Termination of Pregnancy for Fetal Anomalies: A Retrospective Analysis of 112 Cases with Predictors of Late Termination.

Background and Objectives: Termination of pregnancy (TOP) for fetal anomalies is a clinically and ethically complex intervention, and epidemiological data from regional Turkish referral centers are limited. This study aims to characterize the distribution of indications, identify predictors of late termination (gestational age ≥ 20 weeks), and analyze hospital resource utilization in a nine-year consecutive case series. Materials and Methods: A retrospective cohort study was conducted. All 112 cases of TOP for confirmed fetal anomalies or fetomaternal indications were included. Predictors of late termination were identified by binary logistic regression with three a priori selected variables (cardiovascular anomaly, CNS anomaly, maternal age; EPV [events-per-variable ratio] = 13.3). Hospital stay was compared between gestational age groups using the Mann-Whitney U test. Results: The mean gestational age at termination was 18.2 ± 4.0 weeks. Amniotic fluid disorders (predominantly anhidramnios, n = 35, 31.3%) were the single most frequent specific diagnosis. Cardiovascular anomaly was the only variable associated with late termination on logistic regression (OR 15.34, 95% CI 1.81-130.34; p = 0.012); CNS anomaly and maternal age were not significant. Cardiovascular anomalies were terminated at significantly later gestational ages than all other indication categories (pairwise Mann-Whitney U; Bonferroni-corrected p < 0.01 for four of five comparisons). Hospital stay was significantly longer in cases terminated at ≥20 weeks (median 3 vs. 2 days; p = 0.001). Conclusions: Amniotic fluid disorders dominate the indication profile at this center, distinguishing it from chromosomally focused Western series. Cardiovascular anomalies were associated with late termination, a finding consistent with the gestational age constraints of fetal echocardiography. These findings have implications for prenatal screening program design and healthcare resource planning.