[Relationship between the pre-pregnancy BMI, gestational weight gain, and risk of preeclampsia and its subtypes]

The interaction effect of pre-pregnancy body mass index and maternal age on the risk of pregnancy complications in twin pregnancies after assisted reproductive technology

OBJECTIVE

The widespread use of assisted reproductive technology (ART) has led to an increased twin pregnancy rate and increased risk of pregnancy complications. Pre-pregnancy body mass index (BMI) and maternal age are both risk factors for pregnancy complications. This study aimed to explore whether there is an interaction effect between pre-pregnancy BMI and maternal age on pregnancy complications in women with twin pregnancies after ART.

METHODS

Data of 445,750 women with twin pregnancies after ART were extracted from the National Vital Statistics System (NVSS) database in 2016-2021 in this retrospective cohort study. Univariate and multivariate logistic regression analyses were used to explore (1) the associations between pre-pregnancy BMI, maternal age, and total pregnancy complications; (2) interaction effect between pre-pregnancy BMI and maternal age on total pregnancy complications; and (3) this interaction effect in parity, race, gestational weight gain (GWG), and preterm birth subgroups. The evaluation indexes were odds ratios (ORs), relative excess risk of interaction (RERI), attributable proportions of interaction (AP), and synergy index (S) with 95% confidence intervals (CIs).

RESULTS

A total of 6,827 women had pregnancy complications. After adjusting for the covariates, compared with women had non-AMA and pre-pregnancy BMI <25 kg/m2, higher maternal age combined with higher pre-pregnancy BMI was associated with higher odds of total pregnancy complications [OR = 2.16, 95%CI: (1.98-2.36)]. The RERI (95% CI) was 0.22 (0.04-0.41), AP (95% CI) was 0.10 (0.02-0.19), and S (95% CI) was 1.24 (1.03-1.49). Subgroup analysis results indicated that the potential additive effect between pre-pregnancy BMI and maternal age on total pregnancy complications was also found in women with different race, multipara/unipara, GWG levels, or preterm births/non-preterm births (all p < 0.05).

CONCLUSION

Pre-pregnancy BMI and maternal age may have an additive effect on the odds of pregnancy-related complications in women with twin pregnancy after ART.

Results of a Five-Year Experience in First Trimester Preeclampsia Screening

Background and Objectives: The study aimed to evaluate the ability defining the risk of developing preeclampsia by a screening test carried out in the first trimester (between 11 + 0 and 13 + 6 weeks of gestational age), in order to identify high-risk women requiring more intensive health surveillance. The secondary objective was to evaluate the ability of this test to predict the risk of adverse obstetric outcomes such as fetal growth restriction, intrauterine fetal death, gestational hypertension, HELLP syndrome, placental abruption, and preterm birth. Materials and Methods: This was a single-center study, conducted at the Operative Unit of Obstetrics of the State Hospital of the Republic of San Marino. Medical history was collected at the time of enrolment in writing. Subsequently, obstetric outcomes were collected for each enrolled woman, through the analysis of medical records. Results: From October 2014 to May 2019, 589 pregnant women were recruited, of whom, 474 (80.5%) were included in the “low-risk” group, and 115 (19.5%) in the “high-risk” group. At the time of analysis of this population, the obstetric outcomes were available for 498 women (84.5%), while 91 cases (15.5%) were current pregnancies. The PI of the uterine arteries was not significantly different between the two study groups. Otherwise, a significant difference was highlighted for MAP, which is higher in the case of pregnancies at high risk based on the risk factors only, and for PAPP-A, higher in the case of low-risk pregnancies. Regarding the percentage of fetal DNA, according to the most recent literature data, in our series, we report a statistically significant difference of the average between the low and high-risk groups. Conclusions: In our study, we demonstrate that the multiparametric screening test for early PE performed well in identifying women at high risk of early PE, which certainly has the most severe maternal–fetal outcomes. The data reported that ASA intake at low doses is significantly higher in the population with high-risk tests for both early PE and late PE suggest once again that anamnestic evaluation plays an essential role in women’s screening.

Healthier diet associated with reduced risk of excessive gestational weight gain: A Chinese prospective cohort study

Limited studies have examined the associations between diet quality and gestational weight gain (GWG) among Chinese pregnant women, adopting Chinese GWG guidelines. We prospectively investigate the associations of diet quality, using the Chinese Healthy Diet Index for Pregnancy (CHDI-P), which assessed diet quality from 'Diversity', 'Adequacy' and 'Limitation' dimensions with overall 100 points, with GWG among participants enroled in Southwest China. Food consumption was collected by 24 h dietary recalls for three consecutive days and CHDI-P scores were divided into tertiles. GWG was calculated according to the weight measured before delivery and classified into adequate weight gain (AWG), insufficient weight gain (IWG) and excessive weight gain(EWG) following Chinese GWG guidelines. Multinomial regression analyses and stratified analyses by pre-pregnancy body mass index were performed to estimate the association between CHDI-P and GWG. A total of 1416 participants were recruited in early pregnancy, and 971 and 997 participants were respectively followed up in middle and late pregnancy. The mean CHDI-P score was 56.44 ± 6.74, 57.07 ± 7.44 and 57.38 ± 7.94 points in early, middle and late pregnancy, respectively. Women in the lowest CHDI-P scores group had an increased risk of EWG in middle (OR = 1.53, 95% confidence interval [CI] = 1.08-2.17) and late pregnancy (OR = 1.71, 95% CI = 1.21-2.41) than women in the highest group, while overweight/obese women had a greater risk of EWG in late pregnancy (OR = 4.25, 95% CI = 1.30-13.90). No association was found between the CHDI-P scores and IWG. Poor diet quality in middle and late pregnancy was associated with a higher risk of EWG.

Clinical Application of a Multiparameter-Based Nomogram Model in Predicting Preeclampsia

Based on single-center data, the related predictive factors of preeclampsia (PE) were investigated, and a nomogram prediction model was established and validated. A retrospective collection of 93 PE patients admitted to our hospital from January 2019 to January 2021 were included in the PE group. In addition, non-PE pregnant women were selected for physical examination during the same period for matching, and 170 normal pregnant women who met the matching conditions were found as the normal pregnancy group. Clinical data of the selected candidates were collected. The risk factors of PE were screened by logistic regression analysis, and the lipopograph prediction model was constructed and verified. Logistic analysis results showed that age (OR = 3.069, 95% CI = 1.233-7.638), prepregnancy BMI (OR = 2.896, 95% CI = 1.193-7.029), vitamin E deficiency (OR = 2.803, 95% CI = 1.134-6.928), 25-(OH)D (OR = 0.944, 95% CI = 0.903∼9.988), PLGF (OR = 0.887, 95% CI = 0.851∼0.924), PAPP-A (OR = 1.240, 95% CI = 1.131∼1.360), and PI (OR = 6.376, 95% CI = 1.163∼34.967) were the independent risk factors for PE prediction (P < 0.05). The ROC curve showed that the AUC of the model for predicting the risk of PE was 0.957 (95% CI: 0.935-0.979), and the specificity and sensitivity were 0.912 and 0.892, respectively. H-L goodness of the fit test showed that there was no statistical significance in the deviation between the actual observed value and the predicted value of the risk in the line graph model (χ 2 = 7.001, P=0.536). The bootstrap test was used for internal verification, and the original data were repeatedly sampled 1000 times. The average absolute error of the calibration curve is 0.014, and the fitting degree between the calibration curve and the ideal curve is good. Age, prepregnancy BMI, lack of vitamin E, 25-(OH)D, PLGF, PAPP-A, and PI are independent risk factors for predicting PE. The establishment of a nomogram prediction model based on the above parameters can help identify PE high-risk groups in the early clinical stage and provide a reference for individualized clinical diagnosis and treatment.