Ultrasound in the prediction of birthweight discordance in dichorionic twins

Predictive value of maternal serum placental growth factor levels for discordant fetal growth in twins: a retrospective cohort study

BACKGROUND

Accurate prenatal recognition of discordant fetal growth in twins is critical for deciding suitable management strategies. We explored the predictive value of the level of maternal second-trimester placental growth factor (PLGF) as a novel indicator of discordant fetal growth.

METHODS

A total of 860 women pregnant with twins were enrolled, including 168 women with monochorionic twins (31 cases of discordant fetal growth and 137 without) and 692 with dichorionic twins (79 cases of discordant fetal growth and 613 without). Maternal second-trimester PLGF concentrations were measured via immunofluorescence.

RESULTS

Maternal second-trimester PLGF levels were significantly lower in women pregnant with twins who subsequently developed discordant fetal growth than in those who did not (monochorionic twin pregnancy: P < 0.001; dichorionic twin pregnancy: P < 0.001). A 3-4 fold difference in median PLGF concentrations was detected between the two groups with both monochorionic and dichorionic twin pregnancies. Maternal second-trimester PLGF levels were significantly correlated with birth weight differences (monochorionic twin pregnancy: r =  - 0.331, P < 0.001; dichorionic twin pregnancy: r =  - 0.234, P < 0.001). A receiver operating characteristic curve was used to evaluate the predictive efficiency. In monochorionic twin pregnancies, the area under the curve (AUC) was 0.751 (95% confidence interval [CI]: 0.649-0.852), and the cutoff value was 187.5 pg/mL with a sensitivity of 77.4% and specificity of 71.0%. In dichorionic twin pregnancies, the AUC was 0.716 (95% CI; 0.655-0.777), and the cutoff value was 252.5 pg/mL with a sensitivity of 65.1% and specificity of 69.6%. Based on the above cutoff values, univariate and multivariate logistic regression analyses were performed to calculate the odds ratios (OR) for the PLGF levels. After adjustment for potential confounding factors, low PLGF concentrations still significantly increased the risk of discordant fetal growth (monochorionic twin pregnancy: adjusted OR: 7.039, 95% CI: 2.798-17.710, P < 0.001; dichorionic twin pregnancy: adjusted OR: 4.279, 95% CI: 2.572-7.120, P < 0.001).

CONCLUSIONS

A low maternal second-trimester PLGF level is considered a remarkable risk factor and potential predictor of discordant fetal growth. This finding provides a complementary screening strategy for the prediction of discordant fetal growth and offers a unique perspective for the subsequent research in this field.

Accuracy of sonographic fetal weight estimation and prediction of birth-weight discordance in twin pregnancy: large single-center study

OBJECTIVES

To determine the accuracy of sonographic fetal weight estimation in predicting birth weight (BW) and BW discordance in twin gestations, and to evaluate maternal and fetal characteristics that may affect the accuracy of this assessment.

METHODS

This was a retrospective cohort study of all twins delivered at a single tertiary medical center between 2010 and 2021. Twin gestations for which sonographic estimation of fetal weight was performed within the week preceding delivery were included. Statistical analysis was performed to evaluate the strength of the correlation between sonographic estimated fetal weight (EFW) and BW, and to determine the impact of maternal and fetal factors on the accuracy of sonographic estimation.

RESULTS

The study included 2154 twin pregnancies. There was a strong correlation between sonographic EFW and corresponding BW for all twins (r = 0.922; P < 0.001). Strong correlations were observed for both the presenting and non-presenting cotwin (r = 0.921 and r = 0.922, respectively; both P < 0.001), as well as the larger and smaller cotwin (r = 0.928 and r = 0.934, respectively; both P < 0.001). The overall mean ± SD absolute error of sonographic EFW was 7.41 ± 6.81%. This error was greater for the non-presenting cotwin compared with the presenting cotwin (7.99 ± 6.12% vs 7.17 ± 5.64%; P < 0.001), and for the smaller cotwin compared with the larger cotwin (8.56 ± 7.50% vs 6.58 ± 5.47%; P < 0.001). Advanced gestational age at scanning was correlated inversely with the mean absolute error of sonographic EFW. Multivariate logistic regression indicated that an earlier gestational age at scanning, being the non-presenting cotwin and being the smaller cotwin were independent risk factors for sonographic EFW inaccuracy. Pregnancies in which the presenting twin was estimated to be the smaller cotwin had twice the rate of false-positive BW discordance compared with pregnancies in which the presenting twin was estimated to be the larger cotwin (36.0% vs 13.0% for BW discordance > 15%, 35.0% vs 17.0% for BW discordance > 20% and 37.7% vs 12.1% for BW discordance > 25%; all P < 0.001). The error in sonographic EFW discordance was not related to chorionicity, the position of the presenting fetus or gestational age at the time of fetal weight estimation.

CONCLUSIONS

Sonographic estimation of fetal weight within 7 days before delivery accurately predicts BW in twin pregnancy. Sonographic EFW accuracy is reduced for the non-presenting twin, the smaller cotwin and when delivery occurs at an earlier gestational age. Sonographic estimation of fetal weight discordance is less accurate when the presenting twin is the smaller cotwin. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

An intelligent adverse delivery outcomes prediction model based on the fusion of multiple obstetric clinical data

Adverse delivery outcomes is a major re-productive health problem that affects the physical and mental health of pregnant women. Obviously, obstetric clinical data has periodically time series characteristics. This paper proposed a three stage adverse delivery outcomes prediction model via the fusion of multiple time series clinical data. The first stage is data aggregation, in which the data set is collected from the obstetric clinical data and divided based on time series features. In the second stage, a multi-channel gated cycle unit is used to solve the calculation error caused by irregular sampling of time series data. The hidden layer feature vector is connected with the fully connected layer, reshaped into a new one-dimensional feature, and fused with the non-time series data into a new data set. The third stage is the prediction stage of adverse delivery outcomes. By connecting the multi-channel gated cycle unit with the extreme gradient lift, the data transmitted in the corresponding channel is used in the feature extraction stage, in which the weighted entropy-based feature extraction is adopted. With the help of the extracted features, a hybrid artificial neural network architecture (MGRU-XGB) was developed to predict adverse delivery outcomes. The experimental results showed that the hybrid model had the best prediction performance for adverse delivery outcomes compared with other single models in terms of sensitivity, specificity, AUC and other evaluation indexes.

Weekly Paclitaxel Administered During a Twin Pregnancy for Recurrent Breast Cancer: Case Report and Review of the Literature

Although cancer treatment during single pregnancy has been standardized, how to manage cancer diagnosed during a multiple gestation is still unclear. Chemotherapy during pregnancy has shown to be safe, however, there are reports of increased risks of fetal complications such as intrauterine growth restriction and preterm birth. Also, how to best adjust this to the pharmacokinetic characteristics of a twin gestation has yet to be fully investigated. We report the case of an IVF twin pregnancy with a diagnosis of breast cancer recurrence shortly after conception, and how the pregnancy was managed to obtain optimal obstetric, maternal/oncological, and fetal outcomes.