Акушерство, гинекология и репродукция (Jan 2023)
Predicting fetal growth retardation: mathematical modeling
Abstract
Introduction. Annually, more than 13 million neonates are born with fetal growth retardation (FGR) worldwide. FGR increases prenatal mortality and morbidity. Due to no effective treatments for FGR are available, its prevention and prognosis are of extreme relevance.Aim: development of prognostic clinical and anamnestic mathematical model for assessing a risk of developing FGR during pregnancy.Materials and Methods. A prospective, controlled, open, continuous study was performed. The main group (1) included 75 patients who had FGR during pregnancy; the control group (2) consisted of 414 women with favorable pregnancy outcome. All subjects underwent examination, including collecting medical history, a complex of prenatal diagnostics in the first trimester of pregnancy – ultrasound, Doppler uterine arteries, serum level of pregnancy-associated plasma protein-A (PAPP-A), free beta-subunit of human chorionic gonadotropin (β-hCG), placental growth factor (PlGF), and non-invasive prenatal test (NIPT).Results. To determine the relative contribution of each individual trait to the formation of FGR risk and develop a prognostic index, a discriminant analysis was carried out, on the basis of which a prognostic F-index was developed. The formula for calculating the F-index includes the age of pregnant woman, obstetric history data, method of conception, recorded nicotine addiction in pregnancy, detected uterine fibroids, body mass index, biochemical parameters (PAPP-A, β-hCG, PlGF), nuchal translucency of the fetus, the pulsation index of the uterine artery, the level of the fetal fraction and fetal gender (determined during NIPT). The parameters of sensitivity and specificity of the FGR prognosis were 90.1 and 82.18 % respectively, the method effectiveness was 83.97 %.Conclusion. The method developed for predicting FGR can be used in clinical practice to form risk groups for FGR development and choose tactics for pregnancy management.
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