Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.762398
Title: Development of a first trimester prediction model for preeclampsia and prospective validation in a multicentre setting
Author: O'Gorman, Neil Matthew
ISNI:       0000 0004 7656 5497
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2018
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Abstract:
Preeclampsia affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality. In the last ten years, extensive research has been devoted to screening for preeclampsia with the aim of reducing the prevalence of the disease through pharmacologic intervention in the high-risk group and to minimize perinatal morbidity and mortality by tailoring antenatal care accordingly to determine the appropriate time and place for delivery. The purpose of this study was to develop a first trimester screening model for preeclampsia combining a variety of elements from the maternal demographic characteristics and medical history with biophysical and biochemical markers. This model was subsequently prospectively validated on a new dataset. The efficacy of the developed screening model was then compared to the first trimester approaches to screening recommended by the National Institute for Health and Care Excellence and the American College of Obstetricians and Gynecologists. The material covered in this thesis was published in three papers in peer reviewed journals. The first publication involved using data from 35,948 singleton pregnancies that included 1,058 preeclamptic pregnancies (2.9%). Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of uterine artery pulsatility index, mean arterial pressure, serum pregnancy-associated plasma protein-A, and placental growth factor multiple of the median values. Five-fold cross validation was used to assess the performance of screening for preeclampsia in pregnant women that delivered at < 37 weeks’ gestation and ≥37 weeks’ gestation by models that combined maternal factors with individual biomarkers and their combination with screening by maternal factors alone In pregnancies that experienced preeclampsia, the values of uterine artery PI and mean arterial pressure were increased, and the values of serum pregnancy-associated plasma protein-A and placental growth factor were decreased. For all biomarkers, the deviation from normal was greater for early than late preeclampsia; therefore, the performance of screening was related inversely to the gestational age at which delivery became necessary for maternal and/or fetal indications. Combined screening by maternal factors, uterine artery PI, mean arterial pressure, and placental growth factor predicted 75%, of preeclampsia < 37 weeks and 47% preeclampsia ≥37 weeks’ gestation, at a false positive rate of 10%. The second study examined the diagnostic accuracy of the above model in a prospective first-trimester multicentre study of screening for preeclampsia in 8775 singleton pregnancies. The detection rates (DRs) and false-positive rates (FPRs) for delivery with preeclampsia < 32, < 37 and ≥37 weeks’ gestation were estimated and compared with those for the dataset used for development of the algorithm. In this study population, 239 (2.7%) cases developed PE, of which 17 (0.2%), 59 (0.7%) and 180 (2.1%) developed preeclampsia < 32, < 37 and ≥37 weeks’ gestation, respectively. With combined screening using the above model, the DR was 100% for preeclampsia < 32 weeks, 75% for preeclampsia < 37 weeks and 43% for PE ≥37 weeks, at a 10% FPR. These DRs were similar to the estimated rates for the dataset used for development of the model: 89% for preeclampsia < 32 weeks, 75% for PE < 37 weeks and 47% for PE ≥37 weeks. The third component of this thesis was to compare the performance of screening for preeclampsia based on risk factors from the medical history, as recommended by NICE and ACOG, with our model developed in the first study. Screening with use of NICE guidelines detected 41% of preeclampsia at < 32 weeks, 39% of PE at < 37 weeks and 34% of PE at ≥37 weeks, at 10.2% FPR. Screening with use of ACOG recommendations detected 94% of PE at < 32 weeks, 90% of PE at < 37 weeks and 89% ≥37 weeks, at 64.2% FPR. Screening based on the ACOG recommendations for use of aspirin only detected 6% of PE at < 32 weeks, 5% of PE at < 37 weeks and 2% of PE at ≥37 weeks, at a 0.2% FPR. The findings of these studies demonstrate that a combination of maternal factors, biophysical and biochemical markers can effectively identify women at high-risk of developing early preeclampsia and that the model developed in this study performs better than the screening approaches recommended by NICE and ACOG.
Supervisor: Poon, Chiu Yee Liona ; Nicolaides, Kypros Herodotou Sponsor: Not available
Qualification Name: Thesis (M.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.762398  DOI: Not available
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