Antepartum Risk Stratification and Its Influence on Labour Interventions and Outcomes: A Retrospective Cohort Study.

Abstract

Background: Early identification of risk factors in pregnancy is essential to improving maternal and neonatal outcomes. High-risk pregnancies, characterized by maternal or fetal factors that increase the likelihood of complications, contribute significantly to maternal mortality, particularly in low- and middle-income countries (LMICs). This study examines the influence of antepartum risk stratification on labour interventions and outcomes among women in Lagos, Nigeria.

Methods: This retrospective cohort study included 507 women admitted to the labour ward at Lagos State University Teaching Hospital (LASUTH) from May 2019 to April 2022. Participants were classified as low-risk or high-risk based on antenatal clinical profiles, including sociodemographic, obstetric, and medical factors. Outcomes were assessed based on labour interventions (induction, augmentation, mode of delivery) and neonatal outcomes (APGAR scores, NICU admissions). Data was analyzed using descriptive statistics, chi-square tests, and logistic regression to identify factors associated with high-risk classification and outcomes.

Results: High-risk pregnancies constituted 17.6% of the cohort and were associated with younger maternal age, nulliparity, and higher antenatal care utilization. High-risk women had significantly higher rates of induction (14.6% vs. 1.2%), oxytocin augmentation (27% vs. 5.3%), and emergency cesarean delivery (39.3% vs. 23.4%). Neonates of high-risk pregnancies had lower APGAR scores and higher NICU admissions (25.8% vs. 3.8%, p < 0.001). Increased ANC attendance was significantly associated with high-risk classification.

Conclusion: High-risk pregnancies are associated with increased maternal and neonatal complications, highlighting the importance of early risk stratification and adherence to WHO guidelines for adequate antenatal care. Strengthening ANC services and timely interventions can improve outcomes in LMICs.