OBJECTIVE: The objective of this study is to evaluate the predictive performance of the Fetal Medicine Foundation (FMF) algorithm for prediction of preeclampsia (PE) between 11 and 14 weeks of gestation in an unselected Brazilian population. METHODS: We conducted a prospective cohort study with 617 singleton pregnancies of unselected risk. Biophysical markers (mean pulsatility index, mean arterial pressure) and biochemical markers (placental growth factor (PLGF) and PAPP-A) were inserted into the FMF software and converted into multiples of the median (MoM). The subjects were divided into five groups: early-onset PE, parturition <34 weeks' gestation; preterm PE, parturition <37 weeks; PE, parturition at any gestational age; gestational hypertension (GH); and control group. Areas under the receiver operating characteristics curve (AUC) were calculated for the outcomes. RESULTS: Among 617 patients, seven developed early-onset PE, 18 developed preterm PE (seven early PE plus 11 delivered between 34 and 36 + 6 weeks gestation), 34 developed PE (18 preterm PE plus 16 delivered after 37-week gestation), 12 pregnant women developed GH, and 517 women comprised the control group. The best predictive performance using the FMF algorithm occurred in the early-onset PE group, with AUC = 0.946 (95% CI 0.919-0.973) and the detection rate of 28.6% and 85.7% for 5% and 10% false-positive (FP), respectively. CONCLUSIONS: The FMF algorithm to predict PE was effective in a Brazilian population, mainly in the early-onset form of the disease at 10% FP.
OBJECTIVE: The objective of this study is to evaluate the predictive performance of the Fetal Medicine Foundation (FMF) algorithm for prediction of preeclampsia (PE) between 11 and 14 weeks of gestation in an unselected Brazilian population. METHODS: We conducted a prospective cohort study with 617 singleton pregnancies of unselected risk. Biophysical markers (mean pulsatility index, mean arterial pressure) and biochemical markers (placental growth factor (PLGF) and PAPP-A) were inserted into the FMF software and converted into multiples of the median (MoM). The subjects were divided into five groups: early-onset PE, parturition <34 weeks' gestation; preterm PE, parturition <37 weeks; PE, parturition at any gestational age; gestational hypertension (GH); and control group. Areas under the receiver operating characteristics curve (AUC) were calculated for the outcomes. RESULTS: Among 617 patients, seven developed early-onset PE, 18 developed preterm PE (seven early PE plus 11 delivered between 34 and 36 + 6 weeks gestation), 34 developed PE (18 preterm PE plus 16 delivered after 37-week gestation), 12 pregnant women developed GH, and 517 women comprised the control group. The best predictive performance using the FMF algorithm occurred in the early-onset PE group, with AUC = 0.946 (95% CI 0.919-0.973) and the detection rate of 28.6% and 85.7% for 5% and 10% false-positive (FP), respectively. CONCLUSIONS: The FMF algorithm to predict PE was effective in a Brazilian population, mainly in the early-onset form of the disease at 10% FP.
Entities:
Keywords:
Brazilian population; fetal medicine foundation; first trimester; prediction; preeclampsia
Authors: Liona C Poon; Andrew Shennan; Jonathan A Hyett; Anil Kapur; Eran Hadar; Hema Divakar; Fionnuala McAuliffe; Fabricio da Silva Costa; Peter von Dadelszen; Harold David McIntyre; Anne B Kihara; Gian Carlo Di Renzo; Roberto Romero; Mary D'Alton; Vincenzo Berghella; Kypros H Nicolaides; Moshe Hod Journal: Int J Gynaecol Obstet Date: 2019-05 Impact factor: 3.561
Authors: Edward Antwi; Mary Amoakoh-Coleman; Dorice L Vieira; Shreya Madhavaram; Kwadwo A Koram; Diederick E Grobbee; Irene A Agyepong; Kerstin Klipstein-Grobusch Journal: PLoS One Date: 2020-04-21 Impact factor: 3.240