Role of Fetal Medicine Foundation (FMF) Instrument as a Screening Pre-eclampsia: A Cohort Study - Latifah, Murwani Emasrissa; Bernolian, Nuswil; Lestari, Peby Maulina; Mirani, Putri; Martadiansyah, Abarham; Sutrisno, Alfarisi; Andrina, Hana; Stevanny, Bella (Journal of Posthumanism, 2025)
Maternal death is still a problem among pregnant women. One of the most prevalent causes of maternal death is preeclampsia. Preeclampsia contributes not only to maternal death, but also increases fetal morbidity. Early screening for preeclampsia is a key factor to managing the condition. The Fetal Medicine Foundation (FMF) has developed an algorithm to predict preeclampsia during the first trimester of pregnancy. However, there has been lack of studies done in Indonesia its usage. Therefore, this study aims to examine the accuracy of the FMF algorithm as a screening tool to identify preeclampsia in women in the first trimester of pregnancy. //Prospective cohort study done in Obstetrics and Gynecology Department of Mohammad Hoesin Hospital Palembang in January-December 2023. Sixty subjects that met the inclusion criteria were followed from 11 to 13+6 weeks to birth. All subjects undergo history taking for maternal and obstetrics history, physical examination, in particular mean arterial pressure (MAP) measurement, ultrasonography examination to evaluate mean uterine artery pulsatility index (UtA-PI), crown-rump length (CRL), and laboratory testing for pregnancy-associated plasma protein-A [PAPP-A] and placental growth factor [PlGF]. The outcome of this study is the incidence of preeclampsia as well as the detection rate (accuracy rate), false positive rate, positive predictive value (PPV), and negative predictive value (NPV) of the FMF algorithm. Data were analyzed using SPSS version 25.0 with a significance level of p <0.05 and a 95% CI. Kolmogorov Smirnov test was used for data homogeneity, Chi-square or Fisher test for categorical data, One way anova and Kruskal wallis test for numerical data. Sixty subjects were enrolled. Among these, 30 subjects subsequently developed preeclampsia, with 18 (30%) experiencing early-onset preeclampsia, 12 (20%) experiencing late-onset preeclampsia, and 30 (50%) not developing preeclampsia (normotension). There was no significant difference in maternal characteristics and obstetric history among the three groups. MAP is found to be significantly different, with the highest found in the early onset preeclampsia group (p=0.021). Uterine artery pulsatility index (UtA-PI) was significantly higher in early-onset and late-onset preeclampsia subjects (p=0.019). There was no significant difference among the three groups in CRL. Serum PIGF was significantly lower in early onset and late-onset preeclampsia subjects (p-0.0001). Serum PAPP-A is also significantly lower in the early-onset preeclampsia subjects (p=0.0002). The combination of FMF/MAP, UtA-PI, yields the highest accuracy in predicting preeclampsia with 100% values for sensitivity, specificity, PPV, and NPV (p=0,000). The other combinations show lower accuracy, but quite good values of specificity and sensitivity. The FMF algorithm is an accurate screening tool to identify preeclampsia in the first trimester of pregnancy.