Hypertension in Pregnancy最新文献

Background: Predicting severe preeclampsia with need for intensive care is challenging. To better predict high-risk pregnancies to prevent adverse outcomes such as eclampsia is still an unmet need worldwide. In this study we aimed to develop a prediction model for severe outcomes using routine biomarkers and clinical characteristics.

Methods: We used machine learning models based on data from an intensive care cohort with severe preeclampsia (n=41) and a cohort of preeclampsia controls (n=40) with the objective to find patterns for severe disease not detectable with traditional logistic regression models.

Results: The best model was generated by including the laboratory parameters aspartate aminotransferase (ASAT), uric acid and body mass index (BMI) with a cross-validation accuracy of 0.88 and an area under the curve (AUC) of 0.91. Our model was internally validated on a test-set where the accuracy was lower, 0.82, with an AUC of 0.85.

Conclusion: The clinical routine blood parameters ASAT and uric acid as well as BMI, were the parameters most indicative of severe disease. Aspartate aminotransferase reflects liver involvement, uric acid might be involved in several steps of the pathophysiologic process of preeclampsia, and obesity is a well-known risk factor for development of both severe and non-severe preeclampsia likely involving inflammatory pathways..[Figure: see text].

Objective: Preeclampsia (PE) increases the risk of many adverse maternal and fetal outcomes. This study was to investigate the correlation between epicardial adipose tissue (EAT) thickness and PE and birth weight.

Methods: This was a single-center retrospective study, 221 patients with PE were selected, and 81 women without hypertension and proteinuria were selected as a comparison. Echocardiogram was performed in their first prenatal examinations at 11-13 gestational weeks, and the thickness of EAT was measured. At the subsequent follow-up, the birth weight was recorded.

Results: EAT thickness was significantly elevated (6.60 ± 1.34 vs. 5.71 ± 1.79 mm, p < 0.001) in severe PE compared to mild PE. In the multivariate analysis, EAT thickness (OR 5.671, 95% CI, 1.991-16.150, p = 0.001), and C reactive protein (OR 4.097, 95% CI, 2.323-7.224, p < 0.001) were found as significant independent predictors of severe PE after adjusting for other risk factors. Linear regression analysis showed that hs-CRP, EAT thickness, and severe PE significantly negatively affected birth weight.

Conclusion: EAT thickness can be used to identify pregnant women with severe PE risks and low birth weight. It is an independent risk factor for severe PE but is not a valuable sign of mild PE.

Background: Preeclampsia and eclampsia are severe pregnancy disorders marked by hypertension and potential organ damage. The etiological basis of preeclampsia and eclampsia is not fully understood. Previous studies have revealed a link between sleep abnormality and preeclampsia/eclampsia, but the causal relationship remains unclear. In this study, we explored the genetic links between sleep and preeclampsia/eclampsia using genome-wide association study (GWAS) summary data and Mendelian randomization (MR) analysis.

Methods: RNA sequence dataset GSE114691 was downloaded from the Gene Expression Omnibus database, comprising placental tissues from patients with preeclampsia and controls. Differential expression analysis was conducted with R (v4.2.3) and DESeq2 (v1.38.3). Gene set enrichment analysis (GSEA) was carried out using HTSanalyzeR2. GWAS summary data on preeclampsia/eclampsia and genetic markers for sleep abnormality were sourced from the FinnGen Consortium and IEU genetic databases. The Mendelian randomization analysis was conducted with TwoSampleMR (v0.6.2), and the inverse variance weighted (IVW) approach was employed as the principal method.

Results: GSEA analysis revealed that the orexin receptor pathway showed heightened expression in the preeclampsia group versus controls. The random-effects IVW results showed that sleeplessness/insomnia has a genetic causal relationship with preeclampsia (OR = 2.08, 95% CI: 1.07-4.06, p = 0.0318), while sleep duration has evidence of regulating eclampsia (OR = 0.09, 95% CI: 0.01-0.67, p = 0.0187).

Conclusion: This study provides significant evidence for a genetic causal association between sleep abnormalities and preeclampsia/eclampsia. [Figure: see text].

Background: Polycystic ovary syndrome (PCOS) is a metabolic and reproductive disorder. Current research findings present conflicting views on the effects of different PCOS phenotypes on outcomes in pregnancy and for newborns.

Methods: This research study followed the guidelines of the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). A thorough search of literature was carried out using the Cochrane Menstrual Disorders and Subfertility Group trials register, Web of Science, and EMBASE databases from their start to December 2023. The search focused on studies examining the links between hyperandrogenic and non-hyperandrogenic PCOS phenotypes and risks in pregnancy and neonatology. Odds ratios (ORs) and 95% confidence intervals (CIs) were computed using either a fixed-effects or random-effects model.

Results: Our analysis incorporated 10 research studies. Expectant mothers with a hyperandrogenic PCOS subtype had increased ORs for gestational diabetes mellitus (GDM) and preeclampsia (PE) compared to those with a non-hyperandrogenic PCOS subtype, with respective values of 2.14 (95% CI, 1.18-3.88, I² = 0%) and 2.04 (95% CI, 1.02-4.08, I² = 53%). Nevertheless, no notable differences were detected in ORs for outcomes like preterm birth, live birth, miscarriage, cesarean delivery, pregnancy-induced hypertension, small for gestational age babies, large for gestational age newborns, and neonatal intensive care unit admissions between pregnant women with hyperandrogenic PCOS phenotype and those without.

Conclusions: This meta-analysis highlights that the presence of hyperandrogenism heightens the risks of GDM and PE within the PCOS population. Healthcare providers ought to be aware of this connection for improved patient management.

Objectives: Preeclampsia (PET) is a serious pregnancy complication with potential adverse maternal and fetal outcomes. Recent research has examined the soluble fms-like tyrosine kinase 1 (sFlt-1)/placental growth factor (PlGF) ratio for predicting PET. The study aimed to assess the efficacy of the sFlt-1/PlGF ratio in ruling out unnecessary hospital admission and PET.

Methods: sFlt-1/PlGF ratio was performed in patients as clinically indicated.

Results: The sFlt-1/PlGF ratio at a cutoff value of 51 predicted hospital admission with AUC, PPV, NPV, sensitivity, and specificity of 85%, 44%, 98%, 88%, and 85%, respectively. Additionally, at a cutoff value of 38, the sFlt-1/PlGF ratio predicted the short-term development of PET with PPV, NPV, sensitivity, and specificity of 42%, 100%, 100%, and 81%, respectively. The PlGF alone at a cutoff value of 193.36 predicted hospital admission with AUC, PPV, NPV, sensitivity, and specificity of 87%, 80%, 97%, 67%, and 98%, respectively. Moreover, at a cutoff value of 51.35, the PlGF alone predicted the development of PET with PPV, NPV, sensitivity, and specificity of 54%, 98%, 88%, and 90%, respectively. There was a significant association between a high sFlt-1/PlGF ratio and developing PET.

Conclusion: The sFlt-1/PlGF ratio and PlGF are promising for ruling out PET and hospital admission in pregnant women.

Objective: SARS-CoV-2 infection during pregnancy has been linked with an increased risk of hypertensive disorders of pregnancy (HDP). The aim of this study was to examine how both trimester and severity of SARS-CoV-2 infection impact HDP.

Methods: We conducted a cohort study of SARS-CoV-2-infected individuals during pregnancy (n = 205) and examined the association between trimester and severity of infection with incidence of HDP using modified Poisson regression models to calculate risk ratios (RR) and 95% confidence intervals (CI). We stratified the analysis of trimester by severity to understand the role of timing of infection among those with similar symptomatology and also examined timing of infection as a continuous variable.

Results: Compared to a reference cohort from 2018, SARS-CoV-2 infection did not largely increase the risk of HDP (RR: 1.17; CI:0.90, 1.51), but a non-statistically significant higher risk of preeclampsia was observed (RR: 1.33; CI:0.89, 1.98), in our small sample. Among the SARS-CoV-2 cohort, severity was linked with risk of HDP, with infections requiring hospitalization increasing the risk of HDP compared to asymptomatic/mild infections. Trimester of infection was not associated with risk of HDP, but a slight decline in the risk of HDP was observed with later gestational week of infection. Among patients with asymptomatic or mild symptoms, SARS-CoV-2 in the first trimester conferred a higher risk of HDP compared to the third trimester (RR: 1.70; CI:0.77, 3.77), although estimates were imprecise.

Conclusion: SARS-CoV-2 infection in early pregnancy may increase the risk of HDP compared to infection later in pregnancy.

Objective: This study aimed to determine the differences in characteristics and outcomes of early-onset and late-onset Preeclampsia.

Methods: A retrospective cross-sectional study was conducted on female patients giving birth with preeclampsia admitted into the Department of Obstetrics and Gynecology of Dr. Hasan Sadikin Hospital Bandung from January 2020 to December 2022 who met the study criteria. A total of 435 subjects met the inclusion criteria were divided into two groups: early-onset preeclampsia and late-onset preeclampsia. Differences in outcomes were analyzed using the Chi-square or Fisher test for categorical data and the T-independent or Mann-Whitney test for numerical data.

Results: There were differences in the incidence of HELLP syndrome (9.0 vs. 2.7%; p = 0.009), prematurity (77.7 vs. 21.4%; p = 0.000), early neonatal death (10.4 vs. 2.7%; p = 0.002), asphyxia (22.7 vs. 8.0%; p = 0.000), SGA (41.7 vs 21.9%; p = 0.000), and LBW (78.7 vs 40.2%; p = 0.000) in early-onset preeclampsia with late-onset. Length of stay was longer in early-onset preeclampsia cases (4.0 vs 3.0 days; p = 0.000). Increased ureum and liver enzymes results were significantly higher in early-onset preeclampsia.

Conclusion: There is a difference in the outcome of pregnant women with early-onset and late-onset preeclampsia. Women with early-onset preeclampsia tend to have more adverse maternal and neonatal outcomes. In terms of maternal outcome, they tend to have higher liver enzymes level and HELLP syndrome, while in terms of neonatal outcome they tend to have prematurity, early neonatal death, asphyxia, SGA, and LBW.

Background: Preeclampsia (PE) is a pregnancy disorder that represents a major cause of maternal and perinatal morbidity and mortality.

Methods: This network meta-analysis was registered with PROSPERO. We searched the PubMed, ClinicalTrials.gov. and Embase databases for studies published from inception to the 31^st of March 2023. RevMan5.3 software provided by the Cochrane Collaboration was used for direct meta-analysis (DMA) statistical analysis. Funnel maps, network meta-analysis (NMA), the surface under the cumulative ranking curve (SUCRA) to rank the different interventions and publication bias were generated by STATA 17.0 software.

Results: We included eight randomized controlled trials (RCTs) involving a total of 1192 women with PE; two studies were of high quality and six were of moderate quality. Eight interventions were addressed in the NMA. In the DMA, we found that blood pressure in the Ketanserin group were significantly higher than those in the Nicardipine group. NMA showed that blood pressure in the Dihydralazine group was significantly higher than that in the Methyldopa, Labetalol, Nicardipine and Diltiazem groups. And the blood pressure in the Labetalol group was significantly lower than that in the Nicardipine group. SUCRA values showed that Diltiazem was more effective in lowering blood pressure than other drugs looked at in this study.

Conclusion: According to the eight RCTs included in this study, Diltiazem was the most effective in reducing blood pressure in PE patients; Labetalol and Nicardipine also had good effects. Diltiazem is preferred for the treatment of patients with severe PE and high blood pressure.

Objectives: To assess the ability of the USCOM® (USCOM), using measurements of cardiac output (CO) and systemic vascular resistance (SVR), to predict the development of pre-eclampsia (PE) and severe PE in hypertensive pregnancies.

Study design: Prospective cohort study of women in the second or third trimester recruited at a tertiary center in Sydney, Australia. Demographic data and hemodynamic measurements using the USCOM were taken for all study participants at recruitment. Pregnancy outcome, including development of PE and severe PE, was tracked. Data were analyzed using ANOVA testing, pair-wise comparison testing, and Student's t-testing.

Results: Recruitment included 65 normotensive controls, 34 women with chronic hypertension (CH), 51 with gestational hypertension (GH), and 21 with PE. Significantly higher weight, body surface area, and blood pressure measurements were found in the hypertensive, compared with the normotensive control and pregnancies. There were no observed differences in USCOM-measured CO, cardiac index, SVR, or systemic vascular resistance index between hypertensive women who did versus did not develop PE or severe PE in later pregnancy. Analysis of the CH and GH subgroups, as well as only unmedicated hypertensive women (n = 24), also showed no significant difference in hemodynamic parameters between those who did or did not develop PE or severe PE.

Conclusions: Our group was unable to successfully predict the onset of PE or severe PE based on hemodynamic parameters measured with the USCOM. It is possible this relates to the high proportion of women on antihypertensive medication at recruitment.

The diagnostic criteria for preeclampsia do not accurately reflect the pathophysiological characteristics of patients with preeclampsia. Conventional biomarkers and diagnostic approaches have proven insufficient to fully comprehend the intricacies of preeclampsia. This study aimed to screen differentially abundant metabolites as candidate biomarkers for preeclampsia. A propensity score matching method was used to perform a 1:1 match between preeclampsia patients (n = 70) and healthy control individuals (n = 70). Based on univariate and multivariate statistical analysis methods, the different characteristic metabolites were screened and identified. Least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently used to further screen for differentially abundant metabolites. A receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic efficacy of the metabolites. A total of 1,630 metabolites were identified and quantified in maternal serum samples. Fifty-three metabolites were significantly increased, and two were significantly decreased in preeclampsia patients. The area under the curve (AUC) of the model composed of isobutyryl-L-carnitine and acetyl-leucine was 0.878, and the sensitivity and specificity in detecting preeclampsia were 81.4% and 87.1%, respectively. There are significant differences in metabolism between preeclampsia patients and healthy pregnant women, and a range of novel biomarkers have been identified. These findings lay the foundation for the use of metabolomic biomarkers for the diagnosis of preeclampsia.