Prediction of twin pregnancy preeclampsia based on clinical risk factors, early pregnancy serum markers, and uterine artery pulsatility index

Dynamic changes in blood lipid levels and their associations with hypertensive disorders of pregnancy in twin pregnancy: A retrospective study

BACKGROUND

Little knowledge on the association of blood lipid levels with hypertensive disorders of pregnancy (HDP) in twin pregnancy.

OBJECTIVE

To investigate the association of blood lipid levels with HDP in twin pregnancy.

METHODS

This is a retrospective study in the Beijing Birth Cohort on patients followed between January 2014 and November 2021. A total of 2628 women pregnant with twins were included and divided into HDP (n = 565) and normal blood pressure (NBP, n = 2063) groups. HDP subtypes included gestational hypertension (GH, n = 190) and preeclampsia (PE, n = 375). Dynamic changes in blood lipid profiles and their associations with HDP were assessed.

RESULTS

Compared to NBP group, higher triglyceride (TG) and low-density lipoprotein  cholesterol (LDL-c) in the first (T1) and second trimesters (T2) existed in women with PE. In addition, TG increased significantly from T1 to T2, and high-density lipoprotein cholesterol (HDL-c) decreased significantly since T2 in women with PE, especially in women with early-onset PE and severe PE. Elevated TG and LDL-c were associated with HDP, mainly PE. In a subgroup analysis, higher TG or LDL-c increased the risk of HDP for underweight, overweight and primipara women.

CONCLUSIONS

In twin pregnancy, women with PE had higher TG and LDL-c, and elevated TG and LDL-c were associated with PE. A significant increase in TG or decrease in HDL-c were more prone to PE, especially early-onset PE and severe PE. It is helpful to monitor blood lipid levels in women pregnant with twins, especially in underweight, overweight, and primipara women.

Medication-Wide Association Study Using Electronic Health Record Data of Prescription Medication Exposure and Multifetal Pregnancies: Retrospective Study

Background

Medication-wide association studies (MWAS) have been applied to assess the risk of individual prescription use and a wide range of health outcomes, including cancer, acute myocardial infarction, acute liver failure, acute renal failure, and upper gastrointestinal ulcers. Current literature on the use of preconception and periconception medication and its association with the risk of multiple gestation pregnancies (eg, monozygotic and dizygotic) is largely based on assisted reproductive technology (ART) cohorts. However, among non-ART pregnancies, it is unknown whether other medications increase the risk of multifetal pregnancies.

Objective

This study aimed to investigate the risk of multiple gestational births (eg, twins and triplets) following preconception and periconception exposure to prescription medications in patients who delivered at Penn Medicine.

Methods

We used electronic health record data between 2010 and 2017 on patients who delivered babies at Penn Medicine, a health care system in the Greater Philadelphia area. We explored 3 logistic regression models: model 1 (no adjustment); model 2 (adjustment for maternal age); and model 3—our final logistic regression model (adjustment for maternal age, ART use, and infertility diagnosis). In all models, multiple births (MBs) were our outcome of interest (binary outcome), and each medication was assessed separately as a binary variable. To assess our MWAS model performance, we defined ART medications as our gold standard, given that these medications are known to increase the risk of MB.

Results

Of the 63,334 distinct deliveries in our cohort, only 1877 pregnancies (2.96%) were prescribed any medication during the preconception and first trimester period. Of the 123 medications prescribed, we found 26 (21.1%) medications associated with MB (using nominal P values) and 10 (8.1%) medications associated with MB (using Bonferroni adjustment) in fully adjusted model 3. We found that our model 3 algorithm had an accuracy of 85% (using nominal P values) and 89% (using Bonferroni-adjusted P values).

Conclusions

Our work demonstrates the opportunities in applying the MWAS approach with electronic health record data to explore associations between preconception and periconception medication exposure and the risk of MB while identifying novel candidate medications for further study. Overall, we found 3 novel medications linked with MB that could be explored in further work; this demonstrates the potential of our method to be used for hypothesis generation.