Prenatal prognostics: Validating high-risk pregnancy predictions for maternal and perinatal outcomes

High-risk pregnancies pose significant challenges to maternal and perinatal health, necessitating effective identification and management strategies. The development of reliable prediction tools is critical for early intervention and improving outcomes in this vulnerable population to identify high-risk pregnancy and assess its maternal and perinatal outcome.

It is a prospective cross-sectional research design. A non-probability convenience sampling was used to collect 300 samples who met the inclusion criteria. The data were collected from antenatal mothers who were visiting selected primary health centers (PHCs) demographic, obstetric data collected, and a scoring system of high-risk pregnancies were used. Data analysis was performed by using one-way ANOVA and logistic regression.

A total of 58% of antenatal mothers were at extremely high risk of pregnancy. By using one-way ANOVA for regression analysis, a statistically significant variation was found between regression and residual (F = 2.137, P = 0.040). By using logistic regression analysis, only educational status (P = 0.007) is statistically associated with high-risk pregnancy. The association of high-risk pregnancy scores was not associated with sociodemographic variables except age and educational status.

This study establishes the significance of prenatal prediction in identifying high-risk pregnancies and offering a valuable tool for maternal and perinatal risk assessment. The findings underscore the potential for prenatal care strategies to mitigate the risk associated with high-risk pregnancies and contribute to enhanced overall prenatal and perinatal outcomes.