Cervical length measurement for the prediction of preterm birth in symptomatic women with a twin pregnancy: a systematic review and meta-analysis
Files
(Published version)
Date
2013
Authors
Liem, S.
van de Mheen, L.
Bekedam, D.
van Pampus, M.
Opmeer, B.
Lim, A.
Mol, B.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Obstetrics and Gynecology International, 2013; 2013:125897-1-125897-7
Statement of Responsibility
S. M. S. Liem, L. van de Mheen, D. J. Bekedam, M. G. van Pampus, B. C. Opmeer, A. C. Lim, and B. W. J. Mol
Conference Name
Abstract
Objective. The aim of this study was to assess whether cervical length measurement (CL) could predict preterm birth (PTB) in symptomatic women with a twin pregnancy. Methods. We searched MEDLINE and EMBASE to identify studies investigating the accuracy of CL measurement in predicting PTB in symptomatic women with a twin pregnancy. We extracted data to construct two-by-two tables and used bivariate meta-analysis to generate point estimates of sensitivity and specificity. Results. Five studies ( ) were included. Variation in definition of PTB and cut-off points for CL was strong. One study investigated delivery within seven days, demonstrating a sensitivity of 1.0 (95% CI: 0.83–1.0) and a specificity of 0.31 (95% CI 0.2–0.43) for a CL cutoff at 25 mm. Three studies reported on predicting PTB < 37 weeks at a CL cutoff of 30 mm, with sROC point estimates of 0.76 (95% CI: 0.66 to 0.84) and 0.37 (95% CI: 0.21 to 0.56) for sensitivity and specificity, respectively. For preterm birth <34 weeks, no pooled estimates could be estimated since only 2 studies with large heterogeneity were identified. Conclusions. There is limited evidence on the accuracy of cervical length measurement testing the prediction of preterm birth in symptomatic women with a twin pregnancy, especially on the most important outcome, that is, delivery within 7 days.
School/Discipline
Dissertation Note
Provenance
Description
Access Status
Rights
© 2013 S. M. S. Liem et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.