54 papers
Obstetrics and gynecology encompasses the vital care of women's health throughout life, from reproductive wellness and pregnancy to menopause and beyond. This dynamic field explores the complex biological processes of childbirth, the prevention of diseases affecting female reproductive organs, and the latest advancements in maternal safety. It is a discipline deeply rooted in both immediate clinical impact and long-term public health strategies.
On Gist.Science, we continuously monitor medRxiv for the newest preprints in this category, ensuring you have instant access to cutting-edge research before formal publication. Our team processes every new submission to provide both detailed technical summaries and clear, plain-language explanations, making these complex studies understandable for everyone from specialists to curious readers.
Below are the latest papers in obstetrics and gynecology, offering fresh insights into the future of women's healthcare.
This study of fetal monitors at Mongolia's Urgo Maternity Hospital identifies that device failures stem from a combination of technical issues like power instability and wear, alongside human factors such as insufficient staff training and improper use, necessitating a comprehensive approach involving regular maintenance, power stabilization, and enhanced personnel education to ensure reliable operation.
This study of nearly 1.85 million California births reveals that while pregnancy-related comorbidities significantly contribute to severe maternal morbidity disparities among Asian American and Pacific Islander groups, substantial disparities persist for Filipina and Pacific Islander women even after accounting for these conditions, highlighting the need for tailored interventions beyond comorbidity management.
The Cohort for Risk Prediction Model Evaluation (CORE) is a prospective, single-site Indian cohort of 964 pregnant women established to externally validate early second-trimester risk prediction models for high-risk pregnancies using harmonized clinical and ultrasound data, with the goal of improving maternal and neonatal outcomes in India and comparable settings.
This study identifies a prognostic signature based on m6A regulators and autophagy-associated genes in ovarian cancer, constructing a risk score and nomogram that effectively predict patient outcomes, immunotherapy response, and drug susceptibility while validating key genes like PLK2 and LEPR.
In a nationwide Belgian cohort, the prevalence of hyperglycemia in pregnancy significantly increased during the latter half of 2020 compared to 2019, showing a strong positive correlation with the pandemic's Stringency Index, while neonatal weight percentiles remained unchanged.
This study utilizes self-tracked urinary hormone data to develop an autoregressive Hidden Markov model that accurately maps menstrual cycle phases, revealing distinct hormonal differences in women with polyendocrine metabolic ovarian syndrome (PMOS) and demonstrating the model's potential for non-invasive PMOS screening and improved clinical testing protocols.
This study demonstrates that supervised machine learning models trained on linked mother-infant electronic health records can accurately and generalizably estimate gestational age at delivery across different health systems, providing a robust framework to support large-scale maternal and neonatal health research.
Through a three-phase consensus process involving systematic reviews, a Delphi survey, and stakeholder meetings, this study identified 62 priority maternal and child outcomes to be included in a decision aid that supports informed choices between planned vaginal and caesarean births.
This manuscript regarding longitudinal antenatal care quality and postpartum health in Ethiopia, India, Kenya, and South Africa has been withdrawn by the authors to finalize their work and should not be cited.
The INSIGHT study is a large, prospective UK cohort that established a deeply phenotyped dataset of 2,272 pregnant women to identify early biomarkers for spontaneous preterm birth by integrating multi-omic analyses of the innate immune response, vaginal microbiome, and host biology, ultimately demonstrating that maternal plasma cfRNA and combined biological markers can predict risk months before clinical presentation.