B3904 - Comparison of blood pressure measures for assessing risk of adverse outcomes in pregnancy - 25/10/2021

B number: 
B3904
Principal applicant name: 
Amy Taylor | University of Bristol (United Kingdom)
Co-applicants: 
Professor Abigail Fraser
Title of project: 
Comparison of blood pressure measures for assessing risk of adverse outcomes in pregnancy
Proposal summary: 

Blood pressure is routinely measured during pregnancy and is important for determining the risk of experiencing adverse pregnancy outcomes including pre-eclampsia, gestational hypertension, preterm birth, having a small for gestational age baby, and gestational diabetes. There is evidence that measurement early in pregnancy of integrative measures of systolic and diastolic blood pressure may be more important than individual blood pressure measures for predicting which women may go on to experience hypertensive disorders of pregnancy (preeclampsia and gestational hypertension). For example, mean arterial pressure (MAP) calculated as (systolic blood pressure + 2 x diastolic blood pressure)/3 has been shown to be a better predictor of pre-eclampsia than systolic blood pressure (SBP) or diastolic blood pressure (DBP). However, to our knowledge, there have been no direct comparisons of a range of different measures of blood pressure (SBP, DBP, MAP, pulse pressure (PP), mid blood pressure) on all of these adverse pregnancy outcome (APO) subtypes at a the same timepoint early in pregnancy. This research aims to look at which measures/derived measures of blood pressure best predict pre-eclampsia, gestational hypertension, preterm birth, small for gestational age (SGA) and gestational diabetes.

Impact of research: 
A direct comparison of blood pressure measures taken at the same time during pregnancy should give a clearer picture to clinicians of which blood pressure measures are most informative for determining risk of APOs.
Date proposal received: 
Monday, 11 October, 2021
Date proposal approved: 
Monday, 25 October, 2021
Keywords: 
Epidemiology, Hypertension, Statistical methods, Blood pressure