Correlation between uterine artery Doppler and the sFlt-1/PlGF ratio in different phenotypes of placental dysfunction

Preeclampsia prediction model using demographic, clinical, and sonographic data in the second trimester of Japanese nulliparous women

AIM

This study aimed to clarify the factors influencing preeclampsia (PE) development in nulliparous Japanese women and to develop a PE prediction model using second trimester sonographic and clinical data readily available to obstetricians.

METHODS

This historical cohort study examined the obstetric records of nulliparous women who delivered at Yamanashi Prefectural Central Hospital from January 2019 to May 2023. A model was constructed to predict the PE development rate, with a focus on 796 nulliparous women. The assessed outcome was PE, excluding superimposed PE. Data on maternal age, assisted reproductive technology, mean arterial pressure, uterine artery notching, and umbilical artery resistance index were extracted. Multivariable logistic regression analysis was conducted on these five factors.

RESULTS

The incidence of PE was 4.3% (34/796). Multivariable analysis indicated significant odds ratios for the association of PE with mean arterial pressure (adjusted odds ratio: 1.06, 95% confidence interval: 1.03-1.10) and uterine artery notching (adjusted odds ratio: 6.28, 95% confidence interval: 2.82-14.0) in nulliparous women. The PE prediction formula was established as follows: Probability of PE development (%) = (odds/1 + odds) × 100, odds = ex and x = -11.3 + 0.039 × maternal age (years) + 0.91 × assisted reproductive technology + 0.061 × mean arterial pressure (mmHg) + 1.84 × uterine artery notching + 1.84 × umbilical artery resistance index. The sensitivity and specificity of this model were 58.8% and 84.5%, respectively (area under the curve: 0.79).

CONCLUSIONS

This study is the first to provide a prediction formula targeting the Japanese population. Our specialized model for nulliparous women could guide obstetricians to educate women regarding the precise prospect of PE development.

Mid-trimester uterine artery Doppler for aspirin discontinuation in pregnancies at high risk for preterm pre-eclampsia: Post-hoc analysis of StopPRE trial

OBJECTIVE

To assess whether aspirin treatment can be discontinued in pregnancies with normal uterine artery pulsatility index (≤90th percentile) at 24-28 weeks.

DESIGN

Post-hoc analysis of a clinical trial.

SETTING

Nine maternity hospitals in Spain.

POPULATION OR SAMPLE

Pregnant individuals at high risk of pre-eclampsia at 11-13 weeks and normal uterine artery Doppler at 24-28 weeks.

METHODS

All participants received treatment with daily aspirin at a dose of 150 mg. Participants were randomly assigned, in a 1:1 ratio, either to continue aspirin treatment until 36 weeks (control group) or to discontinue aspirin treatment (intervention group), between September 2019 and September 2021. In this secondary analysis, women with a UtAPI >90th percentile at 24-28 weeks were excluded. The non-inferiority margin was set at a difference of 1.9% for the incidence of preterm pre-eclampsia.

MAIN OUTCOME MEASURES

Incidence of preterm pre-eclampsia.

RESULTS

Of the 1611 eligible women, 139 were excluded for UtAPI >90th percentile or if UtAPI was not available. Finally, 804 were included in this post-hoc analysis. Preterm pre-eclampsia occurred in three of 409 (0.7%) women in the aspirin discontinuation group and five of 395 (1.3%) women in the continuation group (-0.53; 95% CI -1.91 to 0.85), indicating non-inferiority of aspirin discontinuation.

CONCLUSIONS

Discontinuing aspirin treatment at 24-28 weeks in women with a UtAPI ≤90th percentile was non-inferior to continuing aspirin treatment until 36 weeks for preventing preterm pre-eclampsia.

Maternal serum soluble fms-like tyrosine kinase-1-to-placental growth factor ratio distinguishes growth-restricted from non-growth-restricted small-for-gestational-age fetuses

BACKGROUND

Fetal growth restriction secondary to chronic placental insufficiency is a major cause of perinatal morbidity and mortality. A significant proportion of fetuses with fetal growth restriction are small for gestational age, defined as a birthweight of ≤10th percentile. However, not all small-for-gestational-age fetuses are growth restricted. Some are constitutionally small and otherwise healthy. It is important to distinguish between small-for-gestational-age fetuses with and without fetal growth restriction to ensure appropriate interventions in small-for-gestational-age fetuses with fetal growth restriction and to minimize unnecessary interventions in healthy small-for-gestational-age fetuses. The maternal serum ratio of soluble fms-like tyrosine kinase-1 and placental growth factor is an indicator of placental insufficiency in the latter half of pregnancy. As such, the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio may be a clinically useful tool to distinguish between small-for-gestational-age fetuses with and without fetal growth restriction.

OBJECTIVE

This study aimed to determine whether the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio can distinguish between small-for-gestational-age fetuses with and without fetal growth restriction with a birthweight of ≤10th percentile.

STUDY DESIGN

A retrospective audit of 233 singleton pregnancies delivering an infant with a birthweight of ≤10th percentile corrected for gestational age with an antenatal maternal serum soluble fms-like tyrosine kinase-1-to-placental growth factor result was performed. Fetal growth restriction was defined as a birthweight of ≤10th percentile with an umbilical artery pulsatility index of >95th percentile, fetal middle cerebral artery pulsatility index of <5th percentile, amniotic fluid index of <6 cm, and/or cerebroplacental ratio of <1st percentile. The soluble fms-like tyrosine kinase-1-to-placental growth factor ratios before delivery between fetuses with and without fetal growth restriction (121 [fetal growth restriction] vs 112 [no fetal growth restriction]) were compared. The Student t test and Fisher exact test were used to compare cases and controls. The Mann-Whitney U test, linear regression analysis, and Spearman correlation coefficient (Rho) were used to examine associations between the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio and fetal outcomes to determine whether the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio served as a prognostic marker of fetal growth restriction severity.

RESULTS

The mean soluble fms-like tyrosine kinase-1-to-placental growth factor ratio was increased in fetal growth restriction cases compared with non-fetal growth restriction controls (234.3±25.0 vs 67.4±7.7, respectively; P<.0001). When controlling for preeclampsia, which is associated with placental insufficiency, fetal growth restriction cases still demonstrated an independent increase in the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio (effect size, 0.865; 95% confidence interval, 0.509-1.220; P<.001). The soluble fms-like tyrosine kinase-1-to-placental growth factor ratio was negatively correlated with birthweight percentiles in pregnancies delivering an infant with a birthweight of ≤10th percentile (r=-0.3565; P<.0001). This association was maintained for fetuses with fetal growth restriction (r=-0.2309; P<.05), whereas fetuses without fetal growth restriction had no significant correlation between the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio and neonatal birthweight percentiles.

CONCLUSION

The soluble fms-like tyrosine kinase-1-to-placental growth factor ratio was significantly higher in small-for-gestational-age fetuses with fetal growth restriction than small-for-gestational-age fetuses without fetal growth restriction, independent of preeclampsia. Furthermore, the soluble fms-like tyrosine kinase-1-to-placental growth factor ratio was negatively correlated with fetal growth restriction birthweight percentiles, suggesting that it may be a clinical measure of fetal growth restriction severity. Therefore, the ratio may usefully delineate fetal growth restriction from constitutionally small but otherwise healthy fetuses antenatally, allowing for timely interventions in small-for-gestational-age cases with fetal growth restriction and unnecessary interventions to be minimized in small-for-gestational-age cases without fetal growth restriction.

Placenta-Specific miR-125b Overexpression Leads to Increased Rates of Pregnancy Loss in Mice

Pregnancy loss (PL) is one of the common complications that women can experience during pregnancy, with an occurrence rate of 1 to 5%. The potential causes of pregnancy loss are unclear, with no effective treatment modalities being available. It has been previously reported that the level of miR-125b was significantly increased in placentas of PL patients. However, the role of miR-125b in the development of PL still remains unknown. In the current study, an miR-125b placenta-specific over-expression model was constructed by lentiviral transfecting zona-free mouse embryos followed by embryo transfer. On gestation day 15, it was observed that the placenta was significantly smaller in the miR-125b placenta-specific overexpression group than the control group. Additionally, the abortion rate of the miR-125b placenta-specific overexpression group was markedly higher than in the control group. The blood vessel diameter was larger in the miR-125b-overexpressing specific placenta. In addition, miR-125b-overexpressing HTR8 and JEG3 cell lines were also generated to analyze the migration and invasion ability of trophoblasts. The results showed that miR-125b overexpression significantly suppressed the migration and invasion ability of HTR8 and JEG3 cells. Overall, our results demonstrated that miR-125b can affect embryo implantation through modulating placenta angiogenesis and trophoblast cell invasion capacity that can lead to PL.

Prediction of Preeclampsia and Intrauterine Growth Restriction: Development of Machine Learning Models on a Prospective Cohort

BACKGROUND

Preeclampsia and intrauterine growth restriction are placental dysfunction-related disorders (PDDs) that require a referral decision be made within a certain time period. An appropriate prediction model should be developed for these diseases. However, previous models did not demonstrate robust performances and/or they were developed from datasets with highly imbalanced classes.

OBJECTIVE

In this study, we developed a predictive model of PDDs by machine learning that uses features at 24-37 weeks' gestation, including maternal characteristics, uterine artery (UtA) Doppler measures, soluble fms-like tyrosine kinase receptor-1 (sFlt-1), and placental growth factor (PlGF).

METHODS

A public dataset was taken from a prospective cohort study that included pregnant women with PDDs (66/95, 69%) and a control group (29/95, 31%). Preliminary selection of features was based on a statistical analysis using SAS 9.4 (SAS Institute). We used Weka (Waikato Environment for Knowledge Analysis) 3.8.3 (The University of Waikato, Hamilton, NZ) to automatically select the best model using its optimization algorithm. We also manually selected the best of 23 white-box models. Models, including those from recent studies, were also compared by interval estimation of evaluation metrics. We used the Matthew correlation coefficient (MCC) as the main metric. It is not overoptimistic to evaluate the performance of a prediction model developed from a dataset with a class imbalance. Repeated 10-fold cross-validation was applied.

RESULTS

The classification via regression model was chosen as the best model. Our model had a robust MCC (.93, 95% CI .87-1.00, vs .64, 95% CI .57-.71) and specificity (100%, 95% CI 100-100, vs 90%, 95% CI 90-90) compared to each metric of the best models from recent studies. The sensitivity of this model was not inferior (95%, 95% CI 91-100, vs 100%, 95% CI 92-100). The area under the receiver operating characteristic curve was also competitive (0.970, 95% CI 0.966-0.974, vs 0.987, 95% CI 0.980-0.994). Features in the best model were maternal weight, BMI, pulsatility index of the UtA, sFlt-1, and PlGF. The most important feature was the sFlt-1/PlGF ratio. This model used an M5P algorithm consisting of a decision tree and four linear models with different thresholds. Our study was also better than the best ones among recent studies in terms of the class balance and the size of the case class (66/95, 69%, vs 27/239, 11.3%).

CONCLUSIONS

Our model had a robust predictive performance. It was also developed to deal with the problem of a class imbalance. In the context of clinical management, this model may improve maternal mortality and neonatal morbidity and reduce health care costs.