Naegele's rule and the length of pregnancy - A review

The mediating role of trust in government in intergenerational transmission of fertility intentions

China's one-child policy was in effect from 1982 to 2015. However, the literature examining the association between people's trust in local government and intergenerational transmission of fertility intentions is scarce. To fill this gap, we investigated the impact of individuals' sibship size on their ideal number of children, the mediating effect of their trust in local government on the issue of fertility between two successive generations, and the moderating effect of education level on sibship size related to trust in local governments. Based on the 2019 Chinese Social Survey data, 2,340 respondents aged 18-35 participated in the analysis. The results showed that (i) individuals' number of siblings significantly positively predicted their ideal number of children; (ii) individuals' number of siblings significantly negatively predicted their trust in the local government, which in turn significantly negatively influenced fertility intentions; (iii) the mediating mechanism was significant in residents with higher levels of education, but not in people with lower degrees of education. Fertility-boosting incentives can prioritize couples who are the only child in their family. It is necessary for local governments to improve their credibility and strengthen their pregnancy-related communication with groups with higher levels of education.

Estimating gestational age using the anthropometric measurements of newborns in North Shewa Zone public hospitals, Oromia, Ethiopia

Background

The accurate estimation of gestational age is crucial in identifying prematurity and other health problems in newborns and in providing appropriate perinatal care. Although there are numerous methods for measuring gestational age, they are not always applicable. During these situations, it becomes challenging to ascertain whether a baby has been born prematurely or not. Therefore, this study aims to estimate gestational age by utilizing newborn anthropometric parameters.

Purpose

The objective of this study is to estimate the gestational age of newborns in public hospitals located in the North Shewa Zone of the Oromia Region in Ethiopia, by using anthropometric parameters.

Methods

A cross-sectional study was conducted at a facility from February 2022 to April 2022, using an interview-based questionnaire and anthropometric measurements. The anthropometric parameters that were measured include foot length (FL), mid-upper arm circumference (MUAC), and chest and head circumference (CHC). The study's sample size had a total of 420 participants. The data were cleaned, edited, manually checked for completeness, and entered into Epi-data version 3.1. Subsequently, the data were transferred into SPSS for analysis. The data were analyzed using descriptive analysis, simple linear regression, and multiple linear regressions. Finally, the data were presented using statements and tables.

Results

There is a significant and positive correlation between anthropometric parameters, including head circumference (r: 0.483), MUAC (r: 0.481), foot length (r: 0.457), and chest circumference (r: 0.482) with gestational age. All anthropometric parameters demonstrated positive and significant estimates of gestational age. The combination of the four measurements yielded the strongest estimate of gestational age. Gestational age can be calculated by the formula: Gestational age (Weeks) = 9.78 + 0.209*CHC + 0.607*MUAC + 0.727*FL + 0.322*HC.

Conclusion

Gestational age can be measured using head circumference, mid-upper arm circumference, foot length, and chest circumference. Utilizing the four anthropometric parameters in combination exhibits greater efficacy in estimating gestational age than using them individually. Therefore, it is recommended to use these alternative approaches when standard methods are not applicable.

Preterm pigs for preterm birth research: reasonably feasible

Preterm birth will disrupt the pattern and course of organ development, which may result in morbidity and mortality of newborn infants. Large animal models are crucial resources for developing novel, credible, and effective treatments for preterm infants. This review summarizes the classification, definition, and prevalence of preterm birth, and analyzes the relationship between the predicted animal days and one human year in the most widely used animal models (mice, rats, rabbits, sheep, and pigs) for preterm birth studies. After that, the physiological characteristics of preterm pig models at different gestational ages are described in more detail, including birth weight, body temperature, brain development, cardiovascular system development, respiratory, digestive, and immune system development, kidney development, and blood constituents. Studies on postnatal development and adaptation of preterm pig models of different gestational ages will help to determine the physiological basis for survival and development of very preterm, middle preterm, and late preterm newborns, and will also aid in the study and accurate optimization of feeding conditions, diet- or drug-related interventions for preterm neonates. Finally, this review summarizes several accepted pediatric applications of preterm pig models in nutritional fortification, necrotizing enterocolitis, neonatal encephalopathy and hypothermia intervention, mechanical ventilation, and oxygen therapy for preterm infants.

Hierarchical Attentive Network for Gestational Age Estimation in Low-Resource Settings

Assessing fetal development is essential to the provision of healthcare for both mothers and fetuses. In low- and middle-income countries, conditions that increase the risk of fetal growth restriction (FGR) are often more prevalent. In these regions, barriers to accessing healthcare and social services exacerbate fetal maternal health problems. One of these barriers is the lack of affordable diagnostic technologies. To address this issue, this work introduces an end-to-end algorithm applied to a low-cost, hand-held Doppler ultrasound device for estimating gestational age (GA), and by inference, FGR. The Doppler ultrasound signals used in this study were collected from 226 pregnancies (45 low birth weight at delivery) between 5 and 9 months GA by lay midwives in highland Guatemala. We designed a hierarchical deep sequence learning model with an attention mechanism to learn the normative dynamics of fetal cardiac activity in different stages of development. This resulted in a state-of-the-art GA estimation performance, with an average error of 0.79 months. This is close to the theoretical minimum for the given quantization level of one month. The model was then tested on Doppler recordings of the fetuses with low birth weight and the estimated GA was shown to be lower than the GA calculated from last menstruation. Thus, this could be interpreted as a potential sign of developmental retardation (or FGR) associated with low birth weight, and referral and intervention may be necessary.

Human development and reproduction in space-a European perspective

This review summarises key aspects of the first reproductive and developmental systems Science Community White Paper, supported by the European Space Agency (ESA). Current knowledge regarding human development and reproduction in space is mapped to the roadmap. It acknowledges that sex and gender have implications on all physiological systems, however, gender identity falls outside the scope of the document included in the white paper collection supported by ESA. The ESA SciSpacE white papers on human developmental and reproductive functions in space aim to reflect on the implications of space travel on the male and female reproductive systems, including the hypothalamic-pituitary-gonadal (HPG) reproductive hormone axis, and considerations for conception, gestation and birth. Finally, parallels are drawn as to how this may impact society as a whole on Earth.

Estimated date of delivery with electronic medical records by a hybrid GBDT-GRU model

An accurate estimated date of delivery (EDD) helps pregnant women make adequate preparations before delivery and avoid the panic of parturition. EDD is normally derived from some formulates or estimated by doctors based on last menstruation period and ultrasound examinations. This study attempted to combine antenatal examinations and electronic medical records to develop a hybrid model based on Gradient Boosting Decision Tree and Gated Recurrent Unit (GBDT-GRU). Besides exploring the features that affect the EDD, GBDT-GRU model obtained the results by dynamic prediction of different stages. The mean square error (MSE) and coefficient of determination (R²) were used to compare the performance among the different prediction methods. In addition, we evaluated predictive performances of different prediction models by comparing the proportion of pregnant women under the error of different days. Experimental results showed that the performance indexes of hybrid GBDT-GRU model outperformed other prediction methods because it focuses on analyzing the time-series predictors of pregnancy. The results of this study are helpful for the development of guidelines for clinical delivery treatments, as it can assist clinicians in making correct decisions during obstetric examinations.