Optimization strategies for multidisciplinary team management in abnormal pregnancy cases: a prognosis-risk grading evaluation of 310 fetuses with structural anomalies

Abstract Purpose To describe our experience with multi-disciplinary team (MDT) in managing abnormal pregnancies and to analyze the impact of MDT on pregnancy management and outcomes under a prognosis-risk classification. Methods A retrospective analysis was conducted on 356 abnormal pregnancy cases managed by MDT, with emphasis on operational protocols, management strategies, and neonatal outcomes. In accordance with MDT recommendations, 310 fetuses with structural anomalies were classified into five prognostic categories based on the Kukora et al. classification system, and three risk groups according to disease severity and clinical outcomes. Statistical analyses were performed using chi-square tests (χ²) to evaluate the differences between groups with isolated versus multiple fetal structural abnormalities, as well as among various risk-stratified groups. The predictive accuracy of MDT assessments regarding fetal prognosis was quantitatively evaluated through likelihood ratio (LR) calculations. Results (1) Distribution of MDT Consultation Cases by Reason (N = 356): fetal structural abnormalities: 310 cases (310/356, 87.1%); genetic counseling: 41 cases (41/356, 11.5%); maternal medical conditions: 5 cases (5/356, 1.4%). (2) Kukora et al. prognostic classification: The likelihood ratios for MDT-predicted fetal survival were: LR I = 7.18, LR IIA = 6.60, LR II = 0.27, LR IIB = 0.024, LR III = 0.01. (3) Risk stratification: Live birth rates showed significant differences across risk groups (χ² = 124.23, P P P P = 0.026), NICU admission (χ² = 12.995, P P = 0.031) compared to those with single structural abnormalities. Conclusion In the routine multidisciplinary team consultation practice, we introduced prognostic classification and risk stratification as an exploratory approach. This method provides an additional framework for managing abnormal pregnancy, potentially offering support from prenatal assessment through postpartum care.