Ultrasonographic assessment of the uterocervical angle in the second trimester of pregnancy as a predictor of spontaneous preterm birth

被引:0
作者
Nicolau, E. G. [1 ]
Reis, L. O. [1 ,2 ]
机构
[1] Pontificia Univ Catolica Campinas, Postgrad Program Hlth Sci, PUC Campinas, Campinas, SP, Brazil
[2] Univ Estadual Campinas, UroScience, Unicamp, Campinas, SP, Brazil
关键词
CERVICAL LENGTH; SINGLETON; HISTORY; WOMEN;
D O I
10.1016/j.crad.2025.106853
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
AIM: To evaluate the uterocervical angle in the second trimester in singleton pregnancies as a predictor of spontaneous preterm labour. MATERIAL AND METHODS: An observational cohort study was carried out from March 2022 to May 2023, including consecutively selected patients with singleton pregnancies who underwent routine examinations between 18.0 and 23.6 weeks to analyse the risk of prematurity. The uterocervical angle (UCA) measurement was added to the transvaginal ultrasonographic analysis of the cervix. Birth-related outcomes were prospectively collected. RESULTS: patients were evaluated. The occurrence of spontaneous preterm birth (sPTB) before 37 weeks was 12%, with 50 patients. An association was observed between a more obtuse uterocervical angle and the occurrence of birth before 37 weeks, with the area under the curve of 0.636 (p=0.0 03; 95% CI: 0.546e0.726). The cutoff point of 77.2 degrees demonstrated a sensitivity of 80% and specificity of 29.4% (p=0.0 03), a positive predictive value of 13.6%, and a negative predictive value of 91.3%, with a positive likelihood ratio of 1.13 and negative 0.88. CONCLUSION: The measurement of UCA in the second trimester of pregnancy is associated with the occurrence of sPTB. The result corroborates recent literature conclusions that UCA is a relatively recent predictor of sPTB. New evidence in different populations may contribute to its possible incorporation into prematurity risk assessment. (c) 2025 The Royal College of Radiologists. Published by Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
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