Objective: To determine maternal and perinatal outcomes after induction of labor (IOL) at 39 weeks compared with expectant management.
Methods: This is a retrospective national cohort study from the National Center for Health Statistics birth database. The study included singleton, low-risk pregnancies with a non-anomalous fetus delivered at 39-42 weeks gestation between 2015 and 2018. Maternal outcomes available included chorioamnionitis (Triple I), blood transfusion, intensive care unit (ICU) admission, uterine rupture, cesarean delivery (CD), and cesarean hysterectomy. Fetal and infant outcomes included stillbirth, 5-min Apgar ≤3, prolonged ventilation, seizures, ICU admission, and death within 28 days. We compared women undergoing IOL at 39 weeks to those managed expectantly. Non-adjusted and adjusted relative risks (aRRs) were estimated using multivariate log-binomial regression analysis.
Results: There were 15,900,956 births available for review of which 5,017,524 met inclusion and exclusion criteria. For the maternal outcomes, the IOL group was less likely to require a CD (aRR 0.880; 95% CI [0.874-0.886]; value < .01) or develop Triple I (aRR 0.714; 95% CI [0.698-0.730]; value < .01) but demonstrated a small increase in the cesarean hysterectomy rate (aRR 1.231; 95% CI [1.029-1.472]; value < .01). Among perinatal outcomes, the stillbirth rate (aRR 0.195; 95% CI [0.153-0.249]; value < .01), 5-min Apgar ≤3 (aRR 0.684; 95% CI [0.647-0.723]; value < .01), prolonged ventilation (aRR 0.840; 95% CI [0.800-0.883]; value < .01), neonatal intensive care (NICU) admission (aRR 0.862; 95% CI [0.849-0.875]; value < .01) were lower after 39 week IOL compared with expectant management. There were no differences in risk for neonatal seizures (aRR 0.848; 95% CI [0.718-1.003]; value 0.011) or death (aRR 1.070; 95% CI [0.722-1.586]; value 0.660).
Conclusions: IOL at 39 weeks of gestation in a low-risk cohort is associated with a lower risk of CD and maternal infection, stillbirth, and lower neonatal morbidity. There was no effect on the risk for neonatal seizures or death.
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http://dx.doi.org/10.1080/14767058.2021.2021396 | DOI Listing |
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Biotechnology Research Center, Yazd Reproductive Sciences Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Islamic Republic of Iran.
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University College of Applied Sciences in Chełm, Pocztowa 54, Chełm, 22-100, Poland.
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January 2025
Department of Environmental Sciences & Engineering, Faculty of Agriculture & Natural Resources, Ardakan University, Ardakan, Iran.
Assessing the impact of climate change on water-related ecosystem services (ES) in Protected Areas (PAs) is essential for developing soil and water conservation strategies that promote sustainability and restore ES. However, the application of ES research in Protected Area (PA) management remains ambiguous and has notable shortcomings. This study primarily aimed to assess the SDR-InVEST (Sediment Delivery Ratio-Integrated Valuation of Ecosystem Services and Tradeoffs) model for estimating ES, including soil loss, sediment export, and sediment retention, under various climate change scenarios from 1997 to 2100 in the data-scarce region of the Bagh-e-Shadi Forest PA.
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January 2025
School of Mathematics and Statistics, Shaoguan University, Shaoguan, 512005, China.
Recently, deep latent variable models have made significant progress in dealing with missing data problems, benefiting from their ability to capture intricate and non-linear relationships within the data. In this work, we further investigate the potential of Variational Autoencoders (VAEs) in addressing the uncertainty associated with missing data via a multiple importance sampling strategy. We propose a Missing data Multiple Importance Sampling Variational Auto-Encoder (MMISVAE) method to effectively model incomplete data.
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January 2025
Computational Learning Theory Team, RIKEN-Advanced Intelligence Project, Fukuoka, 819-0395, Japan.
Providing continuous wireless connectivity for high-speed trains (HSTs) is challenging due to their high speeds, making installing numerous ground base stations (BSs) along the HST route an expensive solution, particularly in rural and wilderness areas. This paper proposes using multiple unmanned aerial vehicles (UAVs) to deliver high data rate wireless connectivity for HSTs, taking advantage of their ability to fly, hover, and maneuver at low altitudes. However, autonomously selecting the optimal UAV by the HST is challenging.
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