OBJECTIVES: To determine the value of combined screening for pre-eclampsia by maternal history, and mid-trimester uterine artery (UtA) Doppler imaging and maternal blood pressure. METHODS: In 3529 singleton pregnancies attending for routine care at 22-24 weeks' gestation we recorded maternal variables, and made UtA Doppler and mean arterial pressure (MAP) measurements. Multiple regression analysis was used to determine the significant predictors of pre-eclampsia, gestational hypertension and small-for-gestational age (SGA) among maternal characteristics, UtA pulsatility index (PI) and MAP. RESULTS: Complete pregnancy outcomes were available in 3359/3529 (95.2%) cases. Pre-eclampsia developed in 101 (3.0%) pregnancies, including 23 (0.7%) in which delivery was before 34 weeks (early pre-eclampsia) and 78 (2.3%) with delivery at 34 weeks or more (late pre-eclampsia); 74 (2.2%) developed gestational hypertension, 366 (10.9%) delivered SGA newborns with no hypertensive disorders, and 2806 (83.8%) were unaffected by pre-eclampsia, gestational hypertension or SGA. Multiple regression analysis demonstrated that maternal characteristics, UtA-PI and MAP provided a significant independent contribution in the prediction of pre-eclampsia, gestational hypertension and SGA. For a false-positive rate of 10%, the estimated detection rates of early and late pre-eclampsia were 100% and 56.4%, respectively. CONCLUSIONS: The combination of maternal demographic characteristics, and UtA Doppler and maternal blood pressure measurements is an effective screening tool for the prediction of pre-eclampsia. (c) 2008 ISUOG.
OBJECTIVES: To determine the value of combined screening for pre-eclampsia by maternal history, and mid-trimester uterine artery (UtA) Doppler imaging and maternal blood pressure. METHODS: In 3529 singleton pregnancies attending for routine care at 22-24 weeks' gestation we recorded maternal variables, and made UtA Doppler and mean arterial pressure (MAP) measurements. Multiple regression analysis was used to determine the significant predictors of pre-eclampsia, gestational hypertension and small-for-gestational age (SGA) among maternal characteristics, UtA pulsatility index (PI) and MAP. RESULTS: Complete pregnancy outcomes were available in 3359/3529 (95.2%) cases. Pre-eclampsia developed in 101 (3.0%) pregnancies, including 23 (0.7%) in which delivery was before 34 weeks (early pre-eclampsia) and 78 (2.3%) with delivery at 34 weeks or more (late pre-eclampsia); 74 (2.2%) developed gestational hypertension, 366 (10.9%) delivered SGA newborns with no hypertensive disorders, and 2806 (83.8%) were unaffected by pre-eclampsia, gestational hypertension or SGA. Multiple regression analysis demonstrated that maternal characteristics, UtA-PI and MAP provided a significant independent contribution in the prediction of pre-eclampsia, gestational hypertension and SGA. For a false-positive rate of 10%, the estimated detection rates of early and late pre-eclampsia were 100% and 56.4%, respectively. CONCLUSIONS: The combination of maternal demographic characteristics, and UtA Doppler and maternal blood pressure measurements is an effective screening tool for the prediction of pre-eclampsia. (c) 2008 ISUOG.
Authors: Silvia Visentin; Ambrogio P Londero; Martina Camerin; Enrico Grisan; Erich Cosmi Journal: Medicine (Baltimore) Date: 2017-01 Impact factor: 1.889
Authors: Edward Antwi; Rolf H H Groenwold; Joyce L Browne; Arie Franx; Irene A Agyepong; Kwadwo A Koram; Kerstin Klipstein-Grobusch; Diederick E Grobbee Journal: BMJ Open Date: 2017-01-16 Impact factor: 2.692
Authors: Seung Woo Yang; Soo Hyun Cho; Young Sun Kang; Seung Hwa Park; In Sook Sohn; Han Sung Kwon; Han Sung Hwang Journal: PLoS One Date: 2019-01-30 Impact factor: 3.240
Authors: Corrie Macdonald-Wallis; Richard J Silverwood; Bianca L de Stavola; Hazel Inskip; Cyrus Cooper; Keith M Godfrey; Sarah Crozier; Abigail Fraser; Scott M Nelson; Debbie A Lawlor; Kate Tilling Journal: BMJ Date: 2015-11-17
Authors: Max Mönckeberg; Valentina Arias; Rosario Fuenzalida; Santiago Álvarez; Victoria Toro; Andrés Calvo; Juan P Kusanovic; Lara J Monteiro; Manuel Schepeler; Jyh K Nien; Jaime Martinez; Sebastián E Illanes Journal: Diagnostics (Basel) Date: 2020-03-26