EP17.29: Cervical elastography: finding a novel predictor for improving the prediction of preterm birth in uncomplicated twin pregnancies

This study set out to investigate a novel ultrasound parameter using cervical elastosonography for improving the prediction of spontaneous preterm birth (sPTB) in twin pregnancies. The study was comprised of 106 twin pregnancies from Beijing Obstetrics and Gynecology Hospital in China. Two groups according to GA at delivery (delivery<35 weeks and delivery≥35 weeks). Five elastographic parameters: Elasticity Contrast Index (ECI), Cervical Hardness Ratio (CHR), Closed Internal cervical ostium Strain rate (CIS), External cervical ostium Strain rate (ES), CIS/ES ratio and Cervical Length (CL). All of the clinical and ultrasonic indicators with P<0.1 were considered as candidates via univariate logistic regression. Based on the extracted unified combination of clinical indicators, the combinations of permutation with the ultrasound candidates were performed step by step in multivariable logistic regression. The best ultrasound indicator with the lowest AIC and the highest AUC was chosen for establishing the prediction score. Over 30% of those who delivered before 35 weeks gestation. Seven major clinical variables were identified as a unified clinical indicator. CISmin as the best ultrasound elastography predictor indicated the lowest AIC and the highest AUC and outperformed alternative indicators significantly in the prediction of delivery before 35 weeks of gestation. CLmin which was commonly used in clinical practice ranked far from all of the cervical elastography parameters and presented the highest AIC and the lowest AUC. A preliminary scoring rule was established and the ability to predict the risk of sPTB in twin pregnancies was improved (Accuracy: 0.896 vs 0.877; AIC: 81.494 vs 91.698; AUC: 0.923 vs 0.906). The cervical elastosonography predictor such as CISmin might be a more useful indicator applied for enhancing the ability to predict twin pregnancies preterm birth than CL. Furthermore, there would be more benefits for advancing clinical decision-making in clinical practice in the near future.