Automated Insulin Delivery in Women with Pregnancy Complicated by Type 1 Diabetes.

BACKGROUND: Hybrid closed-loop insulin therapy has shown promise for management of type 1 diabetes during pregnancy; however, its efficacy is unclear. METHODS: In this multicenter, controlled trial, we randomly assigned pregnant women with type 1 diabetes and a glycated hemoglobin level of at least 6.5% at nine sites in the United Kingdom to receive standard insulin therapy or hybrid closed-loop therapy, with both groups using continuous glucose monitoring. The primary outcome was the percentage of time in the pregnancy-specific target glucose range (63 to 140 mg per deciliter [3.5 to 7.8 mmol per liter]) as measured by continuous glucose monitoring from 16 weeks' gestation until delivery. Analyses were performed according to the intention-to-treat principle. Key secondary outcomes were the percentage of time spent in a hyperglycemic state (glucose level >140 mg per deciliter), overnight time in the target range, the glycated hemoglobin level, and safety events. RESULTS: A total of 124 participants with a mean (±SD) age of 31.1±5.3 years and a mean baseline glycated hemoglobin level of 7.7±1.2% underwent randomization. The mean percentage of time that the maternal glucose level was in the target range was 68.2±10.5% in the closed-loop group and 55.6±12.5% in the standard-care group (mean adjusted difference, 10.5 percentage points; 95% confidence interval [CI], 7.0 to 14.0; P<0.001). Results for the secondary outcomes were consistent with those of the primary outcome; participants in the closed-loop group spent less time in a hyperglycemic state than those in the standard-care group (difference, -10.2 percentage points; 95% CI, -13.8 to -6.6); had more overnight time in the target range (difference, 12.3 percentage points; 95% CI, 8.3 to 16.2), and had lower glycated hemoglobin levels (difference, -0.31 percentage points; 95% CI, -0.50 to -0.12). Little time was spent in a hypoglycemic state. No unanticipated safety problems associated with the use of closed-loop therapy during pregnancy occurred (6 instances of severe hypoglycemia, vs. 5 in the standard-care group; 1 instance of diabetic ketoacidosis in each group; and 12 device-related adverse events in the closed-loop group, 7 related to closed-loop therapy). CONCLUSIONS: Hybrid closed-loop therapy significantly improved maternal glycemic control during pregnancy complicated by type 1 diabetes. (Funded by the Efficacy and Mechanism Evaluation Program; AiDAPT ISRCTN Registry number, ISRCTN56898625.).

Technology advances in diabetes pregnancy: right technology, right person, right time.

This review outlines some of the extraordinary recent advances in diabetes technology, which are transforming the management of type 1 diabetes before, during and after pregnancy. It highlights recent improvements associated with use of continuous glucose monitoring (CGM) but acknowledges that neither CGM nor insulin pump therapy are adequate for achieving the pregnancy glucose targets. Furthermore, even hybrid closed-loop (HCL) systems that are clinically effective outside of pregnancy may not confer additional benefits throughout pregnancy. To date, there is only one HCL system, the CamAPS FX, with a strong evidence base for use during pregnancy, suggesting that the pregnancy benefits are HCL system specific. This is in stark contrast to HCL system use outside of pregnancy, where benefits are HCL category specific. The CamAPS FX HCL system has a rapidly adaptive algorithm and lower glucose targets with benefits across all maternal glucose categories, meaning that it is applicable for all women with type 1 diabetes, before and during pregnancy. For women of reproductive years living with type 2 diabetes, the relative merits of using non-insulin pharmacotherapies vs diabetes technology (dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists and sodium-glucose cotransporter 2 inhibitors) are unknown. Despite the urgent unmet need and potential benefits, studies of pharmacotherapy and technology use are extremely limited in pregnant women with type 2 diabetes.

Glycaemic patterns during breastfeeding with postpartum use of closed-loop insulin delivery in women with type 1 diabetes.

AIMS/HYPOTHESIS: This study aimed to describe the relationship between breastfeeding episodes and maternal glucose levels, and to assess whether this differs with closed-loop vs open-loop (sensor-augmented pump) insulin therapy. METHODS: Infant-feeding diaries were collected at 6 weeks, 12 weeks and 24 weeks postpartum in a trial of postpartum closed-loop use in 18 women with type 1 diabetes. Continuous glucose monitoring (CGM) data were used to identify maternal glucose patterns within the 3 h of breastfeeding episodes. Generalised mixed models adjusted for breastfeeding episodes in the same woman, repeat breastfeeding episodes, carbohydrate intake, infant age at time of feeding and early pregnancy HbA1c. This was a secondary analysis of data collected during a randomised trial (ClinicalTrials.gov registration no. NCT04420728). RESULTS: CGM glucose remained above 3.9 mmol/l in the 3 h post-breastfeeding for 93% (397/427) of breastfeeding episodes. There was an overall decrease in glucose at nighttime within 3 h of breastfeeding (1.1 mmol l-1 h-1 decrease on average; p=0.009). A decrease in nighttime glucose was observed with open-loop therapy (1.2 ± 0.5 mmol/l) but was blunted with closed-loop therapy (0.4 ± 0.3 mmol/l; p<0.01, open-loop vs closed-loop). CONCLUSIONS/INTERPRETATION: There is a small decrease in glucose after nighttime breastfeeding that usually does not result in maternal hypoglycaemia; this appears to be blunted with the use of closed-loop therapy.

Impact of COVID-19 on gestational diabetes pregnancy outcomes in the UK: A multicentre retrospective cohort study.

OBJECTIVE: To determine the impact of implementing emergency care pathway(s) for screening, diagnosing and managing women with gestational diabetes (GDM) during COVID-19. DESIGN: Retrospective multicentre cohort. SETTING: Nine National Health Service (NHS) Hospital Trusts/Health boards in England and Scotland. POPULATION: 4915 women with GDM pre-pandemic (1 April 2018 to 31 March 2020), and 3467 women with GDM during the pandemic (1 May 2020 to 31 March 2021). METHODS: We examined clinical outcomes for women with GDM prior to and during the pandemic following changes in screening methods, diagnostic testing, glucose thresholds and introduction of virtual care for monitoring of antenatal glycaemia. MAIN OUTCOME MEASURES: Intervention at birth, perinatal mortality, large-for-gestational-age infants and neonatal unit admission. RESULTS: The new diagnostic criteria more often identified GDM women who were multiparous, had higher body mass index (BMI) and greater deprivation, and less frequently had previous GDM (all p < 0.05). During COVID, these women had no differences in the key outcome measures. Of the women, 3% were identified with pre-existing diabetes at antenatal booking. Where OGTT continued during COVID, but virtual care was introduced, outcomes were also similar pre- and during the pandemic. CONCLUSIONS: Using HbA1c and fasting glucose identified a higher risk GDM population during the pandemic but this had minimal impact on pregnancy outcomes. The high prevalence of undiagnosed pre-existing diabetes suggests that women with GDM risk factors should be offered HbA1c screening in early pregnancy.

Metabolomic insights into maternal and neonatal complications in pregnancies affected by type 1 diabetes.

AIMS/HYPOTHESIS: Type 1 diabetes in pregnancy is associated with suboptimal pregnancy outcomes, attributed to maternal hyperglycaemia and offspring hyperinsulinism (quantifiable by cord blood C-peptide). We assessed metabolomic patterns associated with risk factors (maternal hyperglycaemia, diet, BMI, weight gain) and perinatal complications (pre-eclampsia, large for gestational age [LGA], neonatal hypoglycaemia, hyperinsulinism) in the Continuous Glucose Monitoring in Women with Type 1 Diabetes in Pregnancy Trial (CONCEPTT). METHODS: A total of 174 CONCEPTT participants gave ≥1 non-fasting serum sample for the biorepository at 12 gestational weeks (147 women), 24 weeks (167 women) and 34 weeks (160 women) with cord blood from 93 infants. Results from untargeted metabolite analysis (ultrahigh performance LC-MS) are presented as adjusted logistic/linear regression of maternal and cord blood metabolites, risk factors and perinatal complications using a modified Bonferroni limit of significance for dependent variables. RESULTS: Maternal continuous glucose monitoring time-above-range (but not BMI or excessive gestational weight gain) was associated with increased triacylglycerols in maternal blood and increased carnitines in cord blood. LGA, adiposity, neonatal hypoglycaemia and offspring hyperinsulinism showed distinct metabolite profiles. LGA was associated with increased carnitines, steroid hormones and lipid metabolites, predominantly in the third trimester. However, neonatal hypoglycaemia and offspring hyperinsulinism were both associated with metabolite changes from the first trimester, featuring triacylglycerols or dietary phenols. Pre-eclampsia was associated with increased abundance of phosphatidylethanolamines, a membrane phospholipid, at 24 weeks. CONCLUSIONS/INTERPRETATION: Altered lipid metabolism is a key pathophysiological feature of type 1 diabetes pregnancy. New strategies for optimising maternal diet and insulin dosing from the first trimester are needed to improve pregnancy outcomes in type 1 diabetes.

Applications of continuous glucose monitoring across settings and populations: Report from the 23rd Hong Kong diabetes and cardiovascular risk factors-East meets west symposium.

Continuous glucose monitoring (CGM) is now an integral part of glycaemic management in people with type 1 diabetes and those with insulin-treated type 2 diabetes. Immediate access to information on CGM glucose levels and trends helps to inform food choices, titration and timing of insulin doses and prompts corrective actions in the event of impending hypo- or hyperglycaemia. Although glycated haemoglobin (HbA1c) remains an important measure of the average of glucose, CGM metrics including time-in-range (TIR) and other metrics on glycaemic variability and hypoglycaemia are strongly endorsed by people with diabetes as impacting their daily lives. There is growing consensus on definitions and targets of CGM metrics with an increasing number of studies demonstrating correlations between CGM metrics and incident complications of diabetes. Implementation of new technologies needs to take into consideration factors such as cost-effectiveness, accessibility as well as acceptability of the person with diabetes and healthcare professional. The United Kingdom is one of the few countries that have developed clinical pathways for integrating CGM into the routine care of people with type 1 diabetes. Besides type 1 diabetes, special groups such as people with impaired kidney function and women during pregnancy may derive additional benefits from CGM.

Pre-pregnancy health of women with pre-existing diabetes or previous gestational diabetes: Analysis of pregnancy risk factors and behavioural data from a digital tool.

AIMS: To examine health behaviours and risk factors in women with pre-existing diabetes or previous gestational diabetes mellitus who are planning pregnancy. METHODS: Health behaviour, risk factor and demographic data obtained from a digital pregnancy planning advisory tool (Tommy's charity UK) were analysed. Descriptive statistical analysis was performed, stratified by diabetes type. RESULTS: Data from 84,359 women, including 668 with type 1 diabetes, 707 with type 2 diabetes and 1785 with previous gestational diabetes obtained over a 12-month period (September 2019-September 2020) were analysed. 65%, 95%CI (61,68%) of women with type 2 diabetes and 46%, 95%CI (43,48%) with previous gestational diabetes were obese (BMI ≥30 kg/m2 ), compared with 26%, 95%CI (26,26%) without diabetes. Use of folic acid supplements was low; 41%, 95%CI (40,41%) of women without diabetes and 42%, 95%CI (40,45%) with previous gestational diabetes reported taking folic acid (any dose) while 47%, 95%CI (43.50%) women with type 1 diabetes and 44%, 95%CI (40,47%) women with type 2 diabetes respectively reported taking the recommended dose (5 mg). More women with type 1 diabetes and type 2 diabetes reported smoking (20%, 95%CI [17,23%] and 23%, 95%CI [20,26%] respectively) and taking illicit/recreational drugs (7%, 95%CI [6,10%] and 9%, 95% CI [7,11%]) compared to women without diabetes (smoking 17%, 95% CI [16,17%], drug use 5%, 95%CI [5,5%]). Alcohol consumption, low levels of physical activity and of fruit and vegetable intake were also evident. CONCLUSIONS: This study highlights the potential of online pregnancy planning advisory tools to reach high-risk women and emphasises the need to improve pre-pregnancy care for women with pre-existing diabetes and previous gestational diabetes, many of whom are actively seeking advice. It is also the first to describe pre-pregnancy health behaviours in women with previous gestational diabetes.

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.

Interventions to enhance pre-pregnancy care for women with type 2 diabetes: A systematic review of the literature.

AIMS: The aim of the study was to examine the content and impact of interventions that have been used to increase the uptake of pre-pregnancy care for women with type 2 diabetes, and their impact on maternal and fetal outcomes. METHODS: A systematic search of multiple databases was conducted in November 2021, and updated July 2022, to identify studies assessing interventions to enhance pre-pregnancy care for women with type 2 diabetes. Over 10% of articles were screened by two reviewers at title and abstract phase, after which all selected full-text articles were screened by two reviewers. Quality assessment was conducted using the Critical Appraisal Skills Programme checklist for cohort studies. Meta-analysis was not possible due to study heterogeneity; therefore, narrative synthesis was conducted. RESULTS: Four eligible cohort studies were identified. The conclusions able to be drawn by this review were limited as women with type 2 diabetes (n = 800) were in the minority in all four studies (35%-40%) and none of the interventions were exclusively tailored for them. The uptake of pre-pregnancy care was lower in women with type 2 diabetes (8%-10%) compared with other participant groups in the studies. Pregnancy preparation indicators generally improved among all groups exposed to pre-pregnancy care, with varying impact on pregnancy outcomes. CONCLUSIONS: This review demonstrates that previous interventions have had a limited impact on pre-pregnancy care uptake in women with type 2 diabetes. Future studies should focus on tailored interventions for improving pre-pregnancy care for women with type 2 diabetes, particularly those from ethnic minorities and living in poorer communities.

MAGIC (maternal glucose in pregnancy) understanding the glycemic profile of pregnancy, intensive CGM glucose profiling and its relationship to fetal growth: an observational study protocol.

BACKGROUND: Continuous glucose monitoring (CGM) provides the most objective method of assessing glucose in daily life. Although there have been small, short-term physiologic studies of glucose metabolism in 'healthy' pregnant women a comprehensive, longitudinal description of changes in glucose over the course of pregnancy and how glucose dysregulation earlier in pregnancy relates to traditional third trimester screening for gestational diabetes, fetal growth and pregnancy outcomes is lacking. This study aims to characterise longitudinal changes in glycemia across gestation using CGM, in order to understand the evolution of dysglycemia and its relationship to fetal growth. METHOD/DESIGN: A multi-centre, prospective, observational, cohort study of 500 healthy pregnant women, recruited in the first trimester of pregnancy. Masked CGM will be performed for a 14-day period on five occasions across pregnancy at ~ 10-12, 18-20, 26-28, 34-36 weeks gestation and postnatally. Routinely collected anthropometric and sociodemographic information will be recorded at each visit including: weight, height, blood pressure, current medication. Age, parity, ethnicity, smoking will be recorded. Blood samples will be taken at each visit for HbA1c and a sample stored. Details on fetal growth from ultrasound scans and the OGTT results will be recorded. Maternal and neonatal outcomes will be collected. CGM glucose profiling is the exposure of interest, and will be performed using standard summary statistics, functional data analysis and glucotyping. The primary maternal outcome is clinical diagnosis of GDM. The primary neonatal outcome is large for gestational age (LGA) (> 90th centile defined by customised birthweight centile). The relationship of glucose to key secondary maternal and neonatal outcomes will be explored. DISCUSSION: This study will ascertain the relationship of maternal dysglycemia to fetal growth and outcomes. It will explore whether CGM glucose profiling can detect GDM before the OGTT; or indeed whether CGM glucose profiling may be more useful than the OGTT at detecting LGA and other perinatal outcomes. TRIAL REGISTRATION: ISRCTN 15,706,303 https://www.isrctn.com/ISRCTN15706303 Registration date: 13th March 2023.

Roadmap to the Effective Use of Continuous Glucose Monitoring in Pregnancy.

The landscape for managing type 1 diabetes during pregnancy has been transformed by increasing use of continuous glucose monitoring (CGM). Women are aiming for pregnancy-specific glucose targets or 70% time in range for pregnancy (TIRp; 63-140 mg/dL) as soon as possible, knowing that every extra 5% TIRp has benefits for reducing the risks of complications in their babies. Ongoing monitoring of maternal A1C (at pregnancy confirmation and at 20, 28, and 36 weeks' gestation) remains useful. Intensification of glycemic management and instruction in using CGM (if not already used) is recommended for individuals with an A1C >6.0% after 20 weeks. A better understanding of CGM-documented glycemic changes throughout pregnancy is needed to inform future management of gestational diabetes and pregnancy in people with type 2 diabetes. Research regarding overcoming barriers to CGM use and optimal TIRp targets for pregnant individuals with type 2 diabetes from diverse racial/ethnic groups is urgently needed.

Impaired awareness of hypoglycaemia in women with type 1 diabetes in pregnancy: Hypoglycaemia fear, glycaemic and pregnancy outcomes.

AIMS: To examine maternal fear of hypoglycaemia, glycaemia and pregnancy outcomes in women with impaired and normal awareness of hypoglycaemia. METHODS: A pre-planned sub-study of 214 pregnant women with type 1 diabetes who participated in the CONCEPTT trial. Participants completed hypoglycaemia fear surveys (HFS-II) at baseline. Logistic regression and Poisson regression analyses were used to obtain an adjusted estimate for the rate ratio relating awareness to the number of severe hypoglycaemic episodes, and for several neonatal outcomes in relation to the total HFS-II score. The role of continuous glucose monitoring (CGM) use was examined. RESULTS: Overall, 30% of participants reported impaired awareness of hypoglycaemia (n = 64). Women with impaired awareness of hypoglycaemia had more episodes of severe hypoglycaemia (mean 0.44 vs. 0.08, p < 0.001) (12-34 weeks gestation) and scored higher on the HFS-II scale (43.7 vs. 36.0, p 0.008), indicating more fear of hypoglycaemia. They spent more time below range (CGM <3.5 mmol/L) and exhibited more glycaemic variability at 12 weeks gestation. Higher overall HFS-II scores were associated with a higher risk of maternal severe hypoglycaemia episodes (Rate Ratio 1.78, 95% CI 1.39-2.27). Women with impaired awareness of hypoglycaemia had less maternal weight gain but there were no differences in neonatal outcomes between women with impaired awareness of hypoglycaemia and normal hypoglycaemia awareness. Higher HFS-II scores were associated with more nephropathy (Odds Ratio 1.91, 95% CI 1.06-3.4). CGM use after 12 weeks was not associated with the number of episodes of severe hypoglycaemia (RR 0.75, 95% CI 0.49-1.15; p = 0.18). CONCLUSIONS: In pregnant women with type 1 diabetes, impaired awareness of hypoglycaemia is associated with more maternal severe hypoglycaemia episodes and more fear of hypoglycaemia. Having impaired awareness of hypoglycaemia and/or fear of hypoglycaemia should alert clinicians to this increased risk. Reassuringly, there was no increase in adverse neonatal outcomes.

Managing hyperglycaemia during antenatal steroid administration, labour and birth in pregnant women with diabetes - an updated guideline from the Joint British Diabetes Society for Inpatient Care.

This article summarises the Joint British Diabetes Societies for Inpatient Care guidelines on the management of glycaemia in pregnant women with diabetes on obstetric wards and delivery units, Joint British Diabetes Societies (JBDS) for Inpatient Care Group, ABCD (Diabetes Care) Ltd. The updated guideline offers two approaches - the traditional approach with tight glycaemic targets (4.0-7.0 mmol/L) and an updated pragmatic approach (5.0-8.0 mmol/L) to reduce the risk of maternal hypoglycaemia whilst maintaining safe glycaemia. This is particularly relevant for women with type 1 diabetes who are increasingly using Continuous Glucose Monitoring (CGM) and Continuous Subcutaneous Insulin Infusion (CSII) during pregnancy. All women with diabetes should have a documented delivery plan agreed during antenatal clinic appointments. Hyperglycaemia following steroid administration can be managed either by increasing basal and prandial insulin doses, typically by 50% to 80%, or by adding a variable rate of intravenous insulin infusion (VRIII). Glucose levels, either capillary blood glucose or CGM glucose levels, should be measured at least hourly from the onset of established labour, artificial rupture of membranes or admission for elective caesarean section. If intrapartum glucose levels are higher than 7.0 or 8.0 mmol/L on two consecutive occasions, VRIII is recommended. Hourly capillary blood glucose rather than CGM glucose measurements should be used to adjust VRIII. The recommended substrate fluid to be administered alongside a VRIII is 0.9% sodium chloride solution with 5% glucose and 0.15% potassium chloride (KCl) (20 mmol/L) or 0.3% KCl (40 mmol/L) at 50 ml/hr. Both the VRIII and CSII rates should be reduced by at least 50% after delivery.

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.

Can placental growth factors explain birthweight variation in offspring of women with type 1 diabetes?

AIMS/HYPOTHESIS: Maternal hyperglycaemia alone does not explain the incidence of large offspring amongst women with type 1 diabetes. The objective of the study was to determine if there is an association between placental function, as measured by angiogenic factors, and offspring birthweight z score in women with type 1 diabetes. METHODS: This cohort study included samples from 157 Continuous Glucose Monitoring in Pregnant Women with Type 1 Diabetes (CONCEPTT) trial participants. Correlations were estimated between birthweight z score and placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) levels measured at baseline and at 24 and 34 weeks of gestation. Linear regression was used to assess the relationship between birthweight z score and placental health, as measured by PlGF and sFlt-1/PlGF ratio, stratified by glycaemic status (continuous glucose monitoring and HbA1c measures) and adjusted for potential confounders of maternal BMI, smoking and weight gain. Higher PlGF levels and lower sFlt-1/PlGF ratios represent healthy placentas, while lower PlGF levels and higher sFlt-1/PlGF ratios represent unhealthy placentas. RESULTS: Among CONCEPTT participants, the slopes relating PlGF levels to birthweight z scores differed according to maternal glycaemia at 34 weeks of gestation (p = 0.003). With optimal maternal glycaemia (HbA1c < 48 mmol/mol [6.5%]/ or continuous glucose monitoring time above range ≤ 30%), birthweight z scores were reduced towards zero (normal weight) with increasing PlGF values (representing a healthy placenta), and increased with decreasing PlGF values. With suboptimal glycaemic status (HbA1c ≥ 48 mmol/mol [6.5%] or time above range > 30%), increasing PlGF values were associated with heavier infants. Those with a healthy placenta (PlGF > 100) and suboptimal glycaemic control had a higher mean z score (2.45) than those with an unhealthy placenta (mean z score = 1.86). Similar relationships were seen when using sFlt-1/PlGF ratio as a marker for a healthy vs unhealthy placenta. CONCLUSIONS/INTERPRETATION: In women with type 1 diabetes, infant birthweight is influenced by both glycaemic status and placental function. In women with suboptimal glycaemia, infant birthweight was heavier when placentas were healthy. Suboptimal placental function should be considered in the setting of suboptimal glycaemia and apparently 'normal' birthweight.

Optimizing the use of technology to support people with diabetes: research recommendations from Diabetes UK's 2019 diabetes and technology workshop.

AIMS: To identify key gaps in the research evidence base that could help improve how technology supports people with diabetes, and provide recommendations to researchers and research funders on how best to address them. METHODS: A research workshop was conducted, bringing together research experts in diabetes, research experts in technology, people living with diabetes and healthcare professionals. RESULTS: The following key areas within this field were identified, and research recommendations for each were developed: Matching the pace of research with that of technology development Time in range as a measure Health inequalities and high-risk groups How to train people to use technology most effectively Impact of technology usage on mental health CONCLUSIONS: This position statement outlines recommendations through which research could improve how technology is employed to care for and support people living with diabetes, and calls on the research community and funders to address them in future research programmes and strategies.

The top 10 research priorities in diabetes and pregnancy according to women, support networks and healthcare professionals.

AIMS: To undertake a Priority Setting Partnership (PSP) to establish priorities for future research in diabetes and pregnancy, according to women with experience of pregnancy, and planning pregnancy, with any type of diabetes, their support networks and healthcare professionals. METHODS: The PSP used established James Lind Alliance (JLA) methodology working with women and their support networks and healthcare professionals UK-wide. Unanswered questions about the time before, during or after pregnancy with any type of diabetes were identified using an online survey and broad-level literature search. A second survey identified a shortlist of questions for final prioritisation at an online consensus development workshop. RESULTS: There were 466 responses (32% healthcare professionals) to the initial survey, with 1161 questions, which were aggregated into 60 unanswered questions. There were 614 responses (20% healthcare professionals) to the second survey and 18 questions shortlisted for ranking at the workshop. The top 10 questions were: diabetes technology, the best test for diabetes during pregnancy, diet and lifestyle interventions for diabetes management during pregnancy, emotional and well-being needs of women with diabetes pre- to post-pregnancy, safe full-term birth, post-natal care and support needs of women, diagnosis and management late in pregnancy, prevention of other types of diabetes in women with gestational diabetes, women's labour and birth experiences and choices and improving planning pregnancy. CONCLUSIONS: These research priorities provide guidance for research funders and researchers to target research in diabetes and pregnancy that will achieve greatest value and impact.

Which growth standards should be used to identify large- and small-for-gestational age infants of mothers with type 1 diabetes? A pre-specified analysis of the CONCEPTT trial.

BACKGROUND: Offspring of women with type 1 diabetes are at increased risk of fetal growth patterns which are associated with perinatal morbidity. Our aim was to compare rates of large- and small-for-gestational age (LGA; SGA) defined according to different criteria, using data from the Continuous Glucose Monitoring in Type 1 Diabetes Pregnancy Trial (CONCEPTT). METHODS: This was a pre-specified analysis of CONCEPTT involving 225 pregnant women and liveborn infants from 31 international centres ( ClinicalTrials.gov NCT01788527; registered 11/2/2013). Infants were weighed immediately at birth and GROW, INTERGROWTH and WHO centiles were calculated. Relative risk ratios, sensitivity and specificity were used to assess the different growth standards with respect to perinatal outcomes, including neonatal hypoglycaemia, hyperbilirubinaemia, respiratory distress, neonatal intensive care unit (NICU) admission and a composite neonatal outcome. RESULTS: Accelerated fetal growth was common, with mean birthweight percentiles of 82.1, 85.7 and 63.9 and LGA rates of 62, 67 and 30% using GROW, INTERGROWTH and WHO standards respectively. Corresponding rates of SGA were 2.2, 1.3 and 8.9% respectively. LGA defined according to GROW centiles showed stronger associations with preterm delivery, neonatal hypoglycaemia, hyperbilirubinaemia and NICU admission. Infants born > 97.7th centile were at highest risk of complications. SGA defined according to INTERGROWTH centiles showed slightly stronger associations with perinatal outcomes. CONCLUSIONS: GROW and INTERGROWTH standards performed similarly and identified similar numbers of neonates with LGA and SGA. GROW-defined LGA and INTERGROWTH-defined SGA had slightly stronger associations with neonatal complications. WHO standards underestimated size in preterm infants and are less applicable for use in type 1 diabetes. TRIAL REGISTRATION: This trial is registered with ClinicalTrials.gov . number NCT01788527 . Trial registered 11/2/2013.

Dead-End Ultrafiltration and DNA-Based Methods for Detection of Cyclospora cayetanensis in Agricultural Water.

Cyclospora cayetanensis is a protozoan parasite that causes foodborne and waterborne diarrheal illness outbreaks worldwide. Most of these outbreaks are associated with the consumption of fresh produce. Sensitive and specific methods to detect C. cayetanensis in agricultural water are needed to identify the parasite in agricultural water used to irrigate crops that have been implicated in outbreaks. In this study, a method to detect C. cayetanensis in water by combining dead-end ultrafiltration (DEUF) with sensitive and specific molecular detection was developed and evaluated. Triplicates of 10-liter agricultural water samples were seeded with 200, 100, 25, 12, and 6 C. cayetanensis oocysts. Surface water samples were also collected in the Mid-Atlantic region. All water samples were processed by DEUF and backflushed from the ultrafilters. DNA was extracted from concentrated samples and analyzed by quantitative PCR (qPCR) targeting the C. cayetanensis 18S rRNA gene. All water samples seeded with 12, 25, 100, and 200 oocysts were positive, and all unseeded samples were negative. Samples seeded with 6 oocysts had a detection rate of 66.6% (8/12). The method was also able to detect C. cayetanensis isolates in surface water samples from different locations of the Chesapeake and Ohio Canal (C&O Canal) in Maryland. This approach could consistently detect C. cayetanensis DNA in 10-liter agricultural water samples contaminated with low levels of oocysts, equivalent to the levels that may be found in naturally incurred environmental water sources. Our data demonstrate the robustness of the method as a useful tool to detect C. cayetanensis from environmental sources.IMPORTANCECyclospora cayetanensis is a protozoan parasite that causes foodborne and waterborne outbreaks of diarrheal illness worldwide. These foodborne outbreaks associated with the consumption of fresh produce and agricultural water could play a role in the contamination process. In this study, a method to detect C. cayetanensis in agricultural water by combining a robust filtration system with sensitive and specific molecular detection was developed and validated by the FDA. The results showed that this approach could consistently detect low levels of C. cayetanensis contamination in 10 liters of agricultural water, corresponding to the levels that may be found in naturally occurring environmental water sources. The method was also able to detect C. cayetanensis in surface water samples from a specific location in the Mid-Atlantic region. Our data demonstrate the robustness of the method to detect C. cayetanensis in agricultural water samples, which could be very useful to identify environmental sources of contamination.