暂无摘要。

UNASSIGNED: The Global Financing Facility (GFF) was launched in 2015 to catalyse increased domestic and external financing for reproductive, maternal, newborn, child, adolescent health, and nutrition. Half of the deaths along this continuum are neonatal deaths, stillbirths or maternal deaths; yet these topics receive the least aid financing across the continuum.
UNASSIGNED: To conduct a policy content analysis of maternal and newborn health (MNH), including stillbirths, in GFF country planning documents, and assess the mortality burden related to the investment.
UNASSIGNED: Content analysis was conducted on 24 GFF policy documents, investment cases and project appraisal documents (PADs), from 11 African countries. We used a systematic data extraction approach and applied a framework for analysis considering mindset, measures, and money for MNH interventions and mentions of mortality outcomes. We compared PAD investments to MNH-related deaths by country.
UNASSIGNED: For these 11 countries, USD$1,894 million of new funds were allocated through the PADs, including USD$303 million (16%) from GFF. All documents had strong content on MNH, with particular focus on pregnancy and childbirth interventions. The investment cases commonly included comprehensive results frameworks, and PADs generally had less technical content and fewer indicators. Mortality outcomes were mentioned, especially for maternal. Stillbirths were rarely included as targets. Countries had differing approaches to funding descriptions. PAD allocations are commensurate with the burden.
UNASSIGNED: The GFF country plans present a promising start in addressing MNH. Emphasising links between investments and burden, explicitly including stillbirth, and highlighting high-impact packages, as appropriate, could potentially increase impact.
Main finding: Maternal and newborn health care packages are strongly included in the Global Financing Facility policy documents for 11 African countries, especially regarding pregnancy and childbirth, though less for stillbirth, or postnatal care, or small and sick newborn care.Added knowledge: This study is the first independent content analysis of Global Financing Facility investment cases and related project appraisal documents, revealing mostly consistent content for maternal and newborn health across documents and overall correlation between national mortality burden and investments committed.Global health impact for policy and action: The Global Financing Facility have demonstrated promising initial investments for maternal and newborn health, although there are also missed opportunities for strengthening, especially for some neonatal high-impact packages and counting impact on stillbirths.

A growing number of birth interventions had led to a concern for potential health consequences. This study investigates the consequences of earlier routine labor induction. It exploits a natural experiment caused by the introduction of new Danish obstetric guidelines in 2011. Consequently, routine labor induction was moved forward from 14 to 10-13 days past the expected due date (EDD) and extended antenatal surveillance was introduced from 7 days past the EDD. Using administrative data, I find that affected mothers on average had a 9-11 percentage points (32%-38%) higher risk of being induced the following years. Yet, mother and child short- and medium-term morbidity were largely unaffected.

Machine learning (ML)-driven diagnosis systems are particularly relevant in pediatrics given the well-documented impact of early-life health conditions on later-life outcomes. Yet, early identification of diseases and their subsequent impact on length of hospital stay for this age group has so far remained uncharacterized, likely because access to relevant health data is severely limited. Thanks to a confidential data use agreement with the California Department of Health Care Access and Information, we introduce Ped-BERT: a state-of-the-art deep learning model that accurately predicts the likelihood of 100+ conditions and the length of stay in a pediatric patient\'s next medical visit. We link mother-specific pre- and postnatal period health information to pediatric patient hospital discharge and emergency room visits. Our data set comprises 513.9K mother-baby pairs and contains medical diagnosis codes, length of stay, as well as temporal and spatial pediatric patient characteristics, such as age and residency zip code at the time of visit. Following the popular bidirectional encoder representations from the transformers (BERT) approach, we pre-train Ped-BERT via the masked language modeling objective to learn embedding features for the diagnosis codes contained in our data. We then continue to fine-tune our model to accurately predict primary diagnosis outcomes and length of stay for a pediatric patient\'s next visit, given the history of previous visits and, optionally, the mother\'s pre- and postnatal health information. We find that Ped-BERT generally outperforms contemporary and state-of-the-art classifiers when trained with minimum features. We also find that incorporating mother health attributes leads to significant improvements in model performance overall and across all patient subgroups in our data. Our most successful Ped-BERT model configuration achieves an area under the receiver operator curve (ROC AUC) of 0.927 and an average precision score (APS) of 0.408 for the diagnosis prediction task, and a ROC AUC of 0.855 and APS of 0.815 for the length of hospital stay task. Further, we examine Ped-BERT\'s fairness by determining whether prediction errors are evenly distributed across various subgroups of mother-baby demographics and health characteristics, or if certain subgroups exhibit a higher susceptibility to prediction errors.

The American Heart Association has updated its definition of cardiovascular health (CVH) with a new framework known as Life\'s Essential 8 (LE8). Although gestational CVH assessment has been recommended, its significance based on LE8 for birth outcomes is unknown. We thus evaluated the status of gestational CVH based on LE8 in 3036 pregnant women of the Shanghai Maternal-Child Pairs Cohort and the population of China Maternal Nutrition and Health Sciences Survey, and also examined the association between gestational CVH and child birth outcomes. We found that only a small proportion (12.84%) had high CVH, while 1.98% had low CVH in this cohort study. In adjusted models, a 10-point increase in the gestational CVH score, indicating a more favorable score, was associated with lower neonatal size such as birth weight (β: - 37.05 [95% confidence interval: - 52.93, - 21.16]), birth length (- 0.12[- 0.22, - 0.01]), weight-for-height z-score (- 0.07[- 0.12, - 0.03]), body mass index z-score (- 0.09 [- 0.13, - 0.04]), length-for-age Z-score (- 0.03 [- 0.06, - 0.01]), and weight-for-age z-score (- 0.08 [- 0.12, - 0.05]). Also, a 10-point increase in the gestational CVH score was associated with the lower risk of large for gestational age (LGA) (0.82 [0.73, 0.92]) and macrosomia infant (0.75 [0.64, 0.88]). CVH categories showed similar results. That is, better maternal CVH status in pregnancy was associated with lower neonatal size and lower risks for LGA and macrosomia in newborns.

BACKGROUND: Pregnancy acts as a cardiovascular stress test. Although many complications resolve following birth, women with hypertensive disorder of pregnancy have an increased risk of developing cardiovascular disease (CVD) long-term. Monitoring postnatal health can reduce this risk but requires better methods to identity high-risk women for timely interventions.
METHODS: Employing a qualitative descriptive study design, focus groups and/or interviews were conducted, separately engaging public contributors and clinical professionals. Diverse participants were recruited through social media convenience sampling. Semi-structured, facilitator-led discussions explored perspectives of current postnatal assessment and attitudes towards linking patient electronic healthcare data to develop digital tools for identifying postpartum women at risk of CVD. Participant perspectives were gathered using post-it notes or a facilitator scribe and analysed thematically.
RESULTS: From 27 public and seven clinical contributors, five themes regarding postnatal check expectations versus reality were developed, including \'limited resources\', \'low maternal health priority\', \'lack of knowledge\', \'ineffective systems\' and \'new mum syndrome\'. Despite some concerns, all supported data linkage to identify women postnatally, targeting intervention to those at greater risk of CVD. Participants outlined potential benefits of digitalisation and risk prediction, highlighting design and communication needs for diverse communities.
CONCLUSIONS: Current health system constraints in England contribute to suboptimal postnatal care. Integrating data linkage and improving education on data and digital tools for maternal healthcare shows promise for enhanced monitoring and improved future health. Recognised for streamlining processes and risk prediction, digital tools may enable more person-centred care plans, addressing the gaps in current postnatal care practice.

The impact of gestational diabetes mellitus (GDM) on maternal or infant microbiome trajectory remains poorly understood. Utilizing large-scale longitudinal fecal samples from 264 mother-baby dyads, we present the gut microbiome trajectory of the mothers throughout pregnancy and infants during the first year of life. GDM mothers had a distinct microbiome diversity and composition during the gestation period. GDM leaves fingerprints on the infant\'s gut microbiome, which are confounded by delivery mode. Further, Clostridium species positively correlate with a larger head circumference at month 12 in male offspring but not females. The gut microbiome of GDM mothers with male fetuses displays depleted gut-brain modules, including acetate synthesis I and degradation and glutamate synthesis II. The gut microbiome of female infants of GDM mothers has higher histamine degradation and dopamine degradation. Together, our integrative analysis indicates that GDM affects maternal and infant gut composition, which is associated with sexually dimorphic infant head growth.

BACKGROUND: Discharge \"against medical advice\" (AMA) in the obstetric population is overall under-studied but disproportionally affects marginalized populations and is associated with worse perinatal outcomes. Reasons for discharges AMA are not well understood. The objective of this study is to identify the obstacles that prevent obstetric patients from accepting recommended care and highlight the structural reasons behind AMA discharges.
METHODS: Electronic health records of patients admitted to antepartum, peripartum, or postpartum services between 2008 and 2018 who left \"AMA\" were reviewed. Progress notes from clinicians and social workers were extracted and analyzed. Reasons behind discharge were categorized using qualitative thematic analysis.
RESULTS: Fifty-seven (0.12%) obstetric patients were discharged AMA. Reasons for discharge were organized into two overarching themes: extrinsic (50.9%) and intrinsic (40.4%) obstacles to accepting care. Eleven participants (19.3%) had no reason documented for their discharge. Extrinsic obstacles included childcare, familial responsibilities, and other obligations. Intrinsic obstacles included disagreement with provider regarding medical condition or plan, emotional distress, mistrust or discontent with care team, and substance use.
CONCLUSIONS: The term \"AMA\" casts blame on individual patients and fails to represent the systemic barriers to staying in care. Obstetric patients were found to encounter both extrinsic and intrinsic obstacles that led them to leave AMA. Healthcare providers and institutions can implement strategies that ameliorate structural barriers. Partnering with patients to prevent discharges AMA would improve maternal and infant health and progress towards reproductive justice.

BACKGROUND: The COVID-19 pandemic resulted in extreme strain on health systems including the health workforce, essential health services and vaccination coverage. We examined disruptions to immunisation and maternal and child health (MCH) services, concerns of personal well-being and delivery of healthcare during the pandemic as well as factors associated with self-reported trauma or burnout among healthcare providers (HCPs).
METHODS: In March-April 2022, we conducted a cross-sectional survey among HCPs in two provinces of Indonesia. HCPs involved in COVID-19 or routine immunisation and MCH services were randomly selected from district/city health office registration lists. We descriptively analysed service disruptions experienced by HCPs as well as trauma, burnout and concerns of personal well-being and delivery of healthcare during the pandemic. Multivariate logistic regression analyses were undertaken to identify factors associated with trauma or burnout.
RESULTS: We recruited 604 HCPs. Mobilisation of staff from routine health services to COVID-19 response duties was a key reason for service disruptions (87.9%). Strategies such as community outreach and task shifting were implemented to overcome disruptions. Trauma or burnout during the pandemic was reported by 64.1% HCPs, with 23.5% reporting worse mental or emotional health.Factors associated with trauma or burnout included delivery of COVID-19 immunisation (adjusted OR (aOR) 2.54, 95% CI 1.08 to 5.94); and delivery of both COVID-19 immunisation and routine immunisation compared with no involvement in vaccination programmes (aOR 2.42, 95% CI 1.06 to 5.52); poor treatment in the workplace (aOR 2.26, 95% CI 1.51 to 3.38) and lower confidence to respond to patient queries on COVID-19 immunisation (aOR 1.51, 95% CI 1.03 to 2.22).
CONCLUSIONS: HCPs experienced service disruptions, trauma and burnout and implemented strategies to minimise disruptions to service delivery and improve patient experiences. Our study highlights the need to ensure that workforce resilience and strategies to protect and support HCPs are considered for pandemic planning, preparedness and management.

UNASSIGNED: Postpartum fatigue (PPF) can impair the physical and mental well-being of women. The aims of this study were to assess the associations between fatigue and maternal health-related variables, specifically, sleep quality, depression symptoms, and resilience, and to explore the moderating role of resilience in the relationships between sleep quality, depression symptoms, and fatigue.
UNASSIGNED: This cross-sectional study used data collected from mothers during the postpartum period via an online platform. PPF was assessed using the Fatigue Severity Scale, whereas sleep quality and depression symptoms were assessed using the Pittsburgh Sleep Quality Index and Edinburgh Postnatal Depression Scale, respectively. The Brief Resilience Scale was used to assess resilience. Simple and multiple binary logistic regression analyses were performed to examine the association of each independent variable with PPF and to determine the most significant predictors of PFF. The data were analyzed using SPSS, and structural equation modeling was performed using AMOS 23. A moderation analysis was performed to explore the moderating role of resilience using the Hayes PROCESS macro.
UNASSIGNED: A total of 1,443 postpartum mothers were included in the analysis. The simple binary logistic regression analysis showed that having chronic disease (odds: 1.52; p = 0.02), mother\'s age (odds: 0.97; p = 0.03), mother\'s body mass index (BMI; odds: 1.03; p = 0.01), depression symptoms (odds: 1.09; p ≤ 0.0001), sleep quality (odds: 1.17; p ≤ 0.0001), and resilience (odds: 0.42; p ≤ 0.0001) all contributed to fatigue during postpartum. Multivariate logistic regression showed that the mother\'s BMI, sleep quality, depression symptoms, and resilience were significant predictors of PPF. Moderation analyses showed that resilience was not a significant moderator between the main effects of sleep quality and fatigue (interaction effect: β = 0.01, p = 0.31, 95% CI: -0.01 to 0.04) or between the main effects of depression symptoms and fatigue during postpartum (interaction effect: β = 0.01, p = 0.82, 95% CI: -0.01 to 0.02).
UNASSIGNED: Given the deleterious effects of PPF on maternal health outcomes, factors associated with PPF should be assessed regularly. In addition to mothers\' BMI, sleep quality, and depression symptoms, resilience could also be a crucial factor in predicting fatigue severity during this critical time for mothers even though it was not a significant moderator among this sample.