c of ≥48 mmol/mol (6.5%) at pregnancy confirmation and ≤ 86 mmol/mol (10%) at randomization. Participants who provide written informed consent before 13 weeks 6 days gestation will be entered into a run-in phase to collect 96 h (24 h overnight) of CGM glucose values. Eligible participants will be randomized on a 1:1 basis to CGM (Dexcom G6) with usual insulin delivery (control) or closed-loop (intervention). The closed-loop system includes a model predictive control algorithm (CamAPS FX application), hosted on an android smartphone that communicates wirelessly with the insulin pump (Dana Diabecare RS) and CGM transmitter. Research visits and device training will be provided virtually or face-to-face in conjunction with 4-weekly antenatal clinic visits where possible. Randomization will stratify for clinic site. One hundred twenty-four participants will be recruited. This takes into account 10% attrition and 10% who experience miscarriage or pregnancy loss. Analyses will be performed according to intention to treat. The primary analysis will evaluate the change in the time spent in the target glucose range (3.5-7.8 mmol/l) between the intervention and control group from 16 weeks gestation until delivery. Secondary outcomes include overnight time in target, time above target (> 7.8 mmol/l), standard CGM metrics, HbA1c and psychosocial functioning and health economic measures. Safety outcomes include the number and severity of ketoacidosis, severe hypoglycaemia and adverse device events. Discussion This will be the largest randomized controlled trial to evaluate the impact of closed-loop insulin delivery during type 1 diabetes pregnancy. Trial registration ISRCTN 56898625 Registration Date: 10 April, 2018.

Summary: Background: Closed-loop insulin delivery systems have the potential to address suboptimal glucose control in children and adolescents with type 1 diabetes. We compared safety and efficacy of the Cambridge hybrid closed-loop algorithm with usual care over 6 months in this population. Methods: In a multicentre, multinational, parallel randomised controlled trial, participants aged 6–18 years using insulin pump therapy were recruited at seven UK and five US paediatric diabetes centres. Key inclusion criteria were diagnosis of type 1 diabetes for at least 12 months, insulin pump therapy for at least 3 months, and screening HbA1c levels between 53 and 86 mmol/mol (7·0–10·0%). Using block randomisation and central randomisation software, we randomly assigned participants to either closed-loop insulin delivery (closed-loop group) or to usual care with insulin pump therapy (control group) for 6 months. Randomisation was stratified at each centre by local baseline HbA1c. The Cambridge closed-loop algorithm running on a smartphone was used with either (1) a modified Medtronic 640G pump, Medtronic Guardian 3 sensor, and Medtronic prototype phone enclosure (FlorenceM configuration), or (2) a Sooil Dana RS pump and Dexcom G6 sensor (CamAPS FX configuration). The primary endpoint was change in HbA1c at 6 months combining data from both configurations. The primary analysis was done in all randomised patients (intention to treat). Trial registration ClinicalTrials.gov, NCT02925299. Findings: Of 147 people initially screened, 133 participants (mean age 13·0 years [SD 2·8]; 57% female, 43% male) were randomly assigned to either the closed-loop group (n=65) or the control group (n=68). Mean baseline HbA1c was 8·2% (SD 0·7) in the closed-loop group and 8·3% (0·7) in the control group. At 6 months, HbA1c was lower in the closed-loop group than in the control group (between-group difference −3·5 mmol/mol (95% CI −6·5 to −0·5 [–0·32 percentage points, −0·59 to −0·04]; p=0·023). Closed-loop usage was low with FlorenceM due to failing phone enclosures (median 40% [IQR 26–53]), but consistently high with CamAPS FX (93% [88–96]), impacting efficacy. A total of 155 adverse events occurred after randomisation (67 in the closed-loop group, 88 in the control group), including seven severe hypoglycaemia events (four in the closed-loop group, three in the control group), two diabetic ketoacidosis events (both in the closed-loop group), and two non-treatment-related serious adverse events. There were 23 reportable hyperglycaemia events (11 in the closed-loop group, 12 in the control group), which did not meet criteria for diabetic ketoacidosis. Interpretation: The Cambridge hybrid closed-loop algorithm had an acceptable safety profile, and improved glycaemic control in children and adolescents with type 1 diabetes. To ensure optimal efficacy of the closed-loop system, usage needs to be consistently high, as demonstrated with CamAPS FX. Funding: National Institute of Diabetes and Digestive and Kidney Diseases.

Background: Hyperglycaemia and hypoglycaemia are common in preterm infants and are associated with increased mortality and morbidity. Continuous glucose monitoring is widely used to target glucose control in adults and children, but not in neonates. Objective: To evaluate the role of continuous glucose monitoring in the preterm infant. Design: The REAl-time Continuous glucose moniToring in neonatal intensive care project combined (1) a feasibility study, (2) a multicentre randomised controlled trial and (3) a pilot of ‘closed-loop’ continuous glucose monitoring. The feasibility study comprised a single-centre study (n = 20). Eligibility criteria included a birthweight ≤ 1200 g and aged ≤ 48 hours. Continuous glucose monitoring was initiated to support glucose control. The efficacy and safety outcomes guided the design of the randomised controlled trial. The randomised controlled trial comprised a European multicentre trial (n = 182). Eligibility criteria included birthweight ≤ 1200 g and aged ≤ 24 hours. Exclusion criteria included any lethal congenital abnormality. Continuous glucose monitoring was initiated to support glucose control within 24 hours of birth. In the intervention group, the continuous glucose monitoring sensor provided real-time data on glucose levels, which guided clinical management. In control infants, the continuous glucose monitoring data were masked, and glucose level was managed in accordance with standard clinical practice and based on the blood glucose levels. The primary outcome measure was the percentage of time during which the sensor glucose level was within the target range of 2.6–10 mmol/l. Secondary outcome measures included mean sensor glucose level, the percentage of time during which the sensor glucose level was within the target range of 4–8 mmol/l, the percentage of time during which the sensor glucose level was in the hyperglycaemic range (i.e. > 15 mmol/l) and sensor glucose level variability. Safety outcomes included hypoglycaemia exposure. Acceptability assessment and health economic analyses were carried out and further exploratory health outcomes were explored. The mean percentage of time in glucose target range of 2.6–10 mmol/l was 9% higher in infants in the continuous glucose monitoring group (95% confidence interval 3% to 14%; p = 0.002), and the mean time in the target range of 4–8 mmol/l was 12% higher in this group (95% confidence interval 4% to 19%; p = 0.004). There was no difference in the number of episodes of hypoglycaemia. Exploratory outcomes showed a reduced risk of necrotising enterocolitis in the intervention arm (odds ratio 0.33, 95% confidence interval 0.13 to 0.78; p = 0.01). Health economic analyses demonstrated that continuous glucose monitoring was cost-effective on the basis of the cost per additional case of adequate glucose control between 2.6 and 10 mmol/l. The ‘closed-loop’ study was a single-center pilot study, with eligibility criteria including a birthweight of ≤ 1200 g and aged ≤ 48 hours. Infants underwent continuous glucose monitoring for the first week of life (n = 21), with those in the intervention group receiving closed-loop insulin delivery between 48 and 72 hours of age. The primary outcome of percentage of time in the target range (i.e. sensor glucose 4–8 mmol/l) increased from a median of 26% (interquartile range 6–64%) to 91% (interquartile range 78–99%) during closed-loop insulin delivery (p

BackgroundType 1 diabetes in young children is a heavy parental burden. As part of pilot phase of the KIDSAP01 study, we conducted a baseline assessment in parents to study the association between hypoglycemia fear, parental well-being and child behavior.MethodsAll parents were invited to fill in baseline questionnaires: hypoglycemia fear survey (HFS), WHO-5, Epworth Sleepiness Scale and Strength and Difficulties Questionnaire (SDQ).Results24 children (median age: 5-year, range 1-7 years, 63% male, mean diabetes duration: 3 ± 1.7 years) participated. 23/24 parents filled out the questionnaires. We found a higher score for the hypoglycemia fear behavior 33.9 ± 5.6 compared to hypoglycemia worry 34.6 ± 12.2. Median WHO-5 score was 16 (8 - 22) with poor well-being in two parents. Median daytime sleepiness score was high in five parents (>10). For six children a high total behavioral difficulty score (>16) was reported. Pro social behavior score was lower than normal in six children (

Recent advances in diabetes technology have led to the development of closed-loop insulin delivery systems for the management of type 1 diabetes. Several such systems are now commercially available for children and young people. While all available systems have been shown to improve glycaemic control and quality of life in this population, qualitative data also highlights the challenges in using closed-loop systems, which vary among different pediatric age-groups. Very young children require systems that are able to cope with low insulin doses and significant glycaemic variability due to their high insulin sensitivity and unpredictable eating and exercise patterns. Adolescents' compliance is often related to size and number of devices, usability of the systems, need for calibrations, and their ability to interact with the system. Given the speed of innovations, understanding the capabilities and key similarities and differences of current systems can be challenging for healthcare professionals, caregivers and young people with type 1 diabetes alike. The aim of this review is to summarize the key evidence on currently available closed-loop systems for children and young people with type 1 diabetes, as well as commenting on user experience, where real-world data are available. We present findings on a system-basis, as well as identifying specific challenges in different pediatric age-groups and commenting on how current systems might address these. Finally, we identify areas for future research with regards to closed-loop technology tailored for pediatric use and how these might inform reimbursement and alleviate disease burden.

Introduction Diabetes management in very young children remains challenging. Glycaemic targets are achieved at the expense of high parental diabetes management burden and frequent hypoglycaemia, impacting quality of life for the whole family. Our objective is to assess whether automated insulin delivery can improve glycaemic control and alleviate the burden of diabetes management in this particular age group.Methods and analysis The study adopts an open-label, multinational, multicentre, randomised, crossover design and aims to randomise 72 children aged 1–7 years with type 1 diabetes on insulin pump therapy. Following screening, participants will receive training on study insulin pump and study continuous glucose monitoring devices. Participants will be randomised to 16-week use of the hybrid closed-loop system (intervention period) or to 16-week use of sensor-augmented pump therapy (control period) with 1–4 weeks washout period before crossing over to the other arm. The order of the two study periods will be random. The primary endpoint is the between-group difference in time spent in the target glucose range from 3.9 to 10.0 mmol/L based on sensor glucose readings during the 16-week study periods. Analyses will be conducted on an intention-to-treat basis. Key secondary endpoints are between group differences in time spent above and below target glucose range, glycated haemoglobin and average sensor glucose. Participants’ and caregivers’ experiences will be evaluated using questionnaires and qualitative interviews, and sleep quality will be assessed. A health economic analysis will be performed.Ethics and dissemination Ethics approval has been obtained from Cambridge East Research Ethics Committee (UK), Ethics Committees of the University of Innsbruck, the University of Vienna and the University of Graz (Austria), Ethics Committee of the Medical Faculty of the University of Leipzig (Germany) and Comité National d’Ethique de Recherche (Luxembourg). The results will be disseminated by peer-reviewed publications and conference presentations.Trial registration number NCT03784027.

IntroductionManagement of newly diagnosed type 1 diabetes (T1D) in children and adolescents is challenging for patients, families and healthcare professionals. The objective of this study is to determine whether continued intensive metabolic control using hybrid closed-loop (CL) insulin delivery following diagnosis of T1D can preserve C-peptide secretion, a marker of residual beta-cell function, compared with standard multiple daily injections (MDI) therapy.Methods and analysisThe study adopts an open-label, multicentre, randomised, parallel design, and aims to randomise 96 participants aged 10–16.9 years, recruited within 21 days of diagnosis with T1D. Following a baseline mixed meal tolerance test (MMTT), participants will be randomised to receive 24 months treatment with conventional MDI therapy or with CL insulin delivery. A further 24-month optional extension phase will be offered to all participants to continue with the allocated treatment. The primary outcome is the between group difference in area under the stimulated C-peptide curve (AUC) of the MMTT at 12 months post diagnosis. Analyses will be conducted on an intention-to-treat basis. Key secondary outcomes are between group differences in time spent in target glucose range (3.9–10 mmol/L), glycated haemoglobin (HbA1c) and time spent in hypoglycaemia (

Abstract There is considerable physiological and clinical evidence of harm and increased risk of death associated with dysglycemia in critical care. However, glycemic control (GC) currently leads to increased hypoglycemia, independently associated with a greater risk of death. Indeed, recent evidence suggests GC is difficult to safely and effectively achieve for all patients. In this review, leading experts in the field discuss this evidence and relevant data in diabetology, including the artificial pancreas, and suggest how safe, effective GC can be achieved in critically ill patients in ways seeking to mimic normal islet cell function. The review is structured around the specific clinical hurdles of: understanding the patient’s metabolic state; designing GC to fit clinical practice, safety, efficacy, and workload; and the need for standardized metrics. These aspects are addressed by reviewing relevant recent advances in science and technology. Finally, we provide a set of concise recommendations to advance the safety, quality, consistency, and clinical uptake of GC in critical care. This review thus presents a roadmap toward better, more personalized metabolic care and improved patient outcomes.

BackgroundStudies have shown that overnight closed-loop insulin delivery can improve glucose control and reduce the risk of hypoglycemia and hence may improve metabolic outcomes and reduce burden for children with type 1 diabetes and their families. However, research so far has not reported insulin levels while comparing closed-loop to open-loop insulin delivery in children. Therefore, in this study we obtained glucose levels as well as plasma insulin levels in children with type 1 diabetes to evaluate the efficacy of a model-based closed-loop algorithm compared to an open-loop administration.MethodsFifteen children with type 1 diabetes, 6-12 years, participated in this open-label single center study. We used a randomized cross over design in which we compared overnight closed-loop insulin delivery with sensor augmented pump therapy for two nights in both the hospital and at home (i.e., 1 night in-patient stay and at home per treatment condition). Only during the in-patient stay, hourly plasma insulin and blood glucose levels were assessed and are reported in this paper.ResultsResults of paired sample t-tests revealed that although plasma insulin levels were significantly lower during the closed-loop than in the open-loop (Mean difference 36.51 pmol/l; t(13) = 2.13, p = .03, effect size d = 0.57), blood glucose levels did not vary between conditions (mean difference 0.76 mmol/l; t(13) = 1.24, p = .12, d = 0.37). The administered dose of insulin was significantly lower during the closed-loop compared with the open-loop (mean difference 0.10 UI; t(12) = 2.45, p = .02, d = 0.68).ConclusionsLower insulin doses were delivered in the closed-loop, resulting in lower plasma insulin levels, whereby glucose levels were not affected negatively. This suggests that the closed-loop administration is better targeted and hence could be more effective.

Apolipoprotein kinetics are customarily determined by modeling time curves of specific radioactivity or isotopic enrichment in plasma after intravenous infusion of radiolabeled lipoproteins or stable isotope-enriched amino acids. However, this provides no information on the fractional rate of transfer of the apolipoprotein from plasma to interstitial fluid (kp-if) or its mean residence time in interstitial fluid (MRTif). To determine these parameters for a pharmacologic dose of exogenous apolipoprotein A-I (apoA-I) given intravenously as apoA-I/lecithin discs, we measured apoA-I in plasma and prenodal leg lymph in five healthy men before, during, and after a 4 h infusion at 10 mg/kg/h. ApoA-I concentrations in plasma and lymph were modeled by linear compartmental models (SAAM II version 1.1), using lymph albumin to adjust for the effects of variations in lymph flow rate. kp-if averaged 0.75%/h (range, 0.33–1.32), and MRTif averaged 29.1 h (14.1–40.0). Neither parameter was correlated with the distribution volume (57–105 ml/kg) or the fractional elimination rate (1.44–2.91%/h) of apoA-I, determined by modeling plasma apoA-I concentration alone. Although used here to study the mass kinetics of apoA-I, if combined with infusion of a tracer, analysis of lymph could also expand the modeling of endogenous apolipoprotein kinetics.