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Objective: To describe glucose metrics in a high-risk population of women with type 2 diabetes (T2DM) in pregnancy and to explore the associations with neonatal outcomes. Research Design and Methods: Prospective observational study of 57 women. Continuous glucose monitoring (CGM) trajectories were determined from metrics collected in early and late gestation using the first and last two (mean 16 and 35) weeks of Freestyle Libre data. Logistic regression was used to examine associations of CGM metrics with neonatal hypoglycemia (glucose <2.6 mmol/L requiring intravenous dextrose) and large for gestational age (LGA) (>90th percentile for gestational age and sex). Pregnancy-specific target glucose range was 3.5-7.8 mmol/L (63-140 mg/dL). Results: Forty-one women used CGM for 15 weeks (mean age 33 years, 73% Aboriginal or Torres Strait Islander, 32% living remotely). There was limited change in average metrics from early to late pregnancy. For the subgroup with sensor use >50% ( n  = 29), mean time in range (TIR) increased by 9%, time above range reduced by 12%, average glucose reduced by 1 mmol/L, and time below range increased by 3%. Neonatal hypoglycemia was associated with most CGM metrics, HbA1c and CGM targets, particularly those from late pregnancy. LGA was associated with hyperglycemic metrics from early pregnancy. Each 1% increase TIR was associated with a 4%-5% reduction in risk of neonatal complications. Conclusion: In this high-risk group of women with T2DM, CGM metrics only improved during pregnancy in those with greater sensor use and were associated with LGA in early pregnancy and neonatal hypoglycemia throughout. Culturally appropriate health care strategies are critical for successful use of CGM technology.

Introduction: Recent high-profile calls have emphasized that women's experiences should be considered in maternity care provisioning. We explored women's experiences of using closed-loop during type 1 diabetes (T1D) pregnancy to inform decision-making about antenatal rollout and guidance and support given to future users. Methods: We interviewed 23 closed-loop participants in the Automated insulin Delivery Among Pregnant women with T1D (AiDAPT) trial after randomization to closed-loop and ∼20 weeks later. Data were analyzed thematically. Results: Women described how closed-loop lessened the physical and mental demands of diabetes management, enabling them to feel more normal and sleep better. By virtue of spending increased time-in-range, women also worried less about risks to their baby and being judged negatively by health care professionals. Most noted that intensive input and support during early pregnancy had been crucial to adjusting to, and developing confidence in, the technology. Women emphasized that attaining pregnancy glucose targets still required ongoing effort from themselves and the health care team. Women described needing education to help them determine when, and how, to intervene and when to allow the closed-loop to operate without interference. All women reported more enjoyable pregnancy experiences as a result of using closed-loop; some also noted being able to remain longer in paid employment. Conclusions: Study findings endorse closed-loop use in T1D pregnancy by highlighting how the technology can facilitate positive pregnancy experiences. To realize fully the benefits of closed-loop, pregnant women would benefit from initial intensive oversight and support together with closed-loop specific education and training. Clinical Trial Registration number: NCT04938557.

Aims: To explore healthcare professionals' views about the training and support needed to rollout closed-loop technology to pregnant women with type 1 diabetes. Methods: We interviewed ( n  = 19) healthcare professionals who supported pregnant women using CamAPS FX closed-loop during the Automated insulin Delivery Amongst Pregnant women with Type 1 diabetes (AiDAPT) trial. Data were analyzed descriptively. An online workshop involving ( n  = 15) trial team members was used to inform recommendations. Ethics approvals were obtained in conjunction with those for the wider trial. Results: Interviewees expressed enthusiasm for a national rollout of closed-loop, but anticipated various challenges, some specific to use during pregnancy. These included variations in insulin pump and continuous glucose monitoring expertise and difficulties embedding and retaining key skills, due to the relatively small numbers of pregnant women using closed-loop. Inexperienced staff also highlighted difficulties interpreting data downloads. To support rollout, interviewees recommended providing expert initial advice training, delivered by device manufacturers together with online training resources and specific checklists for different systems. They also highlighted a need for 24 h technical support, especially when supporting technology naive women after first transitioning onto closed-loop in early pregnancy. They further recommended providing case-based meetings and mentorship for inexperienced colleagues, including support interpreting data downloads. Interviewees were optimistic that if healthcare professionals received training and support, their long-term workloads could be reduced because closed-loop lessened women's need for glycemic management input, especially in later pregnancy. Conclusions: Interviewees identified challenges and opportunities to rolling-out closed-loop and provided practical suggestions to upskill inexperienced staff supporting pregnant women using closed-loop. A key priority will be to determine how best to develop mentorship services to support inexperienced staff delivering closed-loop. Clinical Trials Registration: NCT04938557.

The CONCEPTT trial compared real-time Continuous Glucose Monitoring (RT-CGM) to capillary glucose monitoring in pregnant women with type 1 diabetes. We analyzed CGM and glycated hemoglobin (HbA 1c ) measures in first ( n  = 221), second ( n  = 197), and third ( n  = 172) trimesters, aiming to examine target glucose attainment and associations with pregnancy outcomes. CGM targets were Time-in-range (TIR) > 70%, Time-above-range (TAR) <25%, and Time-below-range (TBR) < 4%, and HbA 1c targets < 6.5% (National Institute for Health and Care Excellence [NICE]) and HbA 1c < 6.0% in second and third trimesters (American Diabetes Association [ADA]). TIR/TAR/TBR targets were achieved by 7.7/14.5/30.3% participants in first, 10.2/14.2/52.8% in second, and 35.5/37.2/52.9% in third trimesters. CGM target attainment was low but increased during pregnancy and with RT-CGM use. In the adjusted analyses, achieving TBR target was associated with a higher risk of pre-eclampsia and neonatal hypoglycemia. ADA HbA 1c target attainment was low and unchanged during pregnancy (23.5/27.9/23.8%) but increased with RT-CGM use. In the adjusted analyses, HbA 1c target attainment was associated with a lower risk of preterm birth, large-for-gestational age and neonatal hypoglycemia. We conclude that CONCEPTT trial participants had a low rate of CGM and of HbA 1c target attainment. Attainment of CGM and NICE HbA 1c targets increased throughout gestation and all targets (both NICE/ADA HbA 1c and CGM) were more likely to be achieved by RT-CGM users, at 34 weeks' gestation. ADA HbA 1c target achievement was independently associated with better perinatal outcomes, while the independent association of TBR target achievement with increased risk warrants further study. ClinicalTrials.gov Registration Identifier NCT01788527.

In recent years, continuous glucose monitoring (CGM) has become increasingly available with the introduction of devices that are specifically approved for use during pregnancy. Evidence in the form of randomized-controlled trials and cohort studies continues to build support for the use of CGM during pregnancy to improve measures of maternal glycemia as well as obstetric and neonatal outcomes. Based on data from the CGM in pregnant women with type 1 diabetes (CONCEPTT) trial alongside a Swedish cohort study of real-world outcomes of pregnant women with type 1 diabetes, the UK National Institute for Health and Clinical Excellence (NICE) guidelines now recommend that real-time CGM be offered to all pregnant women with type 1 diabetes. Based on these guidelines, all pregnant individuals in the United Kingdom with type 1 diabetes will receive government-funded real-time CGM for a 12-month duration. These guidelines are a game-changer and will continue to facilitate more widespread access to CGM use in the United Kingdom and beyond. This review describes the role of CGM in the management of diabetes in pregnancy, discusses contemporary maternal glucose levels and their relationship with outcomes in diabetes pregnancies, and examines the high-quality, randomized-controlled trial and the real-world clinical data evaluating the impact of CGM use.

Background: Pregnant women with diabetes are identified as being more vulnerable to the severe effects of COVID-19 and advised to stringently follow social distancing measures. Here, we review the management of diabetes in pregnancy before and during the lockdown. Methods: Majority of antenatal diabetes and obstetric visits are provided remotely, with pregnant women attending hospital clinics only for essential ultrasound scans and labor and delivery. Online resources for supporting women planning pregnancy and for self-management of pregnant women with type 1 diabetes (T1D) using intermittent or continuous glucose monitoring are provided. Retinal screening procedures, intrapartum care, and the varying impact of lockdown on maternal glycemic control are considered. Alternative screening procedures for diagnosing hyperglycemia during pregnancy and gestational diabetes mellitus (GDM) are discussed. Case histories describe the remote initiation of insulin pump therapy and automated insulin delivery in T1D pregnancy. Results: Initial feedback suggests that video consultations are well received and that the patient experiences for women requiring face-to-face visits are greatly improved. As the pandemic eases, formal evaluation of remote models of diabetes education and technology implementation, including women's views, will be important. Conclusions: Research and audit activities will resume and we will find new ways for supporting pregnant women with diabetes to choose their preferred glucose monitoring and insulin delivery.

Background: Clinicians mediate access to closed-loop technology for people with diabetes. Consequently, their attitudes regarding appropriate levels of closed-loop usage will play a key role in future adoption processes. This study aimed to explore clinician attitudes toward future mainstream closed-loop usage in England. Materials and Methods: We conducted 36 semistructured interviews with clinicians from a range of professional backgrounds working in outpatient clinics in England. Interview topics included clinicians' views on future pathways for closed-loop use and attitudes toward the predictability of users' technology experiences, a key factor in eligibility decision making. We analyzed transcripts using thematic and framework approaches. Results: Clinicians exhibited a range of opinions regarding future eligibility for closed-loop technology. We identified three key strands of clinician opinion, envisaging (1) tighter access for closed loop ( n  = 10), citing funding challenges and issues arising from user overconfidence or negative technology attitudes; (2) similar access to closed loop as for current diabetes technologies ( n  = 15), on the grounds that future funding and access pathways will be similar to current arrangements; and (3) wider access for closed-loop technologies ( n  = 9), given the potential for significant and widespread benefits arising from closed-loop usage, including downstream cost savings alongside improved glycemic control. Conclusions: Clinicians expressed a range of opinions encompassing continuity with current diabetes technologies, while others envisaged either tighter or more liberal access for closed-loop systems. To optimize technology adoption and equitable uptake, future implementation pathways should consider clinician attitudes toward technology use and access.

Aim: To describe the continuous glucose monitoring (CGM) profiles of type 1 diabetes (T1D) offspring in the early neonatal period and its association with maternal intrapartum glucose control., Methods: A prospective observational study of T1D pregnant women and their neonatal offspring. Women had a CGM sensor inserted 2-3 days before delivery. Infants had a masked CGM sensor inserted as soon as possible after delivery. Maternal glycemic outcomes were time-in-target (70-140 mg/dL [3.9-7.8 mmol/L]), hyperglycemia >140 mg/dL (7.8 mmol/L), and mean CGM glucose during the 24 h preceding delivery. Neonatal outcomes included lowest recorded blood glucose concentration, and CGM measures (glucose <47 mg/dL [2.6 mmol/L], time-in-target (47-144 mg/dL [2.6-8.0 mmol/L]), glucose standard deviation [SD]) during the first 72 h of life., Results: Data were available for 16 mother-infant pairs. Mothers had a mean age (SD) 32.3 (4.3) years, T1D duration 17.6 (6.8) years, first antenatal glycated hemoglobin 7.4 (0.8)% (57 [8.5] mmol/mol). In the 24 h preceding delivery, mothers spent mean (SD) 72 (20)% time-in-target (70-140 mg/dL [3.9-7.8 mmol/L]), 19 (15)% time >140 mg/dL (7.8 mmol/L), and 9 (9)% time <70 mg/dL (3.9 mmol/L) with mean (SD) CGM glucose 113 (9) mg/dL (6.3 [0.7] mmol/L). Fifteen infants (93.8%) had ≥1 blood glucose concentration <47 mg/dL (2.6 mmol/L), and five had ≥1 blood glucose concentration <18 mg/dL (1.0 mmol/L). The mean infant CGM glucose on days 1, 2, and 3 of life was 63 (14), 67 (13), 76 (11) mg/dL (3.5 [0.8], 3.7 [0.7], and 4.2 [0.6] mmol/L). Four infants (25%) spent >50% time with CGM glucose levels <47 mg/dL (2.6 mmol/L) on day 1., Conclusions: CGM detected widespread neonatal hypoglycemia, even among mothers with good intrapartum glucose control.

Tight glucose control during labor and delivery is recommended for pregnant women with type 1 diabetes. This can be challenging to achieve using the current treatment modalities. The automated nature of closed loop and its ability to adapt to real-time glucose levels make it well suited for use during labor, delivery, and the immediate postpartum period. We report observational data of participants from two randomized crossover trials who chose to continue using closed loop during labor, delivery, and postpartum. Labor was defined as the 24 h before delivery and postpartum as the 48 h after delivery. The glucose target range during pregnancy was 3.5-7.8 mmol/L (63-140 mg/dL) and 3.9-10 mmol/L (70-180 mg/dL) after delivery. Twenty-seven (84.4%) of the potential 32 trial participants used closed loop through labor, delivery, and postpartum. Use of closed loop was associated with 82.0% (interquartile range [IQR] 49.3, 93.0) time-in-target range during labor and delivery and a mean glucose of 6.9 ± 1.4 mmol/L (124 ± 25 mg/dL). Closed loop performed well throughout vaginal, elective, and emergency cesarean section deliveries. Postpartum, women spent 83.3% (IQR 75.2, 94.6) time-in-target range (3.9-10.0 mmol/L [70-180 mg/dL]), with a mean glucose of 7.2 ± 1.4 mmol/L (130 ± 25 mg/dL). There was no difference in maternal glucose concentration between mothers of infants with and without neonatal hypoglycemia (6.9 ± 1.6 mmol/L and 6.8 ± 1.1 mmol/L [124 ± 29 mg/dL and 122 ± 20 mg/dL] respectively; P = 0.84). Automated closed-loop insulin delivery is feasible during hospital admissions for labor, delivery, and postpartum. Larger scale studies are needed to evaluate its efficacy compared with current clinical approaches as well as understand how women and healthcare providers will adopt this technology.

Background: Performance of continuous glucose monitors (CGMs) may be lower when glucose levels are changing rapidly, such as occurs during physical activity. Our aim was to evaluate accuracy of a current-generation CGM during moderate-intensity exercise in type 1 diabetes (T1D) pregnancy., Subjects and Methods: As part of a study of 24-h closed-loop insulin delivery in 12 women with T1D (disease duration, 17.6 years; glycosylated hemoglobin, 6.4%) during pregnancy (gestation, 21 weeks), we evaluated the Freestyle Navigator(®) sensor (Abbott Diabetes Care, Alameda, CA) during afternoon (15:00-18:00 h) and morning (09:30-12:30 h) exercise (55 min of brisk walking on a treadmill followed by a 2-h recovery), compared with sedentary conditions (18:00-09:00 h). Plasma (reference) glucose, measured at regular 15-30-min intervals with the YSI Ltd. (Fleet, United Kingdom) model YSI 2300 analyzer, was used to assess CGM performance., Results: Sensor accuracy, as indicated by the larger relative absolute difference (RAD) between paired sensor and reference glucose values, was lower during exercise compared with rest (median RAD, 11.8% vs. 18.4%; P<0.001). These differences remained significant when correcting for plasma glucose relative rate of change (P<0.001). Analysis by glucose range showed lower accuracy during hypoglycemia for both sedentary (median RAD, 24.4%) and exercise (median RAD, 32.1%) conditions. Using Clarke error grid analysis, 96% of CGM values were clinically safe under resting conditions compared with only 87% during exercise., Conclusions: Compared with sedentary conditions, accuracy of the Freestyle Navigator CGM was lower during moderate-intensity exercise in pregnant women with T1D. This difference was particularly marked in hypoglycemia and could not be solely explained by the glucose rate of change associated with physical activity.

Objective: This study evaluated the accuracy and large inaccuracy of the Freestyle Navigator (FSN) (Abbott Diabetes Care, Alameda, CA) and Dexcom SEVEN PLUS (DSP) (Dexcom, Inc., San Diego, CA) continuous glucose monitoring (CGM) systems during closed-loop studies., Research Design and Methods: Paired CGM and plasma glucose values (7,182 data pairs) were collected, every 15-60 min, from 32 adults (36.2±9.3 years) and 20 adolescents (15.3±1.5 years) with type 1 diabetes who participated in closed-loop studies. Levels 1, 2, and 3 of large sensor error with increasing severity were defined according to absolute relative deviation greater than or equal to ±40%, ±50%, and ±60% at a reference glucose level of ≥6 mmol/L or absolute deviation greater than or equal to ±2.4 mmol/L,±3.0 mmol/L, and ±3.6 mmol/L at a reference glucose level of <6 mmol/L., Results: Median absolute relative deviation was 9.9% for FSN and 12.6% for DSP. Proportions of data points in Zones A and B of Clarke error grid analysis were similar (96.4% for FSN vs. 97.8% for DSP). Large sensor over-reading, which increases risk of insulin over-delivery and hypoglycemia, occurred two- to threefold more frequently with DSP than FSN (once every 2.5, 4.6, and 10.7 days of FSN use vs. 1.2, 2.0, and 3.7 days of DSP use for Level 1-3 errors, respectively). At levels 2 and 3, large sensor errors lasting 1 h or longer were absent with FSN but persisted with DSP., Conclusions: FSN and DSP differ substantially in the frequency and duration of large inaccuracy despite only modest differences in conventional measures of numerical and clinical accuracy. Further evaluations are required to confirm that FSN is more suitable for integration into closed-loop delivery systems.