Induction of labor is one of the most common procedures in modern obstetrics, with an incidence of approximately 20% of all deliveries. Not all of these inductions result in vaginal delivery; some lead to cesarean sections, either for emergency reasons or for failed induction. That's why, It seems necessary to outline strategies for the improvement of the success rate of induced deliveries. Traditionally, the identification of women in whom labor induction is more likely to be successful is based on the Bishop score. However, several studies have shown it to be subjective, with high variation and a poor predictor of the outcome of labor induction. Transvaginal sonography for cervical measurement can be a more objective criterion in assessing the success of labor induction. Many studies have been done recently to compare cervical measurement and Bishop Score in labor induction.This paper reviewed the literature that evaluated sonographic cervical length measurement to predict induction of labor outcome.
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http://dx.doi.org/10.3233/NPM-16915111 | DOI Listing |
BMC Womens Health
December 2024
Departments of Pediatrics & Child Health Nursing, Institutes of Health Sciences, Wollega University, Nekemte, Ethiopia.
Background: Globally, there has been an explosive rise in the cesarean section rate that exceeds the World Health Organization rate of 10-15% and in the past fifteen years the rates was doubled in some countries including Ethiopia. Therefore, it is essential to recognize the current magnitude and the factors that contribute to increasing cesarean section rates beyond the World Health Organization recommendations and specifically in the study areas.
Objective: This study aimed to assess the magnitude of cesarean sections and its associated factors among mothers who gave birth in public hospitals in East Wollega Zone, Oromia Ethiopia 2022.
Sci Rep
December 2024
Department of Epidemiology and biostatistics, Institute of Public Health, College of Medicine and Health Sciences, University of Gondar, Gondar, Ethiopia.
Birth asphyxia is a well-known cause of neonatal mortality, and the survivors suffer from long-lasting sequels such as seizures, intellectual disabilities, and motor disorders that are great challenges for newborns. Elucidating the determinants of birth asphyxia helps implement evidence-based practice in the local context. Thus, this study aimed at elucidating the determinants of birth asphyxia in urban south Ethiopia.
View Article and Find Full Text PDFMCN Am J Matern Child Nurs
October 2024
Samantha L. Bernstein is an Assistant Professor at MGH Institute of Health Professions, Boston, MA, and is an MCN Editorial Board member. Dr. Bernstein can be reached at
Brief Bioinform
November 2024
Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning, Central China Normal University, Wuhan 430079, China.
Identifying phage-host interactions (PHIs) is a crucial step in developing phage therapy, which is the promising solution to addressing the issue of antibiotic resistance in superbugs. However, the lifestyle of phages, which strongly depends on their host for life activities, limits their cultivability, making the study of predicting PHIs time-consuming and labor-intensive for traditional wet lab experiments. Although many deep learning (DL) approaches have been applied to PHIs prediction, most DL methods are predominantly based on sequence information, failing to comprehensively model the intricate relationships within PHIs.
View Article and Find Full Text PDFAm J Obstet Gynecol
December 2024
Fetal Medicine Research Institute, King's College Hospital, London, UK.
Background: Previous studies demonstrated that placental dysfunction leads to intrapartum fetal distress, particularly when an abnormal pattern of angiogenic markers is demonstrated at 36 weeks of gestation. Prediction of intrapartum fetal compromise is particularly important in patients undergoing induction of labor due to different indications for delivery, as this can be a useful in optimizing the method and timing of the induction.
Objective: To examine whether the risk of preeclampsia assessed by the Fetal Medicine Foundation (FMF) algorithm (derived from a combination of maternal risk factors, mean arterial pressure, placental growth factor and soluble fms-like tyrosine kinase-1), associates with the risk of intrapartum fetal compromise requiring cesarean delivery, in a population of singleton pregnancies undergoing labor induction for various indications.
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