UNASSIGNED: Prevention of HIV vertical transmission programmes (VTPs) in South Africa has decreased paediatric HIV. These programmes require integration in referral hospitals.
UNASSIGNED: To determine knowledge of and attitudes to the national VTP guidelines in staff from Obstetric and Paediatric disciplines at two referral hospitals.
UNASSIGNED: Using a cross-sectional design, a questionnaire to assess knowledge of the guidelines and attitudes (awareness, ease-of-use and non-silo practice, measuring integrated practice) was developed and validated locally. Using standard statistical analyses, data from these questionnaires were used to draw comparisons and determine factors associated with knowledge and attitudes.
UNASSIGNED: Of the 249 participants, 138 (55.4%) were in obstetrics, 125 (50.2%) were nurses, and 168 (67.5%) self-identified as junior staff. Knowledge scores were good, median score (Q1-Q3) was 91.7% (79.1-95.8), and higher in those who had discipline-specific training (P = 0.003). Junior staff (P = 0.002) had higher knowledge levels than senior staff. Most (80%) found the guidelines easy to use and had good awareness, which correlated with knowledge and training. Gaps included understanding of antenatal testing of HIV-negative women and timelines for neonatal HIV testing. Staff scored poorly on integrated practice; the median score (Q1-Q3) was 50% (33.3-58.3), which was inversely correlated with knowledge (r= -0.146, n = 249, P = 0.022).
UNASSIGNED: Staff in referral hospitals appear to be practising within silos when implementing VTPs, and this may result in failures to ensure integrated practice. Regularised interdisciplinary and interprofessional training may be important to ensure the integrated implementation of VTPs in referral hospitals.

UNASSIGNED: This module teaches core knowledge and skills for undergraduate medical education in reproductive health, providing instruction in the management of normal and abnormal pregnancy and labor utilizing interactive small-group flipped classroom methods and case-based instruction.
UNASSIGNED: Advance preparation materials were provided before the education session. The 2-hour session was facilitated by clinical educators using a faculty guide. Using voluntary surveys, we collected data to measure satisfaction among obstetrics and gynecology clerkship students and facilitators following each education session.
UNASSIGNED: Capturing six clerkships spanning 9 months, 116 students participated, and 64 students completed the satisfaction survey, with 97% agreeing that the session was helpful in applying knowledge and principles to common clinical scenarios. Most students (96%) self-reported that they achieved the session\'s learning objectives utilizing prework and interactive small-group teaching. Nine clinical instructors completed the survey; all agreed the provided materials allowed them to facilitate active learning, and the majority (89%) agreed they spent less time preparing to teach this curriculum compared to traditional didactics.
UNASSIGNED: This interactive flipped classroom session meets clerkship learning objectives related to the management of pregnancy and labor using standardized materials. The curriculum reduced preparation time for clinical educators as well.

UNASSIGNED: Laparoscopic surgery requires significant training, and prior studies have shown that surgical residents lack key laparoscopic skills. Many educators have implemented simulation curricula to improve laparoscopic training. Given limited time for dedicated, in-person simulation center practice, at-home training has emerged as a possible mechanism by which to expand training and promote practice. There remains a gap in published at-home laparoscopic curricula employing embedded feedback mechanisms.
UNASSIGNED: We developed a nine-task at-home laparoscopic curriculum and an end-of-curriculum assessment following Kern\'s six-step approach. We implemented the curriculum over 4 months with first- to third-year residents.
UNASSIGNED: Of 47 invited residents from general surgery, obstetrics/gynecology, and urology, 37 (79%) participated in the at-home curriculum, and 25 (53%) participated in the end-of-curriculum assessment. Residents who participated in the at-home curriculum completed a median of six of nine tasks (interquartile range: 3-8). Twenty-two residents (47%) responded to a postcurriculum survey. Of these, 19 (86%) reported that their laparoscopic skills improved through completion of the curriculum, and the same 19 (86%) felt that the curriculum should be continued for future residents. Residents who completed more at-home curriculum tasks scored higher on the end-of-curriculum assessment (p = .009 with adjusted R 2 of .28) and performed assessment tasks in less time (p = .004 with adjusted R 2 of .28).
UNASSIGNED: This learner-centered laparoscopic curriculum provides guiding examples, spaced practice, feedback, and graduated skill development to enable junior residents to improve their laparoscopic skills in a low-stakes, at-home environment.

Obstetric antiphospholipid syndrome (OAPS) is an autoimmune disorder associated with various pathological pregnancies, such as recurrent miscarriage, stillbirth, severe pre-eclampsia and severe placental insufficiency. The persistent presence of antiphospholipid antibodies (aPLs) is the most important laboratory characteristic of OAPS. OAPS severely affects the reproductive health of women of childbearing age in China. Reports indicate that approximately 9.6% stillbirths, 11.5% severe pre-eclampsia, and 54% recurrent miscarriages are associated with OAPS or aPLs. However, the pathogenesis of OAPS remains unclear. Previously, thrombosis at the maternal-fetal interface (MFI) was considered the main mechanism of OAPS-related pathological pregnancies. Consequently, the use of low molecular weight heparin and aspirin throughout pregnancy was recommended to improve outcomes in OAPS patient. In recent years, many studies have found that thrombosis in MFI is uncommon, but various inflammatory factors are significantly increased in the MFI of OAPS patients. Based on these findings, some clinicians have started using anti-inflammatory treatments for OAPS, which have preliminarily improved the pregnancy outcomes. Nevertheless, there is no consensus on these second-line treatments of OAPS. Another troubling issue is the clinical diagnosis of OAPS. Similar to other autoimmune diseases, there are only classification criteria for OAPS, and clinical diagnosis of OAPS depends on the clinicians\' experience. The present classification criteria of OAPS were established for clinical and basic research purposes, not for patient clinical management. In clinical practice, many patients with both positive aPLs and pathological pregnancy histories do not meet the strict OAPS criteria. This has led to widespread issues of incorrect diagnosis and treatment. Timely and accurate diagnosis of OAPS is crucial for effective treatment. In this article, we reviewed the epidemiological research progress on OAPS and summarized its classification principles, including: 1) the persistent presence of aPLs in circulation; 2) manifestations of OAPS, excluding other possible causes. For the first point, accurate assessment of aPLs is crucial; for the latter, previous studies regarded only placenta-related pregnancy complications as characteristic manifestations of OAPS. However, recent studies have indicated that adverse pregnancy outcomes related to trophoblast damage, such as recurrent miscarriage and stillbirth, also need to be considered in OAPS. We also discussed several key issues in the diagnosis and treatment of OAPS. First, we addressed the definition of non-standard OAPS and offered our opinion on defining non-standard OAPS within the framework of the 2023 American College of Rheumatology (ACR)/European League Against Rheumatism (EULAR) APS criteria. Then, we discussed the advantages and disadvantages of different aPL testing methods, emphasizing that harmonizing results across platforms and establishing specific reference values are keys to resolving controversies in aPL testing results. We also introduced the application of non-criteria aPLs, especially anti-phosphatidylserine/prothrombin antibody (aPS/PT) and anti-β2 glycoprotein Ⅰ domain Ⅰ antibody (aβ2GPⅠDⅠ). Additionally, we discussed aPL-based OAPS risk classification strategies. Finally, we proposed potential treatment methods for refractory OAPS. The goal is to provide a reference for the clinical management of OAPS.

Introduction The World Health Organization (WHO) Safe Surgery Checklist significantly decreases morbidity and mortality in regular operating room cases. However, significant differences in workflow and processes exist between regular operating room cases and cesarean sections performed on the labor and delivery unit. The aim of this study is to adapt the WHO Safe Surgery Checklist for the labor and delivery unit and cesarean sections to improve communication and patient safety. Methods A multidisciplinary team consisting of all major stakeholders reviewed and revised the WHO Safe Surgery Checklist making it more applicable to cesarean section operations. The new Safe Cesarean Section Checklist was tested and then integrated into the electronic medical record and utilized on the labor and delivery unit. A specific cesarean section safety attitudes questionnaire was developed, validated, and administered prior to and one year after implementation. Results Usage of the Safe Cesarean Section Checklist was greater than 95% after initial implementation. Significant improvements were reported by the staff on the cesarean section attitudes questionnaire for several key areas including the feeling that all necessary information was available at the beginning of the procedure, decreases in communication breakdowns and delays, and fewer issues related to not knowing who was in charge during the procedure. Discussion Implementation of the Safe Cesarean Section Checklist was successfully adopted by the staff, and improvements in staff perceptions of several key safety issues on our unit were demonstrated. Additional studies should be undertaken to determine if clinical outcomes from this intervention are comparable to those seen with the use of the WHO Safe Surgery Checklist.

Purpose  To introduce the cranial-dorsal-hip angle (∠CDH) as a novel quantitative tool for assessing fetal position in the first trimester and to validate its feasibility for future AI applications. Materials and Methods  2520 first-trimester fetal NT exams with 2582 CRL images (January-August 2022) were analyzed at a tertiary hospital as the pilot group. Additionally, 1418 cases with 1450 fetal CRL images (September-December 2022) were examined for validation. Three expert sonographers defined a standard for fetal positions. ∠CDH measurements, conducted by two ultrasound technicians, were validated for consistency using Bland-Altman plots and the intra-class correlation coefficient (ICC). This method allowed for categorizing fetal positions as hyperflexion, neutral, and hyperextension based on ∠CDH. Comparative accuracy was assessed against Ioannou, Wanyonyi, and Roux methods using the weighted Kappa coefficient (k value). Results  The pilot group comprised 2186 fetal CRL images, and the validation group included 1193 images. Measurement consistency was high (ICCs of 0.993; P<0.001). The established 95% reference range for ∠CDH in the neutral fetal position was 118.3° to 137.8°. The ∠CDH method demonstrated superior accuracy over the Ioannou, Wanyonyi, and Roux methods in both groups, with accuracy rates of 94.5% (k values: 0.874, 95%CI: 0.852-0.896) in the pilot group, and 92.6% (k values: 0.838, 95%CI: 0.806-0.871) in the validation group. Conclusion  The ∠CDH method has been validated as a highly reproducible and accurate technique for first-trimester fetal position assessment. This sets the stage for its potential future integration into intelligent assessment models.

UNASSIGNED: Congenital heart disease (CHD) affects 8 in 1,000 live births with significant postnatal implications including growth failure, neurodevelopmental delay, and mortality. The placenta develops concomitantly with the fetal heart. High rates of placental pathology and discordant growth in pregnancies affected by CHD highlight the significance of the fetal-placental-cardiac axis.
UNASSIGNED: This study aimed to characterize the relationship between neonatal birthweight (BW), head circumference, placental weight (PW), and placental pathology in pregnancies affected by CHD. PW:BW provides a surrogate to assess placental efficiency, or nutrient exchange and delivery by the placenta, across CHD phenotypes.
UNASSIGNED: Retrospective cohort of 139 live-born singletons with postnatally confirmed CHD with placental pathology. Placental examination, infant BW, head circumference, and CHD categories (septal defects, right-sided defects, left-sided defects, conotruncal anomalies, and others) were included. Chi-square, Fisher\'s exact, or Kruskall-Wallis tests and multinomial logistic regressions, as appropriate.
UNASSIGNED: Median birthweight and head circumference percentile was 33 and 35, respectively. Placental pathology was documented in 37% of cases. PW to BW ratios were <10th percentile for 78% and <3rd percentile for 54% of the cohort, with no difference between CHD categories (P = 0.39 and P = 0.56, respectively).
UNASSIGNED: Infants with CHD have preserved BW and head circumferences in the setting of small placentas and increased prevalence of placental pathology, suggesting placental efficiency. Detection of abnormal placental growth could add prenatal diagnostic value. Placental and neonatal discordant growth may allude to a vascular anomaly predisposing fetuses to developing CHD. Further studies are needed to explore fetal nutrient delivery and utilization efficiency.

BACKGROUND: Current postpartum hemorrhage (PPH) risk stratification is based on traditional statistical models or expert opinion. Machine learning could optimize PPH prediction by allowing for more complex modeling.
OBJECTIVE: We sought to improve PPH prediction and compare machine learning and traditional statistical methods.
METHODS: We developed models using the Consortium for Safe Labor data set (2002-2008) from 12 US hospitals. The primary outcome was a transfusion of blood products or PPH (estimated blood loss of ≥1000 mL). The secondary outcome was a transfusion of any blood product. Fifty antepartum and intrapartum characteristics and hospital characteristics were included. Logistic regression, support vector machines, multilayer perceptron, random forest, and gradient boosting (GB) were used to generate prediction models. The area under the receiver operating characteristic curve (ROC-AUC) and area under the precision/recall curve (PR-AUC) were used to compare performance.
RESULTS: Among 228,438 births, 5760 (3.1%) women had a postpartum hemorrhage, 5170 (2.8%) had a transfusion, and 10,344 (5.6%) met the criteria for the transfusion-PPH composite. Models predicting the transfusion-PPH composite using antepartum and intrapartum features had the best positive predictive values, with the GB machine learning model performing best overall (ROC-AUC=0.833, 95% CI 0.828-0.838; PR-AUC=0.210, 95% CI 0.201-0.220). The most predictive features in the GB model predicting the transfusion-PPH composite were the mode of delivery, oxytocin incremental dose for labor (mU/minute), intrapartum tocolytic use, presence of anesthesia nurse, and hospital type.
CONCLUSIONS: Machine learning offers higher discriminability than logistic regression in predicting PPH. The Consortium for Safe Labor data set may not be optimal for analyzing risk due to strong subgroup effects, which decreases accuracy and limits generalizability.

Dr. Virginia Apgar was an American anesthesiologist and researcher who heavily influenced the development of neonatal resuscitation in the immediate postpartum period with her simple five-point scoring system. Today, the APGAR scoring system is used around the world in delivery rooms to guide clinicians in the evaluation of newborns and to distinguish which might need urgent resuscitation. With a simple scoring system, timer, and clipboard, Dr. Virginia Apgar shifted focus from the parturient to the neonate, improving infant mortality as a result.

Gestational Diabetes Mellitus (GDM) poses significant health risks to mothers and infants. Early prediction and effective management are crucial to improving outcomes. Machine learning techniques have emerged as powerful tools for GDM prediction. This review compiles and analyses the available studies to highlight key findings and trends in the application of machine learning for GDM prediction. A comprehensive search of relevant studies published between 2000 and September 2023 was conducted. Fourteen studies were selected based on their focus on machine learning for GDM prediction. These studies were subjected to rigorous analysis to identify common themes and trends. The review revealed several key themes. Models capable of predicting GDM risk during the early stages of pregnancy were identified from the studies reviewed. Several studies underscored the necessity of tailoring predictive models to specific populations and demographic groups. These findings highlighted the limitations of uniform guidelines for diverse populations. Moreover, studies emphasised the value of integrating clinical data into GDM prediction models. This integration improved the treatment and care delivery for individuals diagnosed with GDM. While different machine learning models showed promise, selecting and weighing variables remains complex. The reviewed studies offer valuable insights into the complexities and potential solutions in GDM prediction using machine learning. The pursuit of accurate, early prediction models, the consideration of diverse populations, clinical data, and emerging data sources underscore the commitment of researchers to improve healthcare outcomes for pregnant individuals at risk of GDM.