Safety and efficacy of 24-h closed-loop insulin delivery in well-controlled pregnant women with type 1 diabetes: a randomized crossover case series

Use of Advanced Hybrid Closed-Loop System during Pregnancy: Strengths and Limitations of Achieving a Tight Glycemic Control

Background: Pregnant women with type 1 diabetes mellitus (T1DM) face an elevated risk of complications for both themselves and their newborns. Experts recommend strict glycemic control. The advanced hybrid closed-loop (AHCL) system, though not officially approved for pregnant T1DM patients, is promising for optimal glycemic control. Methods: We collected CGM metrics, HbA1c levels, insulin pump settings, and doses from a 33-year-old pregnant woman with 23-year history of T1DM from the 6th week of gestation to birth. She was initially on continuous insulin pump therapy with CGM and switched to the AHCL system (MiniMedTM 780G, Medtronic, Northridge, CA, USA) between weeks 13 and 14. Results: The AHCL system improved glycemic control from weeks 14 to 26, achieving international guidelines with TIR = 72%, TAR = 24%, TBR = 4%. At week 30, TIR was 66%, TAR 31%. By altering diet and adding 'fake carbohydrates', she maintained TIR ≥ 70%, TBR ≤ 4%, TAR ≤ 26% from week 34 to birth. A healthy 4 kg, 53 cm baby boy was born at week 38. Conclusions: The use of the AHCL system holds significant promise for improving glycemic control in pregnancy. Optimal glycemic control with MiniMedTM 780G in pregnancy requires accurate carbohydrate counting, specific timing of insulin doses in relation to meal consumption and dietary choices that reduce the glycemic load of meals continue to be crucial factors in achieving optimal glycemic control during pregnancy using the MiniMedTM 780G system. Further research and clinical studies are needed to explore the full potential of these advanced systems in managing T1DM during pregnancy and optimizing maternal and neonatal outcomes.

A Diabetes Pregnancy Technology Roadmap: The 2023 Norbert Freinkel Award Lecture

Norbert Freinkel emphasized the need for "more aggressive therapy with exogenous insulin" during type 1 diabetes (T1D) pregnancy. Recent advances in diabetes technology, continuous glucose monitoring (CGM), and hybrid closed-loop (HCL) insulin delivery systems allow us to revisit Freinkel's observations from a contemporary perspective. The Continuous Glucose Monitoring in Women With Type 1 Diabetes in Pregnancy Trial (CONCEPTT) led to international recommendations that CGM be offered to all pregnant women with T1D to help them meet their pregnancy glucose targets and improve neonatal outcomes. However, despite CGM use, only 35% of trial participants reached the pregnancy glucose targets by 35 weeks' gestation, which is too late for optimal obstetric and neonatal outcomes. The constant vigilance to CGM data and insulin dose adjustment, with perpetual worry about the impact of hyperglycemia on the developing fetal structures, leave many pregnant women feeling overwhelmed. HCL systems that can adapt to marked gestational changes in insulin sensitivity and pharmacokinetics may help to bridge the gap between the nonpregnant time in range glycemic targets (70-180 mg/dL) and the substantially more stringent pregnancy-specific targets (TIRp) (63-140 mg/dL) required for optimal obstetric and neonatal outcomes. Use of HCL (CamAPS FX system) was associated with a 10.5% higher TIRp, 10.2% less hyperglycemia, and 12.3% higher overnight TIRp. Clinical benefits were accompanied by 3.7 kg (8 lb) less gestational weight gain and consistently achieved across a representative patient population of insulin pump or injection users, across trial sites, and across maternal HbA1c categories. Working collaboratively, women, HCL technology, and health care teams achieved improved glycemia with less worry, less work, and more positive pregnancy experiences.

Effect of artificial pancreas system use on glycaemic control among pregnant women with type 1 diabetes mellitus: A meta-analysis of randomized controlled trials

AIM

To assess the efficacy of artificial pancreas systems (APS) use among pregnant women with type 1 diabetes mellitus (T1DM) by conducting a meta-analysis.

METHODS

We searched five databases, including EMBASE, Web of Science, PubMed, Cochrane Library and SCOPUS, for literature on APS use among pregnant women with T1DM before October 9, 2023. The primary endpoint was 24-hour time in range (TIR; 3.5-7.8 mmol/L). Secondary endpoints included glycaemic metrics for 24-hour (mean blood glucose [MBG], time above range [TAR], time below range [TBR]), and overnight TIR and TBR.

RESULTS

We identified four randomized controlled trials involving 164 participants; one study with 16 participants focused on overnight APS use, and the other three focused on 24-hour APS use. Compared with standard care, APS exhibited a favourable effect on 24-hour TIR (standard mean difference [SMD] = 0.53, 95% confidence interval [CI] 0.25, 0.80, P < 0.001), overnight TIR (SMD = 0.67, 95% CI 0.39, 0.95, P < 0.001), and overnight TBR (<3.5 mmol/L; SMD = -0.49, 95% CI -0.77, -0.21 P < 0.001), while there was no significant difference in 24-hour TAR, 24-hour TBR, or MBG between the two groups. We further conducted subgroup analyses after removing the trial focused on overnight APS use and showed that 24-hour APS use reduced not only the 24-hour TIR (SMD = 0.41, 95% CI 0.12, 0.71; P = 0.007) but also the 24-hour TBR (<2.8 mmol/L; SMD = -0.77, 95% CI -1.32, -0.23, P = 0.006).

CONCLUSION

Our findings suggest that APS might improve 24-hour TIR and overnight glycaemic control, and 24-hour APS use also significantly reduced 24-hour TBR (2.8 mmol/L) among pregnant women with T1DM.

Automated Insulin Delivery for Pregnant Women With Type 1 Diabetes: Where do we stand?

Automated insulin delivery (AID) systems mimic an artificial pancreas via a predictive algorithm integrated with continuous glucose monitoring (CGM) and an insulin pump, thereby providing AID. Outside of pregnancy, AID has led to a paradigm shift in the management of people with type 1 diabetes (T1D), leading to improvements in glycemic control with lower risk for hypoglycemia and improved quality of life. As the use of AID in clinical practice is increasing, the number of women of reproductive age becoming pregnant while using AID is also expected to increase. The requirement for lower glucose targets than outside of pregnancy and for frequent adjustments of insulin doses during pregnancy may impact the effectiveness and safety of AID when using algorithms for non-pregnant populations with T1D. Currently, the CamAPS® FX is the only AID approved for use in pregnancy. A recent randomized controlled trial (RCT) with CamAPS® FX demonstrated a 10% increase in time in range in a pregnant population with T1D and a baseline glycated hemoglobin (HbA1c) ≥ 48 mmol/mol (6.5%). Off-label use of AID not approved for pregnancy are currently also being evaluated in ongoing RCTs. More evidence is needed on the impact of AID on maternal and neonatal outcomes. We review the current evidence on the use of AID in pregnancy and provide an overview of the completed and ongoing RCTs evaluating AID in pregnancy. In addition, we discuss the advantages and challenges of the use of current AID in pregnancy and future directions for research.

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.

Recent trends and advances in type 1 diabetes therapeutics: A comprehensive review

Type 1 diabetes (T1D) is a chronic autoimmune disease characterized by the destruction of pancreatic β-cells, leading to insulin deficiency. Insulin replacement therapy is the current standard of care for T1D, but it has significant limitations. However, stem cell-based replacement therapy has the potential to restore β-cell function and achieve glycaemic control eradicating the necessity for drugs or injecting insulin externally. While significant progress has been made in preclinical studies, the clinical translation of stem cell therapy for T1D is still in its early stages. In continuation, further research is essentially required to determine the safety and efficacy of stem cell therapies and to develop strategies to prevent immune rejection of stem cell-derived β-cells. The current review highlights the current state of cellular therapies for T1D including, different types of stem cell therapies, gene therapy, immunotherapy, artificial pancreas, and cell encapsulation being investigated, and their potential for clinical translation.

Healthcare professionals' views about how pregnant women can benefit from using a closed-loop system: Qualitative study

BACKGROUND

Interest is growing in how closed-loop systems can support attainment of within-target glucose levels amongst pregnant women with type 1 diabetes. We explored healthcare professionals' views about how, and why, pregnant women benefitted from using the CamAPS FX system during the AiDAPT trial.

METHODS

We interviewed 19 healthcare professionals who supported women using closed-loop during the trial. Our analysis focused on identifying descriptive and analytical themes relevant to clinical practice.

RESULTS

Healthcare professionals highlighted clinical and quality-of-life benefits to using closed-loop in pregnancy; albeit, they attributed some of these to the continuous glucose monitoring component. They emphasised that the closed-loop was not a panacea and that, to gain maximum benefit, an effective collaboration between themselves, the woman and the closed-loop was needed. Optimal performance of the technology, as they further noted, also required women to interact with the system sufficiently, but not excessively; a requirement that they felt some women had found challenging. Even where healthcare professionals felt that this balance was not achieved, they suggested that women had still benefitted from using the system. Healthcare professionals reported difficulties predicting how specific women would engage with the technology. In light of their trial experiences, healthcare professionals favoured an inclusive approach to closed-loop rollout in routine clinical care.

CONCLUSIONS

Healthcare professionals recommended that closed-loop systems be offered to all pregnant women with type 1 diabetes in the future. Presenting closed-loop systems to pregnant women and healthcare teams as one pillar of a three-party collaboration may help promote optimal use.

Real-world use of Control-IQ™ technology automated insulin delivery in pregnancy: A case series with qualitative interviews

BACKGROUND

Most commercially available automated insulin delivery (AID) systems are not approved for pregnancy use. Information regarding use of the Tandem t:slim X2 insulin pump with Control-IQ™ technology in pregnancy is lacking.

AIMS

This case series aimed to explore glycaemic and qualitative experiences of four early adopters of Control-IQ technology in pregnancy.

METHODS

Participants used Control-IQ technology in pregnancy and postpartum and consented to analysis of glycaemic data and semi-structured interviews.

RESULTS

Case 1 began Control-IQ technology at 10 weeks gestation. Her pregnancy glucose time-in-range (3.5-7.8 mmol/L [63-140 mg/dL]) increased from 58.7% to 73.3% by third trimester. Cases 2-4 began using Control-IQ technology 0-2 months preconception. Pregnancy time-in-range glucose increased from 73.4% to 78.7%, 78% to 83.6%, and 46.5% to 71.9% between first and third trimesters, respectively. A mid-pregnancy decline in time-in-range glucose was observed in two of the four participants related to suboptimal pump setting adjustments and delays in sensor and infusion set replacement. No diabetic ketoacidosis or severe hypoglycaemia occurred. All participants reported reduced diabetes management burden and improved sleep with Control-IQ technology use.

CONCLUSIONS

Early adopters of Control-IQ technology safely used this system off-label in pregnancy and reported reduced diabetes management burden and improved sleep. The largest glycaemic improvements were observed among those with the lowest pregnancy time-in-range glucose at the beginning of pregnancy. Participants with low pregnancy glucose time-in-range increased their time-in-range with Control-IQ technology use and participants with high pregnancy glucose time-in-range maintained and increased their time-in-range with less diabetes management burden.

Closed-loop insulin delivery in pregnant women with type 1 diabetes (CRISTAL): a multicentre randomized controlled trial - study protocol

BACKGROUND

Despite increasing use of continuous glucose monitoring (CGM) and continuous subcutaneous insulin infusion (CSII, insulin pumps) in type 1 diabetes (T1D) in pregnancy, achieving recommended pregnancy glycaemic targets (3.5-7.8 mmol/L or 63-140 mg/dL) remains challenging. Consequently, the risk of adverse pregnancy outcomes remains high. Outside pregnancy, hybrid closed-loop (HCL) insulin delivery systems have led to a paradigm shift in the management of T1D, with 12% higher time in glucose target range (TIR) compared to conventional CSII. However, most commercially available HCL systems are currently not approved for use in pregnancy. This study aims to evaluate the efficacy, safety and cost-effectiveness of the MiniMed™ 780G HCL system (Medtronic) in T1D in pregnancy.

METHODS

In this international, open-label, randomized controlled trial (RCT), we will compare the MiniMed™ 780G HCL system to standard of care (SoC) in T1D in pregnancy. Women aged 18-45 years with T1D diagnosis of at least one year, HbA1c ≤ 86 mmol/mol (≤ 10%), and confirmed singleton pregnancy up to 11 weeks 6 days will be eligible. After providing written informed consent, all participants will wear a similar CGM system (Guardian™ 3 or Guardian™ 4 CGM) during a 10-day run-in phase. After the run-in phase, participants will be randomised 1:1 to 780G HCL (intervention) or SoC [control, continuation of current T1D treatment with multiple daily injections (MDI) or CSII and any type of CGM] stratified according to centre, baseline HbA1c (< 53 vs. ≥ 53 mmol/mol or < 7 vs. ≥ 7%), and method of insulin delivery (MDI or CSII). The primary outcome will be the time spent within the pregnancy glucose target range, as measured by the CGM at four time points in pregnancy: 14-17, 20-23, 26-29, and 33-36 weeks. Prespecified secondary outcomes will be overnight TIR, time below range (TBR: <3.5 mmol/L or < 63 mg/dL), and overnight TBR. Other outcomes will be exploratory. The planned sample size is 92 participants. The study will end after postpartum discharge from hospital. Analyses will be performed according to intention-to-treat as well as per protocol.

DISCUSSION

This large RCT will evaluate a widely used commercially available HCL system in T1D in pregnancy. Recruitment began in January 2021 and was completed in October 2022. Study completion is expected in May 2023.

TRIAL REGISTRATION

ClinicalTrials.gov: NCT04520971. Registration date: August 20, 2020. https://clinicaltrials.gov/ct2/show/NCT04520971.

Automated insulin delivery: benefits, challenges, and recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association

A technological solution for the management of diabetes in people who require intensive insulin therapy has been sought for decades. The last 10 years have seen substantial growth in devices that can be integrated into clinical care. Driven by the availability of reliable systems for continuous glucose monitoring, we have entered an era in which insulin delivery through insulin pumps can be modulated based on sensor glucose data. Over the past few years, regulatory approval of the first automated insulin delivery (AID) systems has been granted, and these systems have been adopted into clinical care. Additionally, a community of people living with type 1 diabetes has created its own systems using a do-it-yourself approach by using products commercialised for independent use. With several AID systems in development, some of which are anticipated to be granted regulatory approval in the near future, the joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association has created this consensus report. We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions. This is the fourth in a series of reports issued by this working group. The working group was jointly commissioned by the executives of both organisations to write the first statement on insulin pumps, which was published in 2015. The original authoring group was comprised by three nominated members of the American Diabetes Association and three nominated members of the European Association for the Study of Diabetes. Additional authors have been added to the group to increase diversity and range of expertise. Each organisation has provided a similar internal review process for each manuscript prior to submission for editorial review by the two journals. Harmonisation of editorial and substantial modifications has occurred at both levels. The members of the group have selected the subject of each statement and submitted the selection to both organisations for confirmation.

What's new in the management of type 1 diabetes in pregnancy?

Type 1 diabetes in pregnancy is associated with an increased risk of complications for both mother and fetus. However, managing glycaemia during pregnancy to reduce these risks is challenging, owing to changes in insulin resistance with advancing gestation, as well as increased daily variation in insulin pharmacokinetics. These factors can add significant psychological and daily self-care burden to mothers during what may already be an anxious time. Increasingly, diabetes technologies are being used during pregnancy to improve and facilitate diabetes self-care. While these can be empowering for people with type 1 diabetes, careful consideration is required in relation to how and when these can be continued safely in the inpatient setting (including acute antenatal admissions, labour and delivery) and when extra support is required from adequately trained healthcare professionals. This article describes current forms of diabetes technologies used and the latest national guidance relating to the care of type 1 diabetes in pregnancy.

Automated Insulin Delivery: Benefits, Challenges, and Recommendations. A Consensus Report of the Joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association

A technological solution for the management of diabetes in people who require intensive insulin therapy has been sought for decades. The last 10 years have seen substantial growth in devices that can be integrated into clinical care. Driven by the availability of reliable systems for continuous glucose monitoring, we have entered an era in which insulin delivery through insulin pumps can be modulated based on sensor glucose data. Over the past few years, regulatory approval of the first automated insulin delivery (AID) systems has been granted, and these systems have been adopted into clinical care. Additionally, a community of people living with type 1 diabetes has created its own systems using a do-it-yourself approach by using products commercialized for independent use. With several AID systems in development, some of which are anticipated to be granted regulatory approval in the near future, the joint Diabetes Technology Working Group of the European Association for the Study of Diabetes and the American Diabetes Association has created this consensus report. We provide a review of the current landscape of AID systems, with a particular focus on their safety. We conclude with a series of recommended targeted actions. This is the fourth in a series of reports issued by this working group. The working group was jointly commissioned by the executives of both organizations to write the first statement on insulin pumps, which was published in 2015. The original authoring group was comprised by three nominated members of the American Diabetes Association and three nominated members of the European Association for the Study of Diabetes. Additional authors have been added to the group to increase diversity and range of expertise. Each organization has provided a similar internal review process for each manuscript prior to submission for editorial review by the two journals. Harmonization of editorial and substantial modifications has occurred at both levels. The members of the group have selected the subject of each statement and submitted the selection to both organizations for confirmation.

AiDAPT: automated insulin delivery amongst pregnant women with type 1 diabetes: a multicentre randomized controlled trial - study protocol

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.

Zone-MPC Automated Insulin Delivery Algorithm Tuned for Pregnancy Complicated by Type 1 Diabetes

Type 1 diabetes (T1D) increases the risk for pregnancy complications. Increased time in the pregnancy glucose target range (63-140 mg/dL as suggested by clinical guidelines) is associated with improved pregnancy outcomes that underscores the need for tight glycemic control. While closed-loop control is highly effective in regulating blood glucose levels in individuals with T1D, its use during pregnancy requires adjustments to meet the tight glycemic control and changing insulin requirements with advancing gestation. In this paper, we tailor a zone model predictive controller (zone-MPC), an optimization-based control strategy that uses model predictions, for use during pregnancy and verify its robustness in-silico through a broad range of scenarios. We customize the existing zone-MPC to satisfy pregnancy-specific glucose control objectives by having (i) lower target glycemic zones (i.e., 80-110 mg/dL daytime and 80-100 mg/dL overnight), (ii) more assertive correction bolus for hyperglycemia, and (iii) a control strategy that results in more aggressive postprandial insulin delivery to keep glucose within the target zone. The emphasis is on leveraging the flexible design of zone-MPC to obtain a controller that satisfies glycemic outcomes recommended for pregnancy based on clinical insight. To verify this pregnancy-specific zone-MPC design, we use the UVA/Padova simulator and conduct in-silico experiments on 10 subjects over 13 scenarios ranging from scenarios with ideal metabolic and treatment parameters for pregnancy to extreme scenarios with such parameters that are highly deviant from the ideal. All scenarios had three meals per day and each meal had 40 grams of carbohydrates. Across 13 scenarios, pregnancy-specific zone-MPC led to a 10.3 ± 5.3% increase in the time in pregnancy target range (baseline zone-MPC: 70.6 ± 15.0%, pregnancy-specific zone-MPC: 80.8 ± 11.3%, p < 0.001) and a 10.7 ± 4.8% reduction in the time above the target range (baseline zone-MPC: 29.0 ± 15.4%, pregnancy-specific zone-MPC: 18.3 ± 12.0, p < 0.001). There was no significant difference in the time below range between the controllers (baseline zone-MPC: 0.5 ± 1.2%, pregnancy-specific zone-MPC: 3.5 ± 1.9%, p = 0.1). The extensive simulation results show improved performance in the pregnancy target range with pregnancy-specific zone MPC, suggest robustness of the zone-MPC in tight glucose control scenarios, and emphasize the need for customized glucose control systems for pregnancy.

Glycaemic control and novel technology management strategies in pregestational diabetes mellitus

INTRODUCTION

Pregestational diabetes (PGDM) is an increasingly common and complex condition that infers risk to both mother and infant. To prevent serious morbidity, strict glycaemic control is essential. The aim of this review is to review the glucose sensing and insulin delivering technologies currently available for women with PGDM.

METHODS

We reviewed online databases for articles relating to technology use in pregnancy using a combination of keywords and MeSH headings. Relevant articles are included below.

RESULTS

A number of technological advancements have improved care and outcomes for women with PGDM. Real time continuous glucose monitoring (rtCGM) offers clear advantages in terms of infants size and neonatal intensive care unit admissions; and further benefits are seen when combined with continuous subcutaneous insulin delivery (insulin pump) and algorithms which continuously adjust insulin levels to glucose targets (hybrid closed loop). Other advancements including flash or intermittent scanning CGM (isCGM) and stand-alone insulin pumps do not confer as many advantages for women and their infants, however they are increasingly used outside of pregnancy and many women enter pregnancy already using these devices.

DISCUSSION

This article offers a discussion of the most commonly used technologies in pregnancy and evaluates their current and future roles.

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.

A systematic review on outcome reporting in randomised controlled trials assessing treatment interventions in pregnant women with pregestational diabetes

BACKGROUND

Pregestational diabetes mellitus (PGDM) is associated with adverse pregnancy outcomes. Studies assessing interventions to improve maternal and infant outcomes have increased exponentially over recent years. Several outcomes in this field of maternal diabetes are rare, making it difficult to synthesise evidence.

OBJECTIVES

To collect outcomes reported in studies assessing treatment interventions in pregnant women with PGDM.

SEARCH STRATEGY

CENTRAL, Web of Science, Medline, CINAHL, Embase and ClinicalTrials.gov from their inception until 27 January 2020.

SELECTION CRITERIA

Any randomised controlled trial assessing treatment interventions in pregnant women with PGDM reported in English.

DATA COLLECTION AND ANALYSIS

Two independent reviewers assessed the suitability of articles and retrieved the data. Outcomes extracted from the literature were broadly categorised into maternal, fetal/infant or other outcomes by the study advisory group.

MAIN RESULTS

Sixty-seven of the 1475 studies identified fulfilled the inclusion criteria. The median number of outcomes reported per study was 15 (range 1-46). The majority of studies were from North America and Europe. Insulin and metformin were the most commonly investigated pharmacological interventions. Glucose monitoring was the most assessed technological intervention. In all, 131 unique outcomes were extracted: maternal (n = 69), fetal/infant (n = 61) and other (n = 1).

CONCLUSIONS

Outcome reporting in treatment interventions trials of pregnant women with PGDM is varied, making it difficult to synthesise evidence, especially for rare outcomes. Systems are needed to standardise outcome reporting in future clinical trials and so facilitate evidence synthesis in this area of maternal diabetes.

REGISTRATION

The systematic review was registered prospectively with the International Prospective Register of Systematic Reviews (PROSPERO) database (Registration number CRD42020173549).

TWEETABLE ABSTRACT

Outcome reporting is heterogeneous in intervention trials of pregnant women with diabetes existing before pregnancy.

A core outcome set for the treatment of pregnant women with pregestational diabetes: an international consensus study

Objective

To develop a core outcome set (COS) for randomised controlled trials (RCTs) evaluating the effectiveness of interventions for the treatment of pregnant women with pregestational diabetes mellitus (PGDM).

Design

A consensus developmental study.

Setting

International.

Population

Two hundred and five stakeholders completed the first round.

Methods

The study consisted of three components. (1) A systematic review of the literature to produce a list of outcomes reported in RCTs assessing the effectiveness of interventions for the treatment of pregnant women with PGDM. (2) A three-round, online eDelphi survey to prioritise these outcomes by international stakeholders (including healthcare professionals, researchers and women with PGDM). (3) A consensus meeting where stakeholders from each group decided on the final COS.

Main outcome measures

All outcomes were extracted from the literature.

Results

We extracted 131 unique outcomes from 67 records meeting the full inclusion criteria. Of the 205 stakeholders who completed the first round, 174/205 (85%) and 165/174 (95%) completed rounds 2 and 3, respectively. Participants at the subsequent consensus meeting chose 19 outcomes for inclusion into the COS: trimester-specific haemoglobin A1c, maternal weight gain during pregnancy, severe maternal hypoglycaemia, diabetic ketoacidosis, miscarriage, pregnancy-induced hypertension, pre-eclampsia, maternal death, birthweight, large for gestational age, small for gestational age, gestational age at birth, preterm birth, mode of birth, shoulder dystocia, neonatal hypoglycaemia, congenital malformations, stillbirth and neonatal death.

Conclusions

This COS will enable better comparison between RCTs to produce robust evidence synthesis, improve trial reporting and optimise research efficiency in studies assessing treatment of pregnant women with PGDM.

165 key stakeholders have developed #Treatment #CoreOutcomes in pregnant women with #diabetes existing before pregnancy.

Type 1 Diabetes: Management in Women From Preconception to Postpartum

CONTEXT

This review presents an up-to-date summary on management of type 1 diabetes mellitus (T1DM) among women of reproductive age and covers the following time periods: preconception, gestation, and postpartum.

EVIDENCE ACQUISITION

A systematic search and review of the literature for randomized controlled trials and other studies evaluating management of T1DM before pregnancy, during pregnancy, and postpartum was performed.

EVIDENCE SYNTHESIS

Preconception planning should begin early in the reproductive years for young women with T1DM. Preconception and during pregnancy, it is recommended to have near-normal glucose values to prevent adverse maternal and neonatal outcomes, including fetal demise, congenital anomaly, pre-eclampsia, macrosomia, neonatal respiratory distress, neonatal hyperbilirubinemia, and neonatal hypoglycemia.

CONCLUSION

Women with T1DM can have healthy, safe pregnancies with preconception planning, optimal glycemic control, and multidisciplinary care.

Diabetes Technology Use in Adults with Type 1 and Type 2 Diabetes

In the last 2 decades, diabetes technology has emerged as a branch of diabetes management thanks to the advent of continuous glucose monitoring (CGM) and increased availability of continuous subcutaneous insulin infusion systems, or insulin pumps. These tools have progressed from rudimentary instruments to sophisticated therapeutic options for advanced diabetes management. This article discusses the available CGM and insulin pump systems and the clinical benefits of their use in adults with type 1 diabetes, intensively insulin-treated type 2 diabetes, and pregnant patients with preexisting diabetes.

The Clinical Case for the Integration of a Ketone Sensor as Part of a Closed Loop Insulin Pump System

Closed loop (CL) systems deliver insulin with a rapid onset and offset in action. Although favorable overall, the absence of a long-acting insulin increases the risk of diabetic ketoacidosis (DKA) which can occur with insulin delivery failure, acute illness, low carbohydrate diets, sodium glucose-linked transporter inhibitors, and high intensity exercise. A CL system relying entirely on interstitial glucose measurements may not provide an alert for DKA and many people with type 1 diabetes (T1D) do not carry a blood ketone meter and test-strips. Ketone sensing is theoretically feasible. A multianalyte platform incorporating a ketone sensor could provide an additional CL input without an increase in burden for the person with T1D, warning of impending DKA to allow remedial action to be taken. We outline the clinical case for inclusion of continuous ketone sensing as part of future CL systems.

Single-Hormone Artificial Pancreas Use in Diabetes: Clinical Efficacy and Remaining Challenges

IN BRIEF Artificial pancreas systems are rapidly developing and constitute the most promising technology for insulin-requiring diabetes management. Single-hormone systems (SH-AP) that deliver only insulin and have a hybrid design that necessitates patients' interventions around meals and exercise are the first to appear on the market. Trials with SH-AP have demonstrated improvement in time spent with blood glucose levels within target ranges, with a concomitant decrease in hypoglycemia. Longer and larger trials involving different patient populations are ongoing to further advance this important technology.

Improving Glucose Prediction Accuracy in Physically Active Adolescents With Type 1 Diabetes

BACKGROUND

Physical activity presents a significant challenge for glycemic control in individuals with type 1 diabetes. As accurate glycemic predictions are key to successful automated decision-making systems (eg, artificial pancreas, AP), the inclusion of additional physiological variables in the estimation of the metabolic state may improve the glucose prediction accuracy during exercise.

METHODS

Predictor-based subspace identification is applied to a dynamic glucose prediction model including heart rate measurements along with variables representing the carbohydrate consumption and insulin boluses. To demonstrate the improvement in prediction ability due to the additional heart rate variable, the performance of the proposed modeling technique is evaluated with (SID-HR) and without heart rate (SID-2) as an additional input using experimental data involving adolescents at ski camp. Furthermore, the performance of the proposed approach is compared to that of the metabolic state observer (MSO) model currently used in the University of Virginia AP algorithm.

RESULTS

The addition of heart rate in the subspace-based model (SID-HR) yields a statistically significant improvement in the root-mean-square error compared to the SID-2 model (P < .001) and the standard MSO (P < .001). Furthermore, the SID-HR model performed favorably in comparison to the SID-2 and MSO models after accounting for its increased complexity.

CONCLUSIONS

Directly considering the effects of physical activity levels on glycemic dynamics through the inclusion of heart rate as an additional input variable in the glucose dynamics model improves the glucose prediction accuracy. The proposed methodology could improve exercise-informed model-based predictive control algorithms in artificial pancreas systems.

Using the Novel Approach of an Artificial Pancreas to Manage Type 1 Diabetes Mellitus in Pregnancy

Recent National Institute for Health and Care Excellence (NICE) guidelines suggest that insulin pump therapy should be used in pregnant women with Type 1 diabetes mellitus (T1DM) who do not achieve optimal glycaemic control with multiple daily injection (MDI) therapy. Furthermore, a landmark trial has confirmed that prospective continuous glucose monitoring (CGM) may be beneficial for women using both MDI and insulin pumps during pregnancy, with positive effects on neonatal outcomes. More recently, overnight use of an artificial pancreas (AP) with a model-predictive control algorithm has been shown to improve the amount of time women spend within the overnight glucose target range (3.5–7.8 mmol/L) during pregnancy. However, preliminary studies where the AP is used day and night have shown a high degree of interindividual variability in response to the intervention, and further randomised trials are needed to understand which women are suitable candidates for CGM, insulin pump, and AP technology. It is understood that improvements in maternal glycaemic control can minimise the risk of adverse neonatal outcomes. Given the substantial improvements in glycaemic control with AP use outside of pregnancy, the recent advances in AP technology provide hope that AP systems will improve the effectiveness of continuous subcutaneous insulin infusion and CGM during pregnancy. Further research is needed to evaluate whether AP can optimise glucose control and neonatal outcomes in T1DM pregnancy. This paper will discuss emerging technologies available for the management of T1DM in pregnancy.

Management of Preexisting Diabetes in Pregnancy: A Review

IMPORTANCE

The presence of preexisting type 1 or type 2 diabetes in pregnancy increases the risk of adverse maternal and neonatal outcomes, such as preeclampsia, cesarean delivery, preterm delivery, macrosomia, and congenital defects. Approximately 0.9% of the 4 million births in the United States annually are complicated by preexisting diabetes.

OBSERVATIONS

Women with diabetes have increased risk for adverse maternal and neonatal outcomes, and similar risks are present with type 1 and type 2 diabetes. Both forms of diabetes require similar intensity of diabetes care. Preconception planning is very important to avoid unintended pregnancies and to minimize risk of congenital defects. Hemoglobin A1c goals are less than 6.5% at conception and less than 6.0% during pregnancy. It is also critical to screen for and manage comorbid illnesses, such as retinopathy and nephropathy. Medications known to be unsafe in pregnancy, such as angiotensin-converting enzyme inhibitors and statins, should be discontinued. Women with obesity should be screened for obstructive sleep apnea, which is often undiagnosed and can result in poor outcomes. Blood pressure goals must be considered carefully because lower treatment thresholds may be required for women with nephropathy. During pregnancy, continuous glucose monitoring can improve glycemic control and neonatal outcomes in women with type 1 diabetes. Insulin is first-line therapy for all women with preexisting diabetes; injections and insulin pump therapy are both effective approaches. Rates of severe hypoglycemia are increased during pregnancy; therefore, glucagon should be available to the patient and close contacts should be trained in its use. Low-dose aspirin is recommended soon after 12 weeks' gestation to minimize the risk of preeclampsia. The importance of discussing long-acting reversible contraception before and after pregnancy, to allow for appropriate preconception planning, cannot be overstated.

CONCLUSIONS AND RELEVANCE

Preexisting diabetes in pregnancy is complex and is associated with significant maternal and neonatal risk. Optimization of glycemic control, medication regimens, and careful attention to comorbid conditions can help mitigate these risks and ensure quality diabetes care before, during, and after pregnancy.

Multivariable Artificial Pancreas for Various Exercise Types and Intensities

BACKGROUND

Exercise challenges people with type 1 diabetes in controlling their glucose concentration (GC). A multivariable adaptive artificial pancreas (MAAP) may lessen the burden.

METHODS

The MAAP operates without any user input and computes insulin based on continuous glucose monitor and physical activity signals. To analyze performance, 18 60-h closed-loop experiments with 96 exercise sessions with three different protocols were completed. Each day, the subjects completed one resistance and one treadmill exercise (moderate continuous training [MCT] or high-intensity interval training [HIIT]). The primary outcome is time spent in each glycemic range during the exercise + recovery period. Secondary measures include average GC and average change in GC during each exercise modality.

RESULTS

The GC during exercise + recovery periods were within the euglycemic range (70-180 mg/dL) for 69.9% of the time and within a safe glycemic range for exercise (70-250 mg/dL) for 93.0% of the time. The exercise sessions are defined to begin 30 min before the start of exercise and end 2 h after start of exercise. The GC were within the severe hypoglycemia (<55 mg/dL), moderate hypoglycemia (55-70 mg/dL), moderate hyperglycemia (180-250 mg/dL), and severe hyperglycemia (>250 mg/dL) for 0.9%, 1.3%, 23.1%, and 4.8% of the time, respectively. The average GC decline during exercise differed with exercise type (P = 0.0097) with a significant difference between the MCT and resistance (P = 0.0075). To prevent large GC decreases leading to hypoglycemia, MAAP recommended carbohydrates in 59% of MCT, 50% of HIIT, and 39% of resistance sessions.

CONCLUSIONS

A consistent GC decline occurred in exercise and recovery periods, which differed with exercise type. The average GC at the start of exercise was above target (185.5 ± 56.6 mg/dL for MCT, 166.9 ± 61.9 mg/dL for resistance training, and 171.7 ± 41.4 mg/dL HIIT), making a small decrease desirable. Hypoglycemic events occurred in 14.6% of exercise sessions and represented only 2.22% of the exercise and recovery period.

Day-and-Night Closed-Loop Insulin Delivery in a Broad Population of Pregnant Women With Type 1 Diabetes: A Randomized Controlled Crossover Trial

OBJECTIVE

Despite advances in technology, optimal glucose control remains elusive and neonatal complications remain ubiquitous in type 1 diabetes (T1D) pregnancy. Our aim was to examine the safety, efficacy, and longer-term feasibility of day-and-night closed-loop insulin delivery.

RESEARCH DESIGN AND METHODS

We recruited 16 pregnant women (mean [SD]: age 32.8 [5.0] years, T1D duration 19.4 [10.2] years, HbA_1c 8.0% [1.1], and BMI 26.6 [4.4] kg/m²) to an open-label, randomized, crossover trial. Participants completed 28 days of closed-loop and sensor-augmented pump (SAP) insulin delivery separated by a washout period. Afterward, participants could continue to use the closed-loop system up to 6 weeks postpartum. The primary end point was the proportion of time with glucose levels within the target range (63-140 mg/dL).

RESULTS

The proportion of time with glucose levels within target was comparable during closed-loop and SAP insulin delivery (62.3 vs. 60.1% [95% CI -4.1 to 8.3]; P = 0.47). Mean glucose and time spent hyperglycemic >140 mg/dL also did not differ (131.4 vs. 131.4 mg/dL [P = 0.85] and 36.6 vs. 36.1% [P = 0.86], respectively). During closed-loop, fewer hypoglycemic episodes occurred (median 8 [range 1-17] vs. 12.5 [1-53] over 28 days; P = 0.04) and less time at <63 mg/dL (1.6 vs. 2.7%; P = 0.02). Hypoglycemia <50 mg/dL (0.24 vs. 0.47%; P = 0.03) and low blood glucose index (1.0 vs. 1.4; P = 0.01) were lower. Less nocturnal hypoglycemia (2300-0700 h) during closed-loop therapy (1.1 vs. 2.7%; P = 0.008) and a trend toward higher overnight time in target (67.7 vs. 60.6%; P = 0.06) were found.

CONCLUSIONS

Closed-loop insulin delivery was associated with comparable glucose control and significantly less hypoglycemia than SAP therapy. Larger, longer-duration multicenter trials are now indicated to determine clinical efficacy of closed-loop insulin delivery in T1D pregnancy and the impact on neonatal outcomes.

Automated blood glucose control in type 1 diabetes: A review of progress and challenges

Since the 2000s, research teams worldwide have been working to develop closed-loop (CL) systems able to automatically control blood glucose (BG) levels in patients with type 1 diabetes. This emerging technology is known as artificial pancreas (AP), and its first commercial version just arrived in the market. The main objective of this paper is to present an extensive review of the clinical trials conducted since 2011, which tested various implementations of the AP for different durations under varying conditions. A comprehensive table that contains key information from the selected publications is provided, and the main challenges in AP development and the mitigation strategies used are discussed. The development timelines for different AP systems are also included, highlighting the main evolutions over the clinical trials for each system.

Experiences of closed-loop insulin delivery among pregnant women with Type 1 diabetes

AIMS

To explore the experiences of pregnant women with Type 1 diabetes, and the relationships between perceptions of glucose control, attitudes to technology and glycaemic responses with regard to closed-loop insulin delivery.

METHODS

We recruited 16 pregnant women with Type 1 diabetes [mean ± sd age 34.1 ± 4.6 years, duration of diabetes 23.6 ± 7.2 years, baseline HbA_1c 51±5 mmol/mol (6.8 ± 0.6%)] to a randomized crossover trial of sensor-augmented pump therapy vs automated closed-loop therapy. Questionnaires (Diabetes Technology Questionnaire, Hypoglycaemia Fear Survey) were completed before and after each intervention, with qualitative interviews at baseline and follow-up.

RESULTS

Women described the benefits and burdens of closed-loop systems during pregnancy. Feelings of improved glucose control, excitement and empowerment were counterbalanced by concerns about device visibility, obsessive data checking and diminished attentiveness to hyper- and hypoglycaemia symptoms. Responding to questionnaires, eight participants felt less worry about overnight hypoglycaemia and that diabetes 'did not run their lives'; however, five reported that closed-loop increased time thinking about diabetes, and three felt it made sleep and preventing hyperglycaemia more problematic. Women slightly overestimated their glycaemic response to closed-loop therapy. Most became more positive in their technology attitudes throughout pregnancy. Women with more positive technology attitudes had higher degrees of overestimation, and poorer levels of glycaemic control.

CONCLUSIONS

Women displayed complex psychosocial responses to closed-loop therapy in pregnancy. Perceptions of glycaemic response may diverge from biomedical data.

CGM, Pregnancy, and Remote Monitoring

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

Different insulin types and regimens for pregnant women with pre-existing diabetes

BACKGROUND

Insulin requirements may change during pregnancy, and the optimal treatment for pre-existing diabetes is unclear. There are several insulin regimens (e.g. via syringe, pen) and types of insulin (e.g. fast-acting insulin, human insulin).

OBJECTIVES

To assess the effects of different insulin types and different insulin regimens in pregnant women with pre-existing type 1 or type 2 diabetes.

SEARCH METHODS

We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (30 October 2016), ClinicalTrials.gov (17 October 2016), the WHO International Clinical Trials Registry Platform (ICTRP; 17 October 2016), and the reference lists of retrieved studies.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that compared different insulin types and regimens in pregnant women with pre-existing diabetes.We had planned to include cluster-RCTs, but none were identified. We excluded quasi-randomised controlled trials and cross-over trials. We included studies published in abstract form and contacted the authors for further details when applicable. Conference abstracts were superseded by full publications.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed trials for inclusion, conducted data extraction, assessed risk of bias, and checked for accuracy. We assessed the quality of the evidence using the GRADE approach.

MAIN RESULTS

The findings in this review were based on very low-quality evidence, from single, small sample sized trial estimates, with wide confidence intervals (CI), some of which crossed the line of no effect; many of the prespecified outcomes were not reported. Therefore, they should be interpreted with caution. We included five trials that included 554 women and babies (four open-label, multi-centre, two-arm trials; one single centre, four-arm RCT). All five trials were at a high or unclear risk of bias due to lack of blinding, unclear methods of randomisation, and selective reporting of outcomes. Pooling of data from the trials was not possible, as each trial looked at a different comparison.1. One trial (N = 33 women) compared Lispro insulin with regular insulin and provided very low-quality evidence for the outcomes. There were seven episodes of pre-eclampsia in the Lispro group and nine in the regular insulin group, with no clear difference between the two groups (risk ratio (RR) 0.68, 95% CI 0.35 to 1.30). There were five caesarean sections in the Lispro group and nine in the regular insulin group, with no clear difference between the two groups (RR 0.59, 95% CI 0.25 to 1.39). There were no cases of fetal anomaly in the Lispro group and one in the regular insulin group, with no clear difference between the groups (RR 0.35, 95% CI 0.02 to 8.08). Macrosomia, perinatal deaths, episodes of birth trauma including shoulder dystocia, nerve palsy, and fracture, and the composite outcome measure of neonatal morbidity were not reported.2. One trial (N = 42 women) compared human insulin to animal insulin, and provided very low-quality evidence for the outcomes. There were no cases of macrosomia in the human insulin group and two in the animal insulin group, with no clear difference between the groups (RR 0.22, 95% CI 0.01 to 4.30). Perinatal death, pre-eclampsia, caesarean section, fetal anomaly, birth trauma including shoulder dystocia, nerve palsy and fracture and the composite outcome measure of neonatal morbidity were not reported.3. One trial (N = 93 women) compared pre-mixed insulin (70 NPH/30 REG) to self-mixed, split-dose insulin and provided very low-quality evidence to support the outcomes. Two cases of macrosomia were reported in the pre-mixed insulin group and four in the self-mixed insulin group, with no clear difference between the two groups (RR 0.49, 95% CI 0.09 to 2.54). There were seven cases of caesarean section (for cephalo-pelvic disproportion) in the pre-mixed insulin group and 12 in the self-mixed insulin group, with no clear difference between groups (RR 0.57, 95% CI 0.25 to 1.32). Perinatal death, pre-eclampsia, fetal anomaly, birth trauma including shoulder dystocia, nerve palsy, or fracture and the composite outcome measure of neonatal morbidity were not reported.4. In the same trial (N = 93 women), insulin injected with a Novolin pen was compared to insulin injected with a conventional needle (syringe), which provided very low-quality evidence to support the outcomes. There was one case of macrosomia in the pen group and five in the needle group, with no clear difference between the different insulin regimens (RR 0.21, 95% CI 0.03 to 1.76). There were five deliveries by caesarean section in the pen group compared with 14 in the needle group; women were less likely to deliver via caesarean section when insulin was injected with a pen compared to a conventional needle (RR 0.38, 95% CI 0.15 to 0.97). Perinatal death, pre-eclampsia, fetal anomaly, birth trauma including shoulder dystocia, nerve palsy, or fracture, and the composite outcome measure of neonatal morbidity were not reported.5. One trial (N = 223 women) comparing insulin Aspart with human insulin reported none of the review's primary outcomes: macrosomia, perinatal death, pre-eclampsia, caesarean section, fetal anomaly, birth trauma including shoulder dystocia. nerve palsy, or fracture, or the composite outcome measure of neonatal morbidity.6. One trial (N = 162 women) compared insulin Detemir with NPH insulin, and supported the outcomes with very low-quality evidence. There were three cases of major fetal anomalies in the insulin Detemir group and one in the NPH insulin group, with no clear difference between the groups (RR 3.15, 95% CI 0.33 to 29.67). Macrosomia, perinatal death, pre-eclampsia, caesarean section, birth trauma including shoulder dystocia, nerve palsy, or fracture and the composite outcome of neonatal morbidity were not reported.

AUTHORS' CONCLUSIONS

With limited evidence and no meta-analyses, as each trial looked at a different comparison, no firm conclusions could be made about different insulin types and regimens in pregnant women with pre-existing type 1 or 2 diabetes. Further research is warranted to determine who has an increased risk of adverse pregnancy outcome. This would include larger trials, incorporating adequate randomisation and blinding, and key outcomes that include macrosomia, pregnancy loss, pre-eclampsia, caesarean section, fetal anomalies, and birth trauma.

Closed-Loop Insulin Delivery during Pregnancy in Women with Type 1 Diabetes

BACKGROUND

In patients with type 1 diabetes who are not pregnant, closed-loop (automated) insulin delivery can provide better glycemic control than sensor-augmented pump therapy, but data are lacking on the efficacy, safety, and feasibility of closed-loop therapy during pregnancy.

METHODS

We performed an open-label, randomized, crossover study comparing overnight closed-loop therapy with sensor-augmented pump therapy, followed by a continuation phase in which the closed-loop system was used day and night. Sixteen pregnant women with type 1 diabetes completed 4 weeks of closed-loop pump therapy (intervention) and sensor-augmented pump therapy (control) in random order. During the continuation phase, 14 of the participants used the closed-loop system day and night until delivery. The primary outcome was the percentage of time that overnight glucose levels were within the target range (63 to 140 mg per deciliter [3.5 to 7.8 mmol per liter]).

RESULTS

The percentage of time that overnight glucose levels were in the target range was higher during closed-loop therapy than during control therapy (74.7% vs. 59.5%; absolute difference, 15.2 percentage points; 95% confidence interval, 6.1 to 24.2; P=0.002). The overnight mean glucose level was lower during closed-loop therapy than during control therapy (119 vs. 133 mg per deciliter [6.6 vs. 7.4 mmol per liter], P=0.009). There were no significant differences between closed-loop and control therapy in the percentage of time in which glucose levels were below the target range (1.3% and 1.9%, respectively; P=0.28), in insulin doses, or in adverse-event rates. During the continuation phase (up to 14.6 additional weeks, including antenatal hospitalizations, labor, and delivery), glucose levels were in the target range 68.7% of the time; the mean glucose level was 126 mg per deciliter (7.0 mmol per liter). No episodes of severe hypoglycemia requiring third-party assistance occurred during either phase.

CONCLUSIONS

Overnight closed-loop therapy resulted in better glucose control than sensor-augmented pump therapy in pregnant women with type 1 diabetes. Women receiving day-and-night closed-loop therapy maintained glycemic control during a high proportion of the time in a period that encompassed antenatal hospital admission, labor, and delivery. (Funded by the National Institute for Health Research and others; Current Controlled Trials number, ISRCTN71510001.).

Continuous subcutaneous insulin infusion versus multiple daily injections of insulin for pregnant women with diabetes

BACKGROUND

Diabetes results in a rise in blood glucose above normal physiological levels; if untreated this may cause damage to many systems including the cardiovascular and renal systems. Pregnancy increases resistance to insulin action; for those women who have pre-gestational diabetes, this results in an increasing insulin requirement. There are several methods of administering insulin. Conventionally, insulin has been administered subcutaneously, formally referred to as intensive conventional treatment, but now more usually referred to as multiple daily injections (MDI). An alternative method of insulin administration is the continuous subcutaneous insulin infusion pump (CSII).

OBJECTIVES

To compare CSII with MDI of insulin for pregnant women with pre-existing and gestational diabetes.

SEARCH METHODS

We searched the Cochrane Pregnancy and Childbirth Group's Trials Register (31 March 2016) and reference lists of retrieved studies.

SELECTION CRITERIA

Randomised trials comparing CSII with MDI for pregnant women with diabetes.

DATA COLLECTION AND ANALYSIS

Three review authors independently assessed studies and two review authors extracted data. Disagreements were resolved through discussion with the third author. We assessed the quality of the evidence using the GRADE approach.

MAIN RESULTS

We included five single-centre trials (undertaken in Italy) with 153 women and 154 pregnancies in this review.There were no clear differences in the primary outcomes reported between CSII and MDI in the included trials: caesarean section (risk ratio (RR) 1.09, 95% confidence interval (CI) 0.66 to 1.77; three trials, 71 women, evidence graded very low), large-for-gestational age (RR 4.15, 95% CI 0.49 to 34.95; three trials, 73 infants; evidence graded very low), and perinatal mortality (RR 2.33, 95% CI 0.38 to 14.32; four trials, 83 infants, evidence graded very low). Other primary outcomes were not reported in these trials (hypertensive disorders of pregnancy, development of type 2 diabetes, composite outcome of serious neonatal outcomes, and neurosensory disability).There was no clear evidence of differences in the maternal secondary outcomes: maternal weight gain during pregnancy, 24 hour mean blood glucose in each trimester, mean maternal HbA1c in each trimester, maternal hypoglycaemia, and maternal hyperglycaemia. The included studies did not report several GRADE outcomes: perineal trauma, return to pre-pregnancy weight, postnatal depression, induction of labour. Many maternal secondary outcomes were also not reported.In two trials, including a total of 61 infants, CSII was associated with an increase in mean birthweight compared with MDI (mean difference (MD) 220.56 g, 95% CI -2.09 g to 443.20 g; P = 0.05). However, the large CI including anything from a small reduction to an increase in mean birthweight and the lack of a difference in macrosomia rate (RR 3.20, CI 0.14 to 72.62; two trials, 61 infants) suggests uncertainty. Large-for-gestational age (see above), andsmall-for-gestational age also suggests uncertainty of effect. No significant differences were found in: gestation at delivery, preterm birth < 37 weeks' gestation, preterm birth < 32 weeks' gestation, neonatal hypoglycaemia (evidence graded very low), respiratory distress syndrome, neonatal hyperbilirubinaemia, and fetal anomaly. There were no data reported on many important infant outcomes, including the GRADE outcomes adiposity and diabetes. There was no follow-up of infants in childhood or adulthood, so longer-term outcomes were not reported.The only outcome reported for use of health service resources wasmaternal days hospitalised, which did not show a difference between groups in the small number of women included (MD 9.40, CI -6.04 to 24.84; one trial, 10 women).The methods used by the trials were poorly reported, for example although blinding of participants and clinicians regarding intervention allocation is impossible, it is possible to blind assessors and this along with other aspects of trial methods was not reported, which means that the trials are at an unclear or high risk of bias. We do not know if the women who participated were representative, and therefore if the results can be generalised. Most GRADE outcomes were not reported. For the GRADE outcomes that were reported, our assessment was that the evidence is very low quality (caesarean section, large-for-gestational age, perinatal mortality, andneonatal hypoglycaemia). This was due to design limitations in the included trials, small sample sizes in the trials contributing data, wide CIs crossing both the line of no effect and the line of appreciable benefit and/or harm, and often few events. We are therefore uncertain whether CSII or MDI improves outcomes for pregnant women with diabetes and their infants, and the results of further studies may differ substantially from those presented in this review.

AUTHORS' CONCLUSIONS

There is no evidence to support the use of one particular form of insulin administration over another for pregnant women with diabetes. There are only a small number of trials appropriate for meta-analysis, a small number of women included and questionable generalisability of the trial population.Pump technology has progressed since these trials were undertaken. Well-designed randomised trials are required to evaluate comparisons such as patch pumps against MDI and more conventional CSII against MDI. These trials should be adequately powered to assess the effect of interventions, and report the core set of outcomes used in Cochrane reviews of diabetes in pregnancy. Trials to assess the effects of pumps on birthweight and macrosomia rates are needed. It would be beneficial for future trials to undertake longer-term follow-up of participants and their infants, assess women's preferences, and conduct an economic evaluation.

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

OBJECTIVE

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

RESEARCH DESIGN AND METHODS

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

RESULTS

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

CONCLUSIONS

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

A Prepregnancy Care Program for Women With Diabetes: Effective and Cost Saving

CONTEXT

Only a minority of women with diabetes attend prepregnancy care service and the economic effects of providing this service are unclear.

OBJECTIVE

The objective of the study was to design, put into practice, and evaluate a regional prepregnancy care program for women with types 1 and 2 diabetes.

DESIGN

This was a prospective cohort and cost-analysis study.

SETTING

The study was conducted at antenatal centers along the Irish Atlantic Seaboard.

PARTICIPANTS

Four hundred fourteen women with type 1 or 2 diabetes participated in the study.

INTERVENTIONS

The intervention for the study was a newly developed prepregnancy care program.

MAIN OUTCOME MEASURES

The program was assessed for its effect on the risk of adverse pregnancy outcomes. The difference between program delivery cost and the excess cost of treating adverse outcomes in nonattendees was evaluated.

RESULTS

In total, 149 (36%) attended: this increased from 19% to 50% after increased recruitment measures in 2010. Attendees were more likely to take preconception folic acid (97.3% vs 57.7%, P < .001) and less likely to smoke (8.7% vs 16.6%, P = .03) or take potentially teratogenic medications at conception (0.7 vs 6.0, P = .008). Attendees had lower glycated hemoglobin levels throughout pregnancy (first trimester glycated hemoglobin 6.8% vs 7.7%, P < .001; third trimester glycated hemoglobin 6.1% vs 6.5%, P = .001), and their offspring had lower rates of serious adverse outcomes (2.4% vs 10.5%, P = .007). The adjusted difference in complication costs between those who received prepregnancy care vs usual antenatal care only is €2578.00. The average cost of prepregnancy care delivery is €449.00 per pregnancy.

CONCLUSIONS

This regional prepregnancy care program is clinically effective. The cost of program delivery is less than the excess cost of managing adverse pregnancy outcomes.

Using technology to advance type 1 diabetes care among women during the reproductive years and in pregnancy

The prevalence of diabetes is increasing globally. Technology to improve care among individuals with diabetes is constantly being developed. Women living with Type 1 Diabetes Mellitus (T1DM) have unique challenges affecting their glucose control relating to menstrual cycles, pregnancy, and menopause. The purpose of this review is to examine the literature related to the use of technology to help women with T1DM manage their diabetes during the reproductive years, pregnancy, and beyond. Continuous subcutaneous insulin infusion (CSII) therapy can provider equivalent or better glucose control when compared with multiple daily injections (MDI), with less hypoglycemia, diabetic ketoacidosis, and weight gain. The CSII therapy has features that could help improve glucose control over the menstrual cycle, menopause, and pregnancy, although the most studied of these stages is pregnancy. Continuous glucose monitoring (CGM) can be combined with any insulin delivery system (MDI or CSII) to provide data on glucose values every few minutes and show glucose trends over time. CGM introduction can highlight glucose variability for women with T1DM, may be beneficial during pregnancy, and can reduce hypoglycemia. Sensor-augmented pump therapy and hybrid artificial pancreas (closed-loop) systems are promising tools that improve outcomes among individuals with diabetes. The use of modern technology to improve glucose and metabolic control among menopausal women with diabetes has not been well studied. Internet and phone-based technologies are emerging as important tools that may help with diabetes self-care for women living with diabetes.

The management of type 1 and type 2 diabetes in pregnancy

Pregestational diabetes is a common medical complication of pregnancy and preconception planning is an essential component of care for affected women of childbearing age. Once pregnant, structured care in a multidisciplinary team setting is necessary to ensure optimal outcomes. Although significant progress has been made, these women and their offspring remain to have a significantly elevated risk of multiple adverse complications. Structured programmes using information technology and enabling access to novel technologies may facilitate our goal of ensuring an outcome closer to that of a pregnancy unaffected by diabetes.

Safety, efficacy and glucose turnover of reduced prandial boluses during closed-loop therapy in adolescents with type 1 diabetes: a randomized clinical trial

AIMS

To evaluate safety, efficacy and glucose turnover during closed-loop with meal announcement using reduced prandial insulin boluses in adolescents with type 1 diabetes (T1D).

METHODS

We conducted a randomized crossover study comparing closed-loop therapy with standard prandial insulin boluses versus closed-loop therapy with prandial boluses reduced by 25%. Eight adolescents with T1D [3 males; mean (standard deviation) age 15.9 (1.5) years, glycated haemoglobin 74 (17) mmol/mol; median (interquartile range) total daily dose 0.9 (0.7, 1.1) IU/kg/day] were studied on two 36-h-long visits. In random order, subjects received closed-loop therapy with either standard or reduced insulin boluses administered with main meals (50-80 g carbohydrates) but not with snacks (15-30 g carbohydrates). Stable-label tracer dilution methodology measured total glucose appearance (Ra_total) and glucose disposal (Rd).

RESULTS

The median (interquartile range) time spent in target (3.9-10 mmol/l) was similar between the two interventions [74 (66, 84)% vs 80 (65, 96)%; p = 0.87] as was time spent above 10 mmol/l [21.8 (16.3, 33.5)% vs 18.0 (4.1, 34.2)%; p = 0.87] and below 3.9 mmol/l [0 (0, 1.5)% vs 0 (0, 1.8)%; p = 0.88]. Mean plasma glucose was identical during the two interventions [8.4 (0.9) mmol/l; p = 0.98]. Hypoglycaemia occurred once 1.5 h post-meal during closed-loop therapy with standard bolus. Overall insulin delivery was lower with reduced prandial boluses [61.9 (55.2, 75.0) vs 72.5 (63.6, 80.3) IU; p = 0.01] and resulted in lower mean plasma insulin concentration [186 (171, 260) vs 252 (198, 336) pmol/l; p = 0.002]. Lower plasma insulin was also documented overnight [160 (136, 192) vs 191 (133, 252) pmol/l; p = 0.01, pooled nights]. Ra_total was similar [26.3 (21.9, 28.0) vs 25.4 (21.0, 29.2) µmol/kg/min; p = 0.19] during the two interventions as was Rd [25.8 (21.0, 26.9) vs 25.2 (21.2, 28.8) µmol/kg/min; p = 0.46].

CONCLUSIONS

A 25% reduction in prandial boluses during closed-loop therapy maintains similar glucose control in adolescents with T1D whilst lowering overall plasma insulin levels. It remains unclear whether closed-loop therapy with a 25% reduction in prandial boluses would prevent postprandial hypoglycaemia.

Artificial Pancreas Project at Cambridge 2013

The development and clinical testing of closed-loop systems (the artificial pancreas) is underpinned by advances in continuous glucose monitoring and benefits from concerted academic and industry collaborative efforts. This review describes the progress of the Artificial Pancreas Project at the University of Cambridge from 2006 to 2014. Initial studies under controlled laboratory conditions, designed to collect representative safety and performance data, were followed by short to medium free-living unsupervised outpatient studies demonstrating the safety and efficacy of closed-loop insulin delivery using a model predictive control algorithm. Accompanying investigations included assessment of the psychosocial impact and key factors affecting glucose control such as insulin kinetics and glucose absorption. Translation to other disease conditions such as critical illness and Type 2 diabetes took place. It is concluded that innovation of iteratively enhanced closed-loop systems will provide tangible means to improve outcomes and quality of life in people with Type 1 diabetes and their families in the next decade.

Closed loop insulin delivery in diabetes

The primary goal of type 1 diabetes treatment is attaining near-normal glucose values. This currently remains out of reach for most people with type 1 diabetes despite intensified insulin treatment in the form of insulin analogues, educational interventions, continuous glucose monitoring, and sensor augmented insulin pump. The main remaining problem is risk of hypoglycaemia, which cannot be sufficiently reduced in all patient groups. Additionally, patients' burn-out often develops with years of tedious day-to-day diabetes management, rendering available diabetes-related technology less efficient. Over the past 40 years, several attempts have been made towards computer-programmed insulin delivery in the form of closed loop, with faster developments especially in the past decade. Automated insulin delivery has reduced human error in glycaemic control and considerably lessened the burden of routine self-management. In this chapter, data from randomized controlled trials with closed-loop insulin delivery that included type 1 diabetes population are summarized, and an evidence-based vision for possible routine utilization of closed loop is provided.

Rapid model exploration for complex hierarchical data: application to pharmacokinetics of insulin aspart

We consider situations, which are common in medical statistics, where we have a number of sets of response data, from different individuals, say, potentially under different conditions. A parametric model is defined for each set of data, giving rise to a set of random effects. Our goal here is to efficiently explore a range of possible ‘population’ models for the random effects, to select the most appropriate model. The range of possible models is potentially vast, because the random effects may depend on observed covariates, and there may be multiple credible ways of partitioning their variability. Here, we consider pharmacokinetic (PK) data on insulin aspart, a fast acting insulin analogue used in the treatment of diabetes. PK models are typically nonlinear (in their parameters), often complex and sometimes only available as a set of differential equations, with no closed‐form solution. Fitting such a model for just a single individual can be a challenging task. Fitting a joint model for all individuals can be even harder, even without the complication of an overarching model selection objective. We describe a two‐stage approach that decouples the population model for the random effects from the PK model applied to the response data but nevertheless fits the full, joint, hierarchical model, accounting fully for uncertainty. This allows us to repeatedly reuse results from a single analysis of the response data to explore various population models for the random effects. This greatly expedites not only model exploration but also cross‐validation for the purposes of model criticism. © 2015 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.