Twin pregnancy management requires evidence-based approaches to optimize outcomes for both mothers and babies. Prof. Basky Thilaganathan presents key strategies that challenge conventional practices while improving clinical decision-making.
The presentation addresses fundamental twin pregnancy care decisions, starting with dating methodology. Rather than using the larger twin for gestational age calculation, research shows dating by average measurements reduces maternal anxiety without compromising fetal growth restriction detection rates. Similarly, consistent left-right twin labeling proves more reliable than cervical proximity methods.
Growth monitoring represents a critical aspect of multiple pregnancy care. Extensive research across 2,000 twin pregnancies demonstrates that estimated fetal weight discordance outperforms both singleton and twin growth charts in predicting adverse outcomes. This approach eliminates the need for specific chart selection while providing superior prognostic information.
Birth timing decisions traditionally rely on arbitrary percentage thresholds, but advanced algorithms combining weight discordance with umbilical artery parameters achieve 90% accuracy in predicting twin complications. This methodology reduces unnecessary preterm birth interventions by two to three-fold while maintaining sensitivity for genuine high-risk cases.
The session includes a live pregnancy ultrasound demonstration using Samsung’s Z20 system, showcasing automated imaging features that streamline routine examinations. Live ViewAssist automatically captures standard planes and measurements, while EzCheck ensures complete examinations through systematic checklists.
These evidence-based strategies represent a shift toward individualized twin pregnancy management that reduces intervention rates while improving outcome prediction accuracy. The integration of validated algorithms with advanced ultrasound technology enables more precise monitoring and delivery timing decisions.
