Adverse maternal outcomes associated with major fetal malformations after singleton live birth

Reevaluating optimal weight changes across the stages of pregnancy

BACKGROUND

While the National Academy of Medicine, formerly known as the Institute of Medicine, recommends the optimum weight change in the second and third trimesters combined, the ideal weight change range per week according to trimesters remains unexplored.

OBJECTIVE

To determine the optimal rates of weight change per week that are associated with decreased adverse pregnancy outcomes for each trimester stratified by prepregnancy body mass index categories.

STUDY DESIGN

This was a secondary analysis of a prospective cohort study using data from the Nulliparous Pregnancy Outcomes Study: Monitoring Mothers-to-Be (2010-2014). Our exposure was the weight change per week, defined as weight change (kg) divided by gestational weeks interval. We examined weight change per week for each trimester: weight change in early pregnancy (early first trimester to second trimester); second trimester (second trimester to third trimester); and third trimester (third trimester to delivery). Our primary outcome was a composite of adverse pregnancy outcomes including hypertensive disorders of pregnancy, preterm birth, spontaneous preterm birth, small-for-gestational-age birth, and stillbirth. To explore potential nonlinear associations between pregnancy weight change and adverse pregnancy outcomes, we applied restricted cubic spline functions with 5 knots. We calculated adjusted relative risks with 95% confidence intervals using generalized linear models with Poisson distribution and robust error variance, controlling for confounders. We estimated adjusted relative risks of adverse pregnancy outcomes for each weight change per week and identified the optimal weight change. The optimal weight change was compared with the National Academy of Medicine-recommended weight change in pregnancy.

RESULTS

Of the 8121 patients included, 4373 (53.8%) had a normal or underweight body mass index, 2002 (24.7%) had an overweight body mass index, and 1746 (21.5%) had an obese body mass index. The weight changes per week associated with the lowest adverse risks for individuals with normal/underweight, overweight, and obese body mass index were 0.7 kg/wk, 0.7 kg/wk, and 0.6 kg/wk, respectively, for the first trimester, 0.7 kg/wk, 0.5 kg/wk, and 0.5 kg/wk, respectively, for the second trimester, and 0.5 kg/wk, 0.4 kg/wk, and 0.4 kg/wk, respectively, for the third trimester. For normal/underweight, weight gain according to the National Academy of Medicine guidelines in the second trimester compared to our optimal weight gain was associated with an increased risk of adverse pregnancy outcomes and preterm birth. For normal/underweight and overweight individuals in the second trimester, weight gain according to the National Academy of Medicine guidelines, compared to our optimal weight gain, was associated with an increased risk of small for gestational age. Conversely, for individuals with obesity in the third trimester, weight gain according to the National Academy of Medicine guidelines compared to our optimal weight gain was associated with a decreased risk of cesarean delivery.

CONCLUSION

The gestational weight change rates associated with the lowest adverse risks were of higher values than those established by the National Academy of Medicine, which may suggest that the National Academy of Medicine guidelines are too strict.

LPC-SonoNet: A Lightweight Network Based on SonoNet and Light Pyramid Convolution for Fetal Ultrasound Standard Plane Detection

The detection of fetal ultrasound standard planes (FUSPs) is important for the diagnosis of fetal malformation and the prevention of perinatal death. As a promising deep-learning technique in FUSP detection, SonoNet's network parameters have a large size. In this paper, we introduced a light pyramid convolution (LPC) block into SonoNet and proposed LPC-SonoNet with reduced network parameters for FUSP detection. The LPC block used pyramid convolution architecture inspired by SimSPPF from YOLOv6 and was able to extract features from various scales with a small parameter size. Using SonoNet64 as the backbone, the proposed network removed one of the convolutional blocks in SonoNet64 and replaced the others with LPC blocks. The proposed LPC-SonoNet model was trained and tested on a publicly available dataset with 12,400 ultrasound images. The dataset with six categories was further divided into nine categories. The images were randomly divided into a training set, a validation set, and a test set in a ratio of 8:1:1. Data augmentation was conducted on the training set to address the data imbalance issue. In the classification of six categories and nine categories, LPC-SonoNet obtained the accuracy of 97.0% and 91.9% on the test set, respectively, slightly higher than the accuracy of 96.60% and 91.70% by SonoNet64. Compared with SonoNet64 with 14.9 million parameters, LPC-SonoNet had a much smaller parameter size (4.3 million). This study pioneered the deep-learning classification of nine categories of FUSPs. The proposed LPC-SonoNet may be used as a lightweight network for FUSP detection.

Maternal implications of fetal anomalies: a population-based cross-sectional study

BACKGROUND

Although it is well-known that the presence of fetal anomalies is associated with maternal morbidity, granular information on these risks by type of anomaly is not available.

OBJECTIVE

To examine adverse maternal outcomes according to the type of fetal anomaly.

STUDY DESIGN

This was a repeated cross-sectional analysis of US vital statistics Live Birth/Infant Death linked data from 2011 to 2020. All pregnancies at 20 weeks or greater were included. Our primary outcome was severe maternal morbidity (SMM), defined as any maternal intensive care unit admission, transfusion, uterine rupture, or hysterectomy. Outcomes were compared between pregnancies with a specific type of fetal anomaly and pregnancies without any fetal anomaly. Fetal anomalies that were available in the dataset included anencephaly, meningomyelocele/spina bifida, cyanotic congenital heart disease, congenital diaphragmatic hernia, omphalocele, gastroschisis, cleft lip and/or palate, hypospadias, limb anomaly, and chromosomal disorders. If a fetus had more than one anomaly, it was classified as multiple anomalies. Adjusted relative risks (aRR) with 99% confidence intervals (99% CI) were calculated using modified Poisson regression. Adjusted risk differences (aRDs) were calculated using the marginal standardization form of predictive margins.

RESULTS

Of 35,760,626 pregnancies included in the analysis, 35,655,624 pregnancies had no fetal anomaly and 105,002 had isolated or multiple fetal anomalies. Compared to pregnancies without fetal anomaly, all fetal anomalies were associated with an increased risk of SMM except for gastroschisis and limb anomaly in order of aRRs (99% CI): 1.58 (1.29-1.92) with cleft lip and/or palate; 1.75 (1.35-2.27) with multiple anomalies; 1.76 (1.18-2.63) with a chromosomal disorder; 2.19 (1.82-2.63) with hypospadias; 2.20 (1.51-3.21) with spina bifida; 2.39 (1.62-3.53) with congenital diaphragmatic hernia; 2.66 (2.27-3.13) with congenital heart disease; 3.15 (2.08-4.76) with omphalocele; and 3.27 (2.22-4.80) with anencephaly. Compared to pregnancies without fetal anomaly, all fetal anomalies were associated with an increased absolute risk of SMM except for gastroschisis and limb anomaly in order of aRDs (99% CI): 0.26 (0.12-0.40) with cleft lip and/or palate, 0.34 (0.13-0.55) with multiple anomalies, 0.34 (0.02-0.66) with a chromosomal disorder, 0.54 (0.36-0.72) with hypospadias, 0.54 (0.17-0.92) with spina bifida, 0.63 (0.21-1.05) with congenital diaphragmatic hernia, 0.75 (0.56-0.95) with congenital heart disease, 0.97 (0.38-1.56) with omphalocele, and 1.03 (0.46-1.59) with anencephaly.

CONCLUSION

The presence of fetal anomalies is associated with adverse maternal health outcomes. The risk of SMM varies according to the type of fetal anomaly. Counseling mothers about the maternal implications of fetal anomalies is paramount to help them make informed decisions regarding their pregnancy outcome.

Congenital Malformations in the Moroccan Surveillance System: Contribution to Prevalence Estimation

Background

Congenital malformations (CMs) are a group of structural or functional anomalies present at birth. These anomalies result in a high rate of mortality, morbidity, and disability in children. CMs are a major public health problem and place a heavy burden on healthcare systems in both developed and developing countries including Morocco, which has had a CMs surveillance system in place since 2011. The aim of this study is to determine the prevalence of CMs in Morocco.

Methods

In this study, the epidemiology of CMs in Morocco was assessed retrospectively using the national surveillance system data gathered from case notification forms from 2017 to 2021.

Results

The main results showed that the prevalence of CMs in Morocco is 3.91/1000 live births (LBs), and the minimum annual prevalence of CMs was reached in 2017 (3.10/1000 LBs) while the maximum annual prevalence was recorded in 2018 (4.55/1000 LBs). The majority of CMs are unspecified CMs (68.55%), neural tube defects (NTDs) account for (21.13%), and orofacial clefts (OFCs) account for (10.32%). In addition, the majority of CMs (61.73%) were from rural areas. According to region, the Dakhla-Oued Eddahab region recorded the highest prevalence of CMs in Morocco, with 8.81/1000 LBs, while the lowest prevalence was recorded in the Rabat-Sale-Kenitra region, with 2.02/1000 LB.

Conclusions

This study reveals that the national prevalence of CMs is high and may be underestimated, as most of the CMS reported is unspecified. The use of a CM registry with detailed reporting of all CMs and the promotion of preventive measures are urgently recommended.