Abstract
BACKGROUND: Milk fat globule-epidermal growth factor 8 (MFG-E8) is expressed in the endometrial epithelium and its expression increases during the implantation process. Due to this knowledge, we aimed to investigate the maternal serum MFG-E8 levels on both healthy pregnant women in the first trimester and pregnant women complicated with missed abortion and threatened abortion in the first trimester. METHODS: This prospective, cross-sectional study was conducted in a tertiary referral hospital, department of obstetrics between July 2020 and February 2021 after ethical committee approval. The study population was consisted of 30 healthy pregnant women (HP) in the first trimester, 30 pregnant women suffering from threatened abortion (TA) in the first trimester and 30 pregnant women suffering from missed abortion (MA) in the first trimester. Maternal serum MFG-E8 levels were analyzed with enzyme linked immunosorbent assay. Delivery and neonatal outcomes of the study population was evaluated. The continuous variables were compared among three groups with variance analysis with post hoc tests. The categorical variables were compared with chi-square and Fisher's exact tests where applicable. RESULTS: The mean age of the study population was 29.36 ± 5.31 years. There was no significant difference among three groups for parameters of age, body mass index, parity number, and gestational week. Despite being within normal ranges, the mean neutrophil and international normalized ratio values of the three groups showed statistically significant difference (p < 0.05). The mean maternal serum MFG-E8 levels of MA, TA, and HP groups were 270 ± 152.3, 414.7 ± 236.7, and 474 ± 222.5 ng/mL, respectively (p = 0.001). It was found that mean of MFG-E8 of the MA group was statistically significantly lower than those of the other two groups (p < 0.05). DISCUSSION: Although maternal serum MFG-E8 level seems to be a parameter that differ between live and nonlive pregnancies, studies with large number of cases are needed to discuss our results and to determine a cut-off value for prediction.