scholarly journals Fetal growth prediction: Establishing fetal growth prediction curves in the second trimester

2021 ◽  
Vol 29 ◽  
pp. 345-350
Author(s):  
Yan Wang ◽  
Xinyu Bao ◽  
Song Zhang ◽  
Lin Yang ◽  
Guoli Liu ◽  
...  
Keyword(s):  
Birth Weight ◽  
Fetal Growth ◽  
Growth Curve ◽  
Stepwise Regression ◽  
Fetal Weight ◽  
Maternal Height ◽  
Second Trimester ◽  
Growth Prediction ◽  
Curve Model ◽  
Input Model

BACKGROUND: Monitoring fetal weight during pregnancy has a guiding role in prenatal care. OBJECTIVE: To establish a personalized fetal growth curve for effectively monitoring fetal growth during pregnancy. METHODS: (1) This study retrospectively analyzed the birth weight database of 2,474 singleton newborns delivered normally at term. The personalized fetal growth curve model was formed by combining the estimating birth weight of newborns with the proportional weight formula. (2) Multiple linear stepwise regression method was used to estimate the birth weight of newborns. RESULTS: (1) Delivery gestational age, weight at first visit, maternal height, pre-pregnancy body mass index, fetal sex, parity had significant effects on birth weight. Based on these parameters, the formula for calculating term optimal weight was obtained (R2= 22.8%, P< 0.001). (2) The personalized fetal growth curve was obtained according to the epidemiological factors input model of each pregnant woman. CONCLUSIONS: A model of personalized fetal growth curve can be established, and be used to evaluate fetal growth and development through estimated fetal weight monitoring.

scholarly journals Establishment of a personalized fetal growth curve model

2021 ◽  
Vol 29 ◽  
pp. 311-317
Author(s):  
Xinyu Bao ◽  
Yan Wang ◽  
Song Zhang ◽  
Lin Yang ◽  
Guoli Liu ◽  
...  
Keyword(s):  
Birth Weight ◽  
Fetal Growth ◽  
Growth Curve ◽  
Growth And Development ◽  
Fetal Weight ◽  
Growth Curve Model ◽  
Normal Range ◽  
Normal Term ◽  
Curve Model ◽  
Gestational Week

BACKGROUND: Fetal weight is one of the important indicators for judging whether fetal growth and development are normal. Fetal weight exceeding the normal range may lead to poor delivery outcomes. OBJECTIVE: We aimed to establish a personalized fetal growth curve in order to effectively monitor fetal growth during pregnancy. Fetal weight can be monitored while fetal growth and development are assessed. METHODS: This study retrospectively analyzed the birth weight and ultrasound database of 3,093 newborns delivered at normal term. The personalized fetal growth curve model was generated based on the birth weight formula established by Gardosi combined with the proportional weight equation. RESULTS: (1) The average birth weight of the single fetus at normal term was 3,457g. (2) According to the regression results of the proportion of fetal weight in full-term pregnancy and gestational week, the proportional weight equation is Weight% = 500.9 - 51.60GA + 1.727GA2- 0.01718GA3 (GA is gestational week), R2 is 98%, P< 0.001. CONCLUSIONS: In this study, the normal birth weight of newborns and normal range of fetal weight can be estimated by using the personalized fetal growth curve model.

scholarly journals Prediction of late-onset fetal growth restriction using a combined first- and second-trimester screening model in South Chinese infants: a retrospective study

2019 ◽  
Author(s):  
Haiqing Zheng ◽  
Yan Feng ◽  
Jiexin Zhang ◽  
Kuanrong Li ◽  
Huiying Liang ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Birth Weight ◽  
Fetal Growth ◽  
Fetal Growth Restriction ◽  
Detection Rate ◽  
Prediction Models ◽  
Late Onset ◽  
Growth Restriction ◽  
Abdominal Circumference ◽  
Second Trimester

Abstract Background Prediction models for early and late fetal growth restriction (FGR) have been established in many high-income countries. However, prediction models for late FGR in China are limited. This study aimed to develop a simple combined first- and second-trimester prediction model for screening late-onset FGR in South Chinese infants.Methods This retrospective study included 2258 women who had singleton pregnancies and received routine ultrasound scans. Late-onset FGR was defined as a birth weight < the 10th percentile plus abnormal Doppler indices and/or a birth weight below the 3rd percentile after 32 weeks, regardless of the Doppler status. Multivariate logistic regression was used to develop a prediction model.Results Ninety-three fetuses were identified as late-onset FGR. The significant predictors for late-onset FGR were maternal age, height, weight, and medical history; the second-trimester head circumference (HC)/abdominal circumference (AC) ratio; and the estimated fetal weight (EFW). This model achieved a detection rate (DR) of 52.6% for late-onset FGR at a 10% false positive rate (FPR) (area under the curve (AUC): 0.80, 95%CI 0.76-0.85).Conclusions A multivariate model combining first- and second-trimester default tests can detect 52.6% of cases of late-onset FGR. Further studies with more screening markers are needed to improve the detection rate.

scholarly journals Prediction of late-onset fetal growth restriction using a combined first- and second-trimester screening model in South Chinese infants: a retrospective study

2020 ◽  
Author(s):  
Haiqing Zheng ◽  
Yan Feng ◽  
Jiexin Zhang ◽  
Kuanrong Li ◽  
Huiying Liang ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Birth Weight ◽  
Prediction Model ◽  
Fetal Growth ◽  
Fetal Growth Restriction ◽  
Detection Rate ◽  
Prediction Models ◽  
Late Onset ◽  
Validation Dataset ◽  
Second Trimester

Abstract Background: Prediction models for early and late fetal growth restriction (FGR) have been established in many high-income countries. However, prediction models for late FGR in China are limited. This study aimed to develop a simple combined first- and second-trimester prediction model for screening late-onset FGR in South Chinese infants. Methods: This retrospective study included 2258 women who had singleton pregnancies and received routine ultrasound scans as training dataset. A validation dataset including 565 pregnant women was used to evaluate the model in order to enable an unbiased estimation. Late-onset FGR was defined as a birth weight < the 10th percentile plus abnormal Doppler indices and/or a birth weight below the 3rd percentile after 32 weeks, regardless of the Doppler status. Multivariate logistic regression was used to develop a prediction model. The model included the a priori risk (maternal characteristics), the second-trimester head circumference (HC/AC) / abdomen circumference (HC) ratio and estimated fetal weight (EFW). Results: Ninety-three fetuses were identified as late-onset FGR. The significant predictors for late-onset FGR were maternal age, height, weight, and medical history; the second-trimester HC/ AC ratio; and the EFW. This model achieved a detection rate (DR) of 52.6% for late-onset FGR at a 10% false positive rate (FPR) (area under the curve (AUC): 0.80, 95%CI 0.76-0.85). The AUC of the validation dataset was 0.65 (95%CI 0.54-0.78). Conclusions: A multivariate model combining first- and second-trimester default tests can detect 52.6% of cases of late-onset FGR at a 10% FPR. Further studies with more screening markers are needed to improve the detection rate.

FACTORS AFFECTING BIRTH WEIGHT

PEDIATRICS ◽  
1989 ◽  
Vol 84 (3) ◽  
pp. A90-A90
Author(s):  
Student
Keyword(s):  
Birth Weight ◽  
Pregnant Women ◽  
Fetal Growth ◽  
Research Group ◽  
Maternal Smoking ◽  
Low Birthweight ◽  
District General Hospital ◽  
Maternal Height ◽  
Socioeconomic Conditions ◽  
Factors Affecting

Maternal smoking, stress, and poor socioeconomic conditions during pregnancy have been linked with low birthweight babies. Is there any way of deciding which of these related potential causes is the most important? In an attempt to do that a research group. . . studied over 1500 pregnant women delivering at a district general hospital in inner London. They showed that the most important influence on fetal growth was smoking, which was associated with a 5% reduction in birth weight after adjustment for maternal height and parity, gestation, and the baby's sex. Of over 40 socioeconomic and psychosocial factors examined, only four were significantly related to a reduction in birth weight, and these became non-significant after adjustment for smoking. The authors conclude that any effects of stress and poor environment on fetal growth are small compared with the effect of smoking.

scholarly journals A PC program for growth prediction in the context of Rao's polynomial growth curve model

1992 ◽  
Vol 22 (3) ◽  
pp. 181-188 ◽  
Author(s):  
Emet D. Schneiderman ◽  
Stephen M. Willis ◽  
Charles J. Kowalski ◽  
Thomas R. Ten Have
Keyword(s):  
Growth Curve ◽  
Polynomial Growth ◽  
Growth Curve Model ◽  
Growth Prediction ◽  
Curve Model

scholarly journals Haplotype genetic score analysis in 10,734 mother/infant pairs reveals complex maternal and fetal genetic effects underlying the associations between maternal phenotypes, birth outcomes and adult phenotypes

2019 ◽  
Author(s):  
Jing Chen ◽  
Jonas Bacelis ◽  
Pol Sole Navais ◽  
Amit Srivastava ◽  
Julius Juodakis ◽  
...  
Keyword(s):  
Birth Weight ◽  
Birth Outcomes ◽  
Fetal Growth ◽  
Late Onset ◽  
Genetic Effects ◽  
European Ancestry ◽  
Birth Size ◽  
Maternal Height ◽  
Genetic Score ◽  
Gestational Duration

ABSTRACTMany maternal traits are associated with a neonate’s gestational duration, birth weight and birth length. These birth outcomes are subsequently associated with late onset health conditions. Based on 10,734 mother/infant duos of European ancestry, we constructed haplotype genetic scores to dissect the maternal and fetal genetic effects underlying these observed associations. We showed that maternal height and fetal growth jointly affect the duration of gestation – maternal height positively influences the gestational duration, while faster fetal growth reduces gestational duration. Fetal growth is influenced by both maternal and fetal effects and can reciprocally influence maternal phenotypes: tall maternal stature and higher blood glucose causally increase birth size; in the fetus, the height and metabolic risk increasing alleles can lead to increased and decreased birth size respectively; birth weight-raising alleles in fetus may reduce gestational duration and increase maternal blood pressure. These maternal and fetal genetic effects can largely explain the observed associations between the studied maternal phenotypes and birth outcomes as well as the life-course associations between these birth outcomes and adult phenotypes.

101 PLACENTAL DEVELOPMENT IN A BOVINE HETEROSIS MODEL

2008 ◽  
Vol 20 (1) ◽  
pp. 131 ◽  
Author(s):  
C. Fitzsimmons ◽  
Z. Kruk ◽  
D. Lines ◽  
C. Roberts ◽  
S. Hiendleder
Keyword(s):  
Birth Weight ◽  
Umbilical Cord ◽  
Fetal Growth ◽  
Growth Regulation ◽  
Reciprocal Cross ◽  
Allantoic Fluid ◽  
Female Offspring ◽  
Hybrid Vigor ◽  
Fetal Weight ◽  
Placental Development

Heterosis or hybrid vigor is a biological phenomenon referring to the phenotypic superiority of hybrids over their parents. Despite its economic importance, the mechanisms of heterosis are still poorly understood. Reciprocal cross Brahman (B) � Angus (A) calves display significant heterosis in birth weight, but this effect is almost entirely due to the dramatic fetal overgrowth observed in Brahman male � Angus female offspring. The reciprocal is much less affected and similar to purebred Brahman calves (Brown et al. 1993 J. Anim. Sci. 71, 3273–3279). We have generated a defined A � A (n = 20), B � A (n = 21), A � B (n = 13), and B � B (n = 15; male parent listed first) day 153 (term = 280) fetal/placental resource from artificially inseminated, estrous cycle synchronized heifers to identify components and mechanisms of heterotic fetal growth regulation. An ANOVA showed that full uterus weight (P < 0.001), fetal weight (P = 0.01), umbilical cord length (P = 0.003) and weight (P = 0.04), placenta fetalis weight (P < 0.001), total caruncle weight (P = 0.002), empty uterus weight (P < 0.001), and combined amniotic/allantoic fluid weight (P < 0.001) were significantly affected by the 4 genetic groups after adjustment for fetal sex and dam weight where required. The weight of reciprocal hybrid fetuses was intermediate to the purebred fetuses and thus did not display heterosis defined as the difference between reciprocal cross and parental means. Full uterus weight and combined amniotic/allantoic fluid weight, in contrast, displayed heterosis of 6.6% (P = 0.02) and 9.0% (P = 0.01). As in neonate calves, the heterosis effects were due to the B � A group. The t-tests demonstrated that full uterus weight in B � A was significantly greater (19.84 � 0.43 kg) than in A � B (16.23 � 0.47 kg; P < 0.001), A � A (17.41 � 0.35 kg; P < 0.001), and B � B (16.76 � 0.49 kg; P = 0.001) crosses. Combined amniotic/allantoic fluids were 12.58 � 0.31 kg in B � A as compared to 10.93 � 0.39 kg in A � B (P = 0.001), 10.75 � 0.29 kg in A � A (P < 0.001), and 11.48 � 0.36 kg in B � B (P = 0.02) crosses. We found similar superiority of the B � A group for parameters that did not fulfil the formal heterosis criterion. These include umbilical cord, placenta fetalis, empty uterus, and total caruncle weights. All but 1 of these (combined amniotic/allantoic fluid weight) were significantly correlated (r = 0.43–0.70; P < 0.001) with fetal weight. We conclude that massive changes in placental parameters underly and precede the heterosis effects in birth weight observed in Brahman � Angus crosses. Although formally designated heterosis, placental and fetal overgrowth is present in only 1 of the hybrids (B � A). This natural overgrowth phenotype is clearly distinct from the early onset overgrowth phenotypes observed after IVF and nuclear transfer cloning (Hiendleder et al. 2004 Biol. Reprod. 71, 217–223) and will be useful in the dissection of factors contributing to fetal growth and development.

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