REduced-Carbohydrate intervention for managing Obesity and Reduction of gestational Diabetes (RECORD): A randomized controlled feasibility trial.

AIM: To test the feasibility and acceptability of a reduced-carbohydrate dietary program, intended to reduce the risk of gestational diabetes. MATERIALS AND METHODS: Fifty-one pregnant women at <20 weeks' gestation, with body mass index ≥30 kg/m2 , and a normal baseline oral glucose tolerance test (OGTT), were randomized 2:1 to an intervention or control group and followed-up until delivery. The dietary intervention aimed at providing 130-150 g carbohydrate/day. Feasibility outcomes assessed at 24-28 weeks' gestation, included adoption of the reduced-carbohydrate diet by the intervention group, and retention of all participants, assessed by completion of a second OGTT. Changes in glycemia, weight gain and dietary intake, and the maternal and neonatal outcomes were also assessed. Participants were interviewed about their experience of the intervention and the study. RESULTS: Forty-nine of 51 participants attended the follow-up OGTT, a retention rate of 96% (95% confidence interval [CI] 86.8%-98.9%). In the intervention group, carbohydrate intake at follow-up was 190.4 (95% CI 162.5-215.6) g/day, a reduction of -24.6 (95% CI -51.5-2.4) g/day from baseline. Potentially favourable effects of the intervention on glucose control, weight gain and blood pressure were observed, but the study was not powered to detect significant differences in these. Participants found the intervention acceptable, and were content with the study processes, but some reported barriers to sustained adherence, mainly pertaining to competing priorities. CONCLUSIONS: Retention was high, suggesting the study processes are feasible, but the carbohydrate reduction in the intervention group was small, and did not meet progression criteria, limiting the likelihood of achieving the desired goal to prevent gestational diabetes. TRIAL REGISTRATION NUMBER: ISRCTN16235884.

Association of common maternal infections with birth outcomes: a multinational cohort study.

PURPOSE: It is unclear whether common maternal infections during pregnancy are risk factors for adverse birth outcomes. We assessed the association between self-reported infections during pregnancy with preterm birth and small-for-gestational-age (SGA) in an international cohort consortium. METHODS: Data on 120,507 pregnant women were obtained from six population-based birth cohorts in Australia, Denmark, Israel, Norway, the UK and the USA. Self-reported common infections during pregnancy included influenza-like illness, common cold, any respiratory tract infection, vaginal thrush, vaginal infections, cystitis, urinary tract infection, and the symptoms fever and diarrhoea. Birth outcomes included preterm birth, low birth weight and SGA. Associations between maternal infections and birth outcomes were first assessed using Poisson regression in each cohort and then pooled using random-effect meta-analysis. Risk ratios (RR) and 95% confidence intervals (CI) were calculated, adjusted for potential confounders. RESULTS: Vaginal infections (pooled RR, 1.10; 95% CI, 1.02-1.20) and urinary tract infections (pooled RR, 1.17; 95% CI, 1.09-1.26) during pregnancy were associated with higher risk of preterm birth. Similar associations with low birth weight were also observed for these two infections. Fever during pregnancy was associated with higher risk of SGA (pooled RR, 1.07; 95% CI, 1.02-1.12). No other significant associations were observed between maternal infections/symptoms and birth outcomes. CONCLUSION: Vaginal infections and urinary infections during pregnancy were associated with a small increased risk of preterm birth and low birth weight, whereas fever was associated with SGA. These findings require confirmation in future studies with laboratory-confirmed infection diagnosis.

An expert review of environmental heat exposure and stillbirth in the face of climate change: Clinical implications and priority issues.

Exposure to extreme heat in pregnancy increases the risk of stillbirth. Progress in reducing stillbirth rates has stalled, and populations are increasingly exposed to high temperatures and climate events that may further undermine health strategies. This narrative review summarises the current clinical and epidemiological evidence of the impact of maternal heat exposure on stillbirth risk. Out of 20 studies, 19 found an association between heat and stillbirth risk. Recent studies based in low- to middle-income countries and tropical settings add to the existing literature to demonstrate that all populations are at risk. Additionally, both short-term heat exposure and whole-pregnancy heat exposure increase the risk of stillbirth. A definitive threshold of effect has not been identified, as most studies define exposure as above the 90th centile of the usual temperature for that population. Therefore, the association between heat and stillbirth has been found with exposures from as low as >12.64°C up to >46.4°C. The pathophysiological pathways by which maternal heat exposure may lead to stillbirth, based on human and animal studies, include both placental and embryonic or fetal impacts. Although evidence gaps remain and further research is needed to characterise these mechanistic pathways in more detail, preliminary evidence suggests epigenetic changes, alteration in imprinted genes, congenital abnormalities, reduction in placental blood flow, size and function all play a part. Finally, we explore this topic from a public health perspective; we discuss and evaluate the current public health guidance on minimising the risk of extreme heat in the community. There is limited pregnancy-specific guidance within heatwave planning, and no evidence-based interventions have been established to prevent poor pregnancy outcomes. We highlight priority research questions to move forward in the field and specifically note the urgent need for evidence-based interventions that are sustainable.

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.

A feasibility study using motivational interviewing and a smartphone application to promote physical activity (+Stay-Active) for women with gestational diabetes.

BACKGROUND: Physical activity (PA) interventions have an encouraging role in gestational diabetes mellitus (GDM) management. Digital technologies can potentially be used at scale to support PA. The aim of this study was to assess the feasibility and acceptability of + Stay-Active: a complex intervention which combines motivational interviewing with a smartphone application to promote PA levels in women with GDM. METHODS: This non-randomised feasibility study used a mixed methods approach. Participants were recruited from the GDM antenatal clinic at Oxford University Hospitals. Following baseline assessments (visit 1) including self-reported and device determined PA measurements (wrist worn accelerometer), women participated in an online motivational interview, and then downloaded (visit 2) and used the Stay-Active app (Android or iOS). Women had access to Stay-Active until 36 weeks' gestation, when acceptability and PA levels were reassessed (visit 3). The primary outcome measures were recruitment and retention rates, participant engagement, and acceptability and fidelity of the intervention. Secondary outcome measures included PA levels, app usage, blood glucose and perinatal outcomes. Descriptive statistics were performed for assessments at study visits. Statistics software package Stata 14 and R were used. RESULTS: Over the recruitment period (46 weeks), 114 of 285 women met inclusion criteria and 67 (58%) enrolled in the study. Mean recruitment rate of 1.5 participants/clinic with 2.5 women/clinic meeting inclusion criteria. Fifty-six (83%) received the intervention at visit 2 and 53 (79%) completed the study. Compliance to accelerometer measurement protocols were sufficient in 78% of participants (52/67); wearing the device for more than 10 h on 5 or more days at baseline and 61% (41/67) at 36 weeks. There was high engagement with Stay-Active; 82% (55/67) of participants set goals on Stay-Active. Sustained engagement was evident, participants regularly accessed and logged multiples activities on Stay-Active. The intervention was deemed acceptable; 85% of women rated their care was satisfactory or above, supported by written feedback. CONCLUSIONS: This combined intervention was feasible and accepted. Recruitment rates were lower than expected. However, retention rates remained satisfactory and participant compliance with PA measurements and engagement was a high. Future work will explore the intervention's efficacy to increase PA and impact on clinical outcomes. TRIAL REGISTRATION: The study has received a favourable opinion from South Central-Hampshire B Research Ethics Committee; REC reference: 20/SC/0342. ISRCTN11366562.

A Stacked Long Short-Term Memory Approach for Predictive Blood Glucose Monitoring in Women with Gestational Diabetes Mellitus.

Gestational diabetes mellitus (GDM) is a subtype of diabetes that develops during pregnancy. Managing blood glucose (BG) within the healthy physiological range can reduce clinical complications for women with gestational diabetes. The objectives of this study are to (1) develop benchmark glucose prediction models with long short-term memory (LSTM) recurrent neural network models using time-series data collected from the GDm-Health platform, (2) compare the prediction accuracy with published results, and (3) suggest an optimized clinical review schedule with the potential to reduce the overall number of blood tests for mothers with stable and within-range glucose measurements. A total of 190,396 BG readings from 1110 patients were used for model development, validation and testing under three different prediction schemes: 7 days of BG readings to predict the next 7 or 14 days and 14 days to predict 14 days. Our results show that the optimized BG schedule based on a 7-day observational window to predict the BG of the next 14 days achieved the accuracies of the root mean square error (RMSE) = 0.958 ± 0.007, 0.876 ± 0.003, 0.898 ± 0.003, 0.622 ± 0.003, 0.814 ± 0.009 and 0.845 ± 0.005 for the after-breakfast, after-lunch, after-dinner, before-breakfast, before-lunch and before-dinner predictions, respectively. This is the first machine learning study that suggested an optimized blood glucose monitoring frequency, which is 7 days to monitor the next 14 days based on the accuracy of blood glucose prediction. Moreover, the accuracy of our proposed model based on the fingerstick blood glucose test is on par with the prediction accuracies compared with the benchmark performance of one-hour prediction models using continuous glucose monitoring (CGM) readings. In conclusion, the stacked LSTM model is a promising approach for capturing the patterns in time-series data, resulting in accurate predictions of BG levels. Using a deep learning model with routine fingerstick glucose collection is a promising, predictable and low-cost solution for BG monitoring for women with gestational diabetes.

Understanding the relationship between social determinants of health and maternal mortality: Scientific Impact Paper No. 67.

Within this document we use the terms pregnant woman and women's health. However, it is important to acknowledge that it is not only people who identify as women for whom it is necessary to access care. Obstetric and gynaecology services and delivery of care must therefore be appropriate, inclusive and sensitive to the needs of those individuals whose gender identity does not align with the sex they were assigned at birth.

Clinical consequences of gestational diabetes mellitus and maternal obesity as defined by asian BMI thresholds in Viet Nam: a prospective, hospital-based, cohort study.

BACKGROUND: Gestational Diabetes Mellitus (GDM) is common in South East Asia, occurring at relatively lean Body Mass Index (BMI). Outside pregnancy, cardiometabolic risks increase at lower BMI in Asian populations, justifying Asian-specific thresholds for overweight and obesity. We aimed to explore the effects of GDM and obesity on perinatal outcomes using a WHO expert consultation-recommended Asian-specific definition of obesity. METHODS: This is a secondary analysis of a prospective, hospital-based, cohort study in Ho Chi Minh City. Participants were recruited from antenatal clinics between 19+ 0-22+ 6 weeks gestation and followed until delivery. GDM screening occurred between 24 and 28 weeks using WHO criteria. Obesity was defined as BMI ≥ 27.5 kg/m2, based on weight and height at recruitment. We assessed associations between GDM (singly, and in combination with obesity) and perinatal outcomes. Participants were categorised into four groups: no GDM/non-obese (reference group), GDM/non-obese, no GDM/obese and GDM/obese. Outcomes included primary caesarean section, hypertensive disorders of pregnancy (HDP), large-for-gestational-age (LGA), birth weight, preterm birth, and composite adverse neonatal outcome. Logistic and linear regressions were performed with adjustment for differences in baseline characteristics. RESULTS: Among 4,970 participants, 908 (18%) developed GDM. Compared to women without GDM, GDM increased risks for preterm birth (OR: 1.40, 95% CI: 1.09-1.78), higher birthweight (birthweight z-score 0.16 versus 0.09, p = 0.027), and LGA (OR 1.14, 0.89-1.46). GDM without obesity was associated with an increased risk of preterm birth (OR 1.35, 1.04-1.74). Obese women without GDM were more likely to deliver by caesarean section and have an LGA baby (1.80, 1.33-2.44 and 2.75, 1.88-4.03). The highest risks were observed amongst women with both GDM and obesity: caesarean Sect. (2.43, 1.49-3.96), LGA (3.36, 1.94-5.80) and preterm birth (2.42, 1.32-4.44). CONCLUSIONS: GDM was associated with an increased risk of preterm birth and larger newborn size. Using an Asian-specific definition of obesity, we demonstrate obese women with GDM are at the highest risk of adverse outcomes. Using a BMI threshold in pregnancy of 27.5 kg/m2 (between 19 and 22 weeks gestation) for Asian women can identify women who will benefit from intensified diabetes, nutritional, and obstetric care. This has relevance for obstetric service delivery within Asia, and other health systems providing pregnancy care for Asian expatriate women.

Physiological mechanisms of the impact of heat during pregnancy and the clinical implications: review of the evidence from an expert group meeting.

Many populations experience high seasonal temperatures. Pregnant women are considered vulnerable to extreme heat because ambient heat exposure has been linked to pregnancy complications including preterm birth and low birthweight. The physiological mechanisms that underpin these associations are poorly understood. We reviewed the existing research evidence to clarify the mechanisms that lead to adverse pregnancy outcomes in order to inform public health actions. A multi-disciplinary expert group met to review the existing evidence base and formulate a consensus regarding the physiological mechanisms that mediate the effect of high ambient temperature on pregnancy. A literature search was conducted in advance of the meeting to identify existing hypotheses and develop a series of questions and themes for discussion. Numerous hypotheses have been generated based on animal models and limited observational studies. There is growing evidence that pregnant women are able to appropriately thermoregulate; however, when exposed to extreme heat, there are a number of processes that may occur which could harm the mother or fetus including a reduction in placental blood flow, dehydration, and an inflammatory response that may trigger preterm birth. There is a lack of substantial evidence regarding the processes that cause heat exposure to harm pregnant women. Research is urgently needed to identify what causes the adverse outcomes in pregnancy related to high ambient temperatures so that the impact of climate change on pregnant women can be mitigated.

Machine Learning-Based Risk Stratification for Gestational Diabetes Management.

Gestational diabetes mellitus (GDM) is often diagnosed during the last trimester of pregnancy, leaving only a short timeframe for intervention. However, appropriate assessment, management, and treatment have been shown to reduce the complications of GDM. This study introduces a machine learning-based stratification system for identifying patients at risk of exhibiting high blood glucose levels, based on daily blood glucose measurements and electronic health record (EHR) data from GDM patients. We internally trained and validated our model on a cohort of 1148 pregnancies at Oxford University Hospitals NHS Foundation Trust (OUH), and performed external validation on 709 patients from Royal Berkshire Hospital NHS Foundation Trust (RBH). We trained linear and non-linear tree-based regression models to predict the proportion of high-readings (readings above the UK's National Institute for Health and Care Excellence [NICE] guideline) a patient may exhibit in upcoming days, and found that XGBoost achieved the highest performance during internal validation (0.021 [CI 0.019-0.023], 0.482 [0.442-0.516], and 0.112 [0.109-0.116], for MSE, R2, MAE, respectively). The model also performed similarly during external validation, suggesting that our method is generalizable across different cohorts of GDM patients.

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.

Chinese women's attitudes towards postpartum interventions to prevent type 2 diabetes after gestational diabetes: a semi-structured qualitative study.

BACKGROUND: Gestational diabetes (GDM) is a global problem affecting millions of pregnant women, including in mainland China. These women are at high risk of Type II diabetes (T2DM). Cost-effective and clinically effective interventions are needed. We aimed to explore Chinese women's perspectives, concerns and motivations towards participation in early postpartum interventions and/or research to prevent the development of T2DM after a GDM-affected pregnancy. METHODS: We conducted a qualitative study in two hospitals in Chengdu, Southwest China. Face-to-face semi-structured interviews were conducted with 20 women with recent experience of GDM: 16 postpartum women and 4 pregnant women. Women were asked about their attitudes towards postpartum screening for type 2 diabetes, lifestyle interventions, mHealth delivered interventions and pharmacologic interventions (specifically metformin). An inductive approach to analysis was used. Interviews were recorded, transcribed, and coded using NVivo 12 Pro. RESULTS: Most women held positive attitudes towards participating in T2DM screening, and were willing to participate in postpartum interventions to prevent T2DM through lifestyle change or mHealth interventions. Women were less likely to agree to pharmacological intervention, unless they had family members with diabetes or needed medication themselves during pregnancy. We identified seven domains influencing women's attitudes towards future interventions: (1) experiences with the health system during pregnancy; (2) living in an enabling environment; (3) the experience of T2DM in family members; (4) knowledge of diabetes and perception of risk; (5) concerns about personal and baby health; (6) feelings and emotions, and (7) lifestyle constraints. Those with more severe GDM, an enabling environment and health knowledge, and with experience of T2DM in family members expressed more favourable views of postpartum interventions and research participation to prevent T2DM after GDM. Those who perceived themselves as having mild GDM and those with time/lifestyle constraints were less likely to participate. CONCLUSIONS: Women with experiences of GDM in Chengdu are generally willing to participate in early postpartum interventions and/or research to reduce their risk of T2DM, with a preference for non-drug, mHealth based interventions, integrating lifestyle change strategies, blood glucose monitoring, postpartum recovery and mental health.

Gestational diabetes mellitus (GDM) is a common pregnancy complication affecting up to 1 in 6 pregnant women worldwide. Whilst the condition usually resolves soon after delivery, women are at high risk of developing type 2 diabetes mellitus (T2DM). In this study, we asked women living in Chengdu, a city in western China, about what they knew about their risk of diabetes and how they felt about participating in interventions after birth to prevent T2DM.After listening to the views of 20 women, we concluded that in this setting most women are happy to attend T2DM screening programs after birth, and would be willing to consider participating in interventions and research after birth to prevent T2DM.The interventions most preferred were those that aimed at lifestyle changes, and many women said would like to receive this information through their smartphone, for example through an app or social media channel. Women were reluctant to take medications to prevent T2DM.The main factors that influenced how women felt towards interventions to prevent T2DM were: (1) their experiences with the health system during pregnancy; (2) whether the home environment was supportive to make changes to diet and lifestyle; (3) any experiences of T2DM in family members; (4) their knowledge of diabetes and perception of risk; (5) concerns about personal and baby health; (6) feelings and emotions in the postnatal period, and (7) lifestyle constraints making it difficult to make dietary changes.

Maternal Infection in Pregnancy and Childhood Leukemia: A Systematic Review and Meta-analysis.

OBJECTIVE: To summarize the published evidence regarding the association between maternal infection during pregnancy and childhood leukemia. STUDY DESIGN: In this systematic review and meta-analysis (PROSPERO number, CRD42018087289), we searched PubMed and Embase to identify relevant studies. We included human studies that reported associations of at least one measure of maternal infection during pregnancy with acute lymphoblastic leukemia (ALL) or all childhood leukemias in the offspring. One reviewer extracted the data first using a standardized form, and the second reviewer independently checked the data for accuracy. Two reviewers used the Newcastle-Ottawa Scale to assess the quality of included studies. We conducted random effects meta-analyses to pool the ORs of specific type of infection on ALL and childhood leukemia. RESULTS: This review included 20 studies (ALL, n = 15; childhood leukemia, n = 14) reported in 32 articles. Most (>65%) included studies reported a positive association between infection variables and ALL or childhood leukemia. Among specific types of infection, we found that influenza during pregnancy was associated with higher risk of ALL (pooled OR, 3.64; 95% CI, 1.34-9.90) and childhood leukemia (pooled OR, 1.77; 95% CI, 1.01-3.11). Varicella (pooled OR, 10.19; 95% CI, 1.98-52.39) and rubella (pooled OR, 2.79; 95% CI, 1.16-6.71) infections were also associated with higher childhood leukemia risk. CONCLUSIONS: Our findings suggest that maternal infection during pregnancy may be associated with a higher risk of childhood leukemia.

Telemedicine Technologies for Diabetes in Pregnancy: A Systematic Review and Meta-Analysis.

BACKGROUND: Diabetes in pregnancy is a global problem. Technological innovations present exciting opportunities for novel approaches to improve clinical care delivery for gestational and other forms of diabetes in pregnancy. OBJECTIVE: To perform an updated and comprehensive systematic review and meta-analysis of the literature to determine whether telemedicine solutions offer any advantages compared with the standard care for women with diabetes in pregnancy. METHODS: The review was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework. Randomized controlled trials (RCT) in women with diabetes in pregnancy that compared telemedicine blood glucose monitoring with the standard care were identified. Searches were performed in SCOPUS and PubMed, limited to English language publications between January 2000 and January 2016. Trials that met the eligibility criteria were scored for risk of bias using the Cochrane Collaborations Risk of Bias Tool. A meta-analysis was performed using Review Manager software version 5.3 (Nordic Cochrane Centre, Cochrane Collaboration). RESULTS: A total of 7 trials were identified. Meta-analysis demonstrated a modest but statistically significant improvement in HbA1c associated with the use of a telemedicine technology. The mean HbA1c of women using telemedicine was 5.33% (SD 0.70) compared with 5.45% (SD 0.58) in the standard care group, representing a mean difference of -0.12% (95% CI -0.23% to -0.02%). When this comparison was limited to women with gestational diabetes mellitus (GDM) only, the mean HbA1c of women using telemedicine was 5.22% (SD 0.70) compared with 5.37% (SD 0.61) in the standard care group, mean difference -0.14% (95% CI -0.25% to -0.04%). There were no differences in other maternal and neonatal outcomes reported. CONCLUSIONS: There is currently insufficient evidence that telemedicine technology is superior to standard care for women with diabetes in pregnancy; however, there was no evidence of harm. No trials were identified that assessed patient satisfaction or cost of care delivery, and it may be in these areas where these technologies may be found most valuable.

Digital Health and Machine Learning Technologies for Blood Glucose Monitoring and Management of Gestational Diabetes.

Innovations in digital health and machine learning are changing the path of clinical health and care. People from different geographical locations and cultural backgrounds can benefit from the mobility of wearable devices and smartphones to monitor their health ubiquitously. This paper focuses on reviewing the digital health and machine learning technologies used in gestational diabetes - a subtype of diabetes that occurs during pregnancy. This paper reviews sensor technologies used in blood glucose monitoring devices, digital health innovations and machine learning models for gestational diabetes monitoring and management, in clinical and commercial settings, and discusses future directions. Despite one in six mothers having gestational diabetes, digital health applications were underdeveloped, especially the techniques that can be deployed in clinical practice. There is an urgent need to (1) develop clinically interpretable machine learning methods for patients with gestational diabetes, assisting health professionals with treatment, monitoring, and risk stratification before, during and after their pregnancies; (2) adapt and develop clinically-proven devices for patient self-management of health and well-being at home settings ("virtual ward" and virtual consultation), thereby improving clinical outcomes by facilitating timely intervention; and (3) ensure innovations are affordable and sustainable for all women with different socioeconomic backgrounds and clinical resources.

Early pregnancy maternal blood pressure and risk of preeclampsia: Does the association differ by parity? Evidence from 14,086 women across 7 countries.

OBJECTIVE: To determine if the relationship between blood pressure (BP) before 16 weeks' gestation and subsequent onset of preeclampsia differs by parity, and by history of hypertensive disorders of pregnancy (HDP) in parous women. STUDY DESIGN: Data from two studies were pooled. First, routinely collected clinical data from three metropolitan hospitals in Sydney, Australia (2017-2020), where BP was measured as part of routine clinical care using validated mercury-free sphygmomanometers. Second, prospectively collected research data from the INTERBIO-21st Study, conducted in six countries, investigating the epidemiology of fetal growth restriction and preterm birth, where BP was measured by dedicated research staff using an automated machine validated for use in pregnancy. MAIN OUTCOME: Adjusted odds ratios (aOR) (95% confidence interval (CI)) for the association of systolic BP (SBP), diastolic BP (DBP) and mean arterial pressure (MAP) with preeclampsia were obtained from logistic regression models. Models were adjusted for age, smoking, body mass index, previous hypertension, previous diabetes, and previous preeclampsia. Interactions for parity, and history of HDP in parous women were included. RESULTS: There were 14,086 pregnancies (Sydney = 11008, INTERBIO-21st = 3078) in the pooled analyses, 6914 (49 %) were parous, of which 414 (6.0 %) had a history of HDP. Nulliparous women had a higher risk of preeclampsia (2.6 %) compared with parous women (1.5 %): [aOR (95 %CI) 3.61 (2.67, 4.94)], as did parous women with a history of HDP (15.0 %) compared with no history (0.7 %) [12.70 (8.02, 20.16)]. MAP before 16 weeks' gestation (mean [SD] 78.8[8.6] mmHg) was more strongly associated than SBP or DBP with development of preeclampsia in parous women [2.22 (1.81, 2.74)] per SD higher MAP] compared with nulliparous women [1.58 (1.34, 1.87)] (p for interaction 0.013). There were no significant differences on the effect of blood pressure on preeclampsia in parous women by history of HDP (p for interaction 0.5465). CONCLUSION: The risk of preeclampsia differs according to parity and history of HDP in a previous pregnancy. Blood pressure in early pregnancy predicts preeclampsia in all groups, although more strongly associated in parous than nulliparous women, but no different in parous women by history of HDP.

A life-course approach to tackling noncommunicable diseases in women.

Women's health has been critically underserved by a failure to look beyond women's sexual and reproductive systems to adequately consider their broader health needs. In almost every country in the world, noncommunicable diseases are the leading causes of death for women. Among these, cardiovascular disease (including heart disease and stroke) and cancer are the major causes of mortality. Risks for these conditions exist at each stage of women's lives, but recognition of the unique needs of women for the prevention and management of noncommunicable diseases is relatively recent and still emerging. Once they are diagnosed, treatments for these diseases are often costly and noncurative. Therefore, we call for a strategic, innovative life-course approach to identifying disease triggers and instigating cost-effective measures to minimize exposure in a timely manner. Prohibitive barriers to implementing this holistic approach to women's health exist in both the social arena and the medical arena. Recognizing these impediments and implementing practical approaches to surmounting them is a rational approach to advancing health equity for women, with ultimate benefits for society as a whole.

Understanding maternal sepsis risk factors and bacterial etiology: A case control study protocol.

INTRODUCTION: Maternal disorders are the third leading cause of sepsis globally, accounting for 5.7 million (12%) cases in 2017. There are increasing concerns about the emergence of antimicrobial resistance (AMR) in bacteria commonly causing maternal sepsis. Our aim is to describe the protocol for a clinical and microbiology laboratory study to understand risk factors for and the bacterial etiology of maternal sepsis in a tertiary Obstetrics and Gynaecology Hospital. METHODS: This case-control study aims to recruit 100 cases and 200 controls at Tu Du Hospital in Ho Chi Minh City, Vietnam, which had approximately 55,000 births in 2022. Women aged ≥ 18 years and ≥ 28 weeks gestation having a singleton birth will be eligible for inclusion as cases or controls, unless they have an uncomplicated localised or chronic infection, or an infection with SARS-CoV-2. Cases will include pregnant or recently pregnant women with sepsis recognised between the onset of labour and/or time of delivery/cessation of pregnancy for up to 42 days post-partum. Sepsis will be defined as suspected or confirmed infection with an obstetrically modified Sequential Organ Failure Assessment score of ≥ 2, treatment with intravenous antimicrobials and requested cultures of any bodily fluid. Controls will be matched by age, location, parity, mode of delivery and gestational age. Primary and secondary outcomes are risk factors associated with the development of maternal sepsis, the frequency of adverse outcomes due to maternal sepsis, bacterial etiology and AMR profiles of cases and controls. DISCUSSION: This study will improve understanding of the epidemiology and clinical implications of maternal sepsis management including the presence of AMR in women giving birth in Vietnam. It will help us to determine whether women in this setting are receiving optimal care and to identify opportunities for improvement.

Validating the ratio of insulin like growth factor binding protein 4 to sex hormone binding globulin as a prognostic predictor of preterm birth in Viet Nam: a case-cohort study.

OBJECTIVE: To validate a serum biomarker developed in the USA for preterm birth (PTB) risk stratification in Viet Nam. METHODS: Women with singleton pregnancies (n = 5000) were recruited between 19+0-23+6 weeks' gestation at Tu Du Hospital, Ho Chi Minh City. Maternal serum was collected from 19+0-22+6 weeks' gestation and participants followed to neonatal discharge. Relative insulin-like growth factor binding protein 4 (IGFBP4) and sex hormone binding globulin (SHBG) abundances were measured by mass spectrometry and their ratio compared between PTB cases and term controls. Discrimination (area under the receiver operating characteristic curve, AUC) and calibration for PTB <37 and <34 weeks' gestation were tested, with model tuning using clinical factors. Measured outcomes included all PTBs (any birth ≤37 weeks' gestation) and spontaneous PTBs (birth ≤37 weeks' gestation with clinical signs of initiation of parturition). RESULTS: Complete data were available for 4984 (99.7%) individuals. The cohort PTB rate was 6.7% (n = 335). We observed an inverse association between the IGFBP4/SHBG ratio and gestational age at birth (p = 0.017; AUC 0.60 [95% CI, 0.53-0.68]). Including previous PTB (for multiparous women) or prior miscarriage (for primiparous women) improved performance (AUC 0.65 and 0.70, respectively, for PTB <37 and <34 weeks' gestation). Optimal performance (AUC 0.74) was seen within 19-20 weeks' gestation, for BMI >21 kg/m2 and age 20-35 years. CONCLUSION: We have validated a novel serum biomarker for PTB risk stratification in a very different setting to the original study. Further research is required to determine appropriate ratio thresholds based on the prevalence of risk factors and the availability of resources and preventative therapies.