Cerclage Area: A Postoperative Ultrasonographic Parameter for Predicting Preterm Birth
DOI:
https://doi.org/10.21613/GORM.2025.1631Keywords:
Cerclage area, Cervical insufficiency, Preterm birth , Transvaginal cerclage, UltrasonographyAbstract
OBJECTIVE: This study evaluated the link between postoperative cervical ultrasonographic measurements in women who underwent transvaginal cerclage for cervical insufficiency and preterm birth, focusing on the potential of the new parameter, cerclage area (CA), to predict preterm birth.
STUDY DESIGN: This prospective observational study at a tertiary care center (January 2022–June 2024) included 45 pregnant women who underwent McDonald transvaginal cerclage per ACOG guidelines. Postoperative transvaginal ultrasonography assessed cervical wall thickness, suture depth, cervical length above and below the cerclage, and cerclage area. Participants were followed to delivery; obstetric and neonatal outcomes were recorded.
RESULTS: In the assessments conducted, 48.9% of the cases were preterm, whereas 51.1% were term deliveries. Classical parameters and CA did not differ significantly between the preterm and term groups (p>0.05). However, the CA was significantly correlated with the depths of both the anterior and posterior sutures, and with the thickness of the posterior cervical wall (p<0.05).
CONCLUSION: Although the cerclage area does not significantly predict preterm birth, it may be a useful quantitative tool for assessing cervical structure after cerclage placement. Larger, multicenter studies are needed to clarify the clinical value of this metric.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Neval Cayonu Kahraman, Gulsah Aynaoglu Yildiz, Ozge Yucel Celik, Betul Tokgoz Cakir, Ozgur Arat, Sevki Celen, Ali Turhan Caglar, Yaprak Engin Ustun

This work is licensed under a Creative Commons Attribution 4.0 International License.
All the articles published in GORM are licensed with "Creative Commons Attribution 4.0 License (CC BY 4.0)". This license entitles all parties to copy, share and redistribute all the articles, data sets, figures and supplementary files published in this journal in data mining, search engines, web sites, blogs and other digital platforms under the condition of providing references.



