Biophysical and biochemical prediction of preeclampsia at 20-24 weeks’ gestation
- Gallo Gordillo, Dahiana Marcela
- Kypros H. Nicolaides Director
- Francisca S. Molina García Co-director
Defence university: Universidad de Granada
Fecha de defensa: 19 October 2016
- Cristina Campoy Folgoso Chair
- Olga Ocón Hernández Secretary
- Nicola Persico Committee member
- Catalina De Paco Matallana Committee member
- Walter Plasencia Acevedo Committee member
Type: Thesis
Abstract
Introduction Preeclampsia (PE) affects 2-3% of all pregnancies and is a major cause of maternal and perinatal morbidity and mortality1,2. The traditional approach to screening for PE is to identify risk factors from maternal demographic characteristics and medical history (maternal factors).3,4 According to ACOG, taking a medical history to evaluate for risk factors is currently the best and only recommended screening approach for PE.3 In the UK, the National Institute for Health and Clinical Excellence (NICE) has issued guidelines recommending that women should be considered to be at high-risk of developing PE if they have any one high-risk factor or any two moderate-risk factors.4 However, the performance of such approach, which essentially treats each risk factor as a separate screening test with additive detection rate (DR) and screen positive rate, is poor with DR of only 35% of all-PE and 40% of preterm-PE requiring delivery at <37 weeks’ gestation, at false positive rate (FPR) of about 10%.5 An alternative approach to screening, which allows estimation of individual patient-specific risks of PE requiring delivery before a specified gestation, is to use Bayes theorem to combine the a priori risk from maternal factors, derived by a multivariable logistic model, with the results of various combinations of biophysical and biochemical measurements made at different times during pregnancy5-8. We have previously reported that first-trimester screening by a combination of maternal factors with mean arterial pressure (MAP), uterine artery pulsatility index (UTPI) and serum placental growth factor (PLGF) can predict 75% of preterm-PE and 47% of term-PE, at 10% FPR 8. Aims The objectives of this study of singleton pregnancies with data on MAP, UTPI, PLGF and serum soluble fms-like tyrosine kinase-1 (SLFT) at 19-24 weeks’ gestation are: 1. To develop a model for prediction of PE using combined screening by maternal characteristics and medical history, uterine artery PI, MAP, serum PLGF and sFLT-1 at 20-24 weeks’ gestation. 2. To explore the possibility of carrying out routine screening for preterm-PE by maternal factors and MAP in all pregnancies and reserving measurements of UTPI and PLGF only for a subgroup of the population selected on the basis of the risk derived from screening by maternal factors and MAP alone. 3. To determine maternal characteristics affecting uterine artery PI in normal pregnancies at 20-24 weeks’ gestation and examine in pregnancies with PE the relation between uterine artery PI MoM and severity of disease. 4. To assess the performance of screening for PE by MAP at 11-13 and at 20-24 weeks’ gestation. Methodology This is a prospective screening for adverse obstetric outcomes in women attending for their routine hospital visit at 11-13 and/or 19-24 weeks’ gestation in three maternity hospitals in England between January 2006 and July 2014. We had data from maternal factors, uterine artery pulsatility index (UTPI), mean arterial pressure (MAP), serum placental growth factor (PLGF) and serum soluble fms-like tyrosine kinase-1 (SFLT) from 123,406, 67,605, 31,120, 10,828 and 8,079 pregnancies, respectively. Bayes theorem was used to combine the a priori risk from maternal factors with various combinations of biomarker multiple of the median (MoM) values. The modeled performance of screening for PE requiring delivery at <32, <37 and >37 weeks’ gestation was estimated. The modeled performance was compared to the empirical one which was derived from five-fold cross validation. We also examined the performance of screening based on risk factors from the medical history, as recommended by ACOG and NICE guidelines. Conclusions 1. The performance of screening for PE by maternal factors and biomarkers in the mid-trimester is superior to taking a medical history. 2. The high DR of preterm-PE can be achieved by two-stage screening in the first- and second-trimester with maternal factors and MAP in the whole population and measurements of UTPI and PLGF in only some of the pregnancies. 3. UTPI is affected by maternal characteristics. In women that develop PE, UTPI at 20-24 weeks’ gestation is increased and the increase is particularly marked in those with early-PE and in PE wth SGA. 4. MAP must be adjusted for maternal characteristics and medical history and expressed as MoM before valid comparisons can be carried out between normal and pathological pregnancies. The performance of screening for PE by MAP MoM is best when measurements are taken at both 11-13 and 20-24 weeks' gestation than at only one of these gestational ranges. Español Introducción La Preeclampsia (PE) afecta al 2-3% de todos los embarazos y es la principal causa de morbi-mortalidad materna y perinatal1,2. El modelo tradicional para cribado de PE es identificar factores de riesgo a partir de caracteristicas demográficas maternas e historia médica (factores maternos) 3,4.De acuerdo al Colegio Americano de Ginecología y Obstetricia (ACOG), el mejor y único método de cribado de PE recomendado actualmente es la historia médica por medio de la cual se evaluan factores de riesgo3. En el Reino Unido, el Instituto Nacional de Salud y Excelencia Clínica (NICE) ha establecido unas guías de recomendación donde las mujeres deben ser consideradas alto riesgo de desarrollar PE si tienen un factor de riesgo mayor o dos factores de riesgo moderado4. Sin embargo, este método trata esencialmente cada factor de riesgo como un test de cribado separado con una tasa de detección (TD) sumativa y la TD es pobre de solo 35% para todas las PE Y 40% para PE temprana requiriendo parto <37 semanas de gestación a una tasa de falsos positivos (TFP) del 10%.5 Un método de cribado alternativo que estima los riesgos individuales y especificos para PE de cada paciente requiriendo parto antes de una edad gestacional especifica es usando el teorema de Bayes que combina el riesgo previo de los facores maternos, derivado de un modelo logistico multivariable con los resultados de varias combinaciones de medidas biofisicas y bioquimicas realizadas a diferentes edades gestacionales 5-8. Nosotros hemos reportado previamenteque el cribado del primer trimestre usando una combinación de factores maternos con PAM, IPAU y factor de crecimiento placentario puede predecir 75% de la preeclampsia temprana y 47% de PE al termino a una TFP del 10% 8. Objetivos Los objetivos de este estudio en embarazos únicos con datos de PAM, IPAU, factor de crecimiento placentario y soluble tirosin kinasa-1 son: 1.Desarrollar un modelo para PE basado en la combinación de factores maternos con biomarcadores en el segundo trimestre. 2. Explorar la posibilidad de realizar un cribado de rutina para preeclampsia temprana por factores maternos y PAM en todos los embarazos y reservar medidas del índice de pulsatilidad de la arteria uterina y factor de crecimiento placentario solo para un subgrupo de población seleccionado con base en el riesgo derivado del cribado por factores maternos y PAM solamente. 3. Determinar las características maternas que afectan el índice de pulsatilidad de la arteria uterina (IPAU) en embarazos normales a las 20-24 semanas de gestación y segundo, examinar en los embarazos con preeclampsia (PE) la relación entre los multiplos de la mediana (MoM) de la arteria uterina y la severidad de la enfermedad. 4. Evaluar el desempeño del cribado para PE usando presión arterial media (PAM) entre 11-13 y 20-24 semanas. Metodología Este es un estudio prospectivo de resultados obstétricos adversos en mujeres que acuden a su visita de rutina al hospital entre 11-13 semanas y 19-24 semanas de gestación en tres hospitales de maternidad en Inglaterra entre enero del 2006 y julio del 2014. Teníamos datos de factores maternos, índice de pulsatilidad de la arteria uterina (IPAU), presión arterial media (PAM), factor de crecimiento placentario sérico y tirosina quinasa-1 sérica en 123.406, 67.605, 31.120, 10.828 y 8.079 embarazos respectivamente. El teorema de Bayes se utilizó para combinar el riesgo a priori de los factores maternos con varias combinaciones de los multiplos de la mediana (MoM) de biomarcadores. Se estimó el rendimiento del modelo de detección de PE requiriendo parto antes de las 32, 37 y mayor a las 37 semanas de gestación. El modelo de cribado de preeclampsia se comparó con el modelo empírico el cual se deriva de una validación cruzada. También se examinó el rendimiento del cribado basado en los factores de riesgo a partir de la historia clínica, según lo recomendado por el ACOG y las guías NICE. Conclusiones 1.El rendimiento del cribado de PE por factores maternos y biomarcadores en la mitad del trimestre es superior que la historia medica. 2.La alta tasa de detección de preeclampsia temprana se puede lograr mediante un cribado de dos etapas en el primer y segundo trimestre con factores maternos y PAM en toda la población y mediciones de IPAU y factor de crecimiento placentario sólo en algunos de los embarazos. 3.El IP de la arteria uterina se ve afectado por las características maternas. En mujeres que desarrollaron PE, el IP de la arteria uterina entre las 20-24 semanas de gestación está incrementado y el incremento es particularmente marcado en aquellos con PE temprana y en PE con PEG. 4. PAM tiene que ser ajustada por caracteristicas maternas e historia médica y debe ser expresada en MoM antes de hacer comparaciones válidas entre embarazos normales y patológicos. El rendimiento del cribado para PE por PAM expresado en MoM es mejor cuando se toman ambas medidas, a las 11-13 y 20-24 semanas que cuando se toma uno de los dos rangos de edad gestacional. Referencias 1. World Health Organization. Make Every Mother and Child Count. World Health Report, Geneva, Switzerland 2005. 2. Knight M, Kenyon S, Brocklehurst P, Neilson J, Shakespeare J, Kurinczuk JJ (Eds.) on behalf of MBRRACEUK. Saving Lives, Improving Mothers’ Care - Lessons learned to inform future maternity care from the UK and Ireland Confidential Enquiries into Maternal Deaths and Morbidity 2009-12. Oxford: National Perinatal Epidemiology Unit, University of Oxford 2014. 3. ACOG. First-trimester risk assessment for early-onset preeclampsia. Committee opinion No. 638. Obstet Gynecol 2015;126:e25-7. 4. National Collaborating Centre for Women's and Children's Health (UK). Hypertension in Pregnancy: The Management of Hypertensive Disorders During Pregnancy. London: RCOG Press, 2010. 5. Wright D, Syngelaki A, Akolekar R, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal characteristics and medical history. Am J Obstet Gynecol 2015;DOI:10.1016/j.ajog.2015.02.018. 6. Wright D, Akolekar R, Syngelaki A, Poon LC, Nicolaides KH. A competing risks model in early screening for preeclampsia. Fetal Diagn Ther 2012;32:171-8. 7. Akolekar R, Syngelaki A, Poon L, Wright D, Nicolaides KH. Competing risks model in early screening for preeclampsia by biophysical and biochemical markers. Fetal Diagn Ther 2013;33:8-15. 8. O’Gorman N, Wright D, Syngelaki A, Akolekar R, Wright A, Poon LC, Nicolaides KH. Competing risks model in screening for preeclampsia by maternal factors and biomarkers at 11-13 weeks’ gestation. Am J Obstet Gynecol 2015; in press