Authors: Frances Conti-Ramsden MBBS Academic Clinical Fellow, Carolyn Gill PhD BRC Research Assistant, Paul T Seed MSc CStat Senior Lecturer in Medical Statistics, Kate Bramham PhD Clinical Senior Lecturer in Nephrology Lucy C Chappell PhD NIHR Research Professor in Obstetrics, Fergus P McCarthy PhD Clinical Senior Lecturer in Obstetrics and Gynaecology.
Objectives: To determine whether glycogen phosphorylase isoenzyme B (GPBB) and/or brain natriuretic peptide (BNP) concentrations are elevated in pre-eclampsia and superimposed pre-eclampsia (SPE), demonstrating cardiac ischaemia and strain.
Study Design: A nested case-control study was performed using samples and clinical data available from a prospective pregnancy cohort. Four groups were selected: healthy pregnant controls (n = 21), pre-eclampsia (n = 19), pre-existing chronic hypertension (CHT) and/or chronic kidney disease (CKD) without (n = 20) or with superimposed pre-eclampsia (SPE) (n = 19). Plasma samples were taken at time of disease or the third trimester in controls.
Main Outcome Measures: Plasma concentrations of GPBB and BNP.
Results: There was no significant difference in GPBB plasma concentrations between controls and pre-eclampsia (geometric mean (GM) [95% CI]: 4.74 [2.54-8.84]ng/mL vs 5.01 [2.58-9.74]ng/mL, p = 0.90)), or between CHT and/or CKD and SPE (GM [95% CI]: 9.49 [4.93-18.25]ng/mL vs 10.24 [5.27-19.92]ng/mL, p = 0.87). BNP plasma concentrations were significantly raised in women with pre-eclampsia compared to controls (GM [95% CI]: 31.83 [20.18-50.22]pg/mL vs 11.33 [7.34-17.51]pg/mL, p = 0.001). Women with CKD, but not CHT, who developed SPE had elevated BNP concentrations. There were no significant differences in BNP concentration between women with comorbidity (CHT and/or CKD) and controls.
Conclusions: GPBB has a limited role as a biomarker in hypertensive disorders of pregnancy. BNP concentrations were elevated in pre-eclampsia compared to controls. This suggests cardiac strain at the time of pre-eclampsia. Further studies are needed to examine whether BNP can identify women at increased risk of cardiovascular disease.
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http://dx.doi.org/10.1016/j.ejogrb.2019.04.034 | DOI Listing |
JAMA Netw Open
January 2025
Magee-Womens Research Institute, Department of Obstetrics, Gynecology and Reproductive Sciences, Epidemiology and Clinical and Translational Research, University of Pittsburgh, Pittsburgh, Pennsylvania.
Importance: Chronic hypertension and preeclampsia are leading risk enhancers for maternal-neonatal morbidity and mortality. Severe maternal morbidity (SMM) indicators include heart, kidney, and liver disease, but studies have not excluded patients with preexisting diseases that define SMM. Thus, SMM risks for uncomplicated chronic hypertension specific to preeclampsia remain unclear.
View Article and Find Full Text PDFIntroduction And Objective: As thresholds for the diagnosis of gestational diabetes mellitus (GDM) become lower, and the prevalence of obesity in society rises, more pregnant women will be diagnosed with GDM and hypertension. Both conditions hold dangers for mother and baby. Our objective was to properly describe this association.
View Article and Find Full Text PDFSci Rep
December 2024
Laboratorio de Medicina Experimental, Hospital Alemán, Av. Pueyrredón 1640, C1118AAT, Ciudad Autónoma de Buenos Aires, Argentina.
Chronic hypertension is an increasingly prevalent condition that constitutes a risk factor for superimposed preeclampsia during pregnancy. In this study, we assessed the gut microbiome in a rat model of superimposed preeclampsia to characterize the microbial signature associated with defective placentation processes identified at the preclinical disease stage. The blood pressure profile, renal function parameters and fetal phenotype were evaluated in pregnant Stroke-prone Spontaneously Hypertensive Rats (SHRSP) and their normotensive controls.
View Article and Find Full Text PDFBMC Pregnancy Childbirth
December 2024
Department of Computer Science, Columbia University, 1214 Amsterdam Ave, 721 Schapiro CEPSR, New York, NY, 10027, USA.
Preeclampsia is one of the leading causes of maternal morbidity, with consequences during and after pregnancy. Because of its diverse clinical presentation, preeclampsia is an adverse pregnancy outcome that is uniquely challenging to predict and manage. In this paper, we developed racial bias-free machine learning models that predict the onset of preeclampsia with severe features or eclampsia at discrete time points in a nulliparous pregnant study cohort.
View Article and Find Full Text PDFAust J Gen Pract
December 2024
BMed, Obstetrics and Gynaecology Senior Health Medical Officer, Joan Kirner Women@s and Children@s Hospital, Melbourne, Vic.
Background: Hypertensive disorders in pregnancy (HDIP) are among the leading causes of maternal and perinatal morbidity and mortality and should not be reserved for specialist care and expertise.1 General practitioners (GPs) are inevitably involved in the care of women with HDIP, particularly in the preconception, early pregnancy and postpartum periods and, also, as shared maternity care providers. It is, therefore, critical that GPs can assess and manage HDIP.
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