Diagnostic accuracy of intracranial translucency in detecting spina bifida: a systematic review and meta-analysis.
Publication/Presentation Date
11-1-2016
Abstract
OBJECTIVE: To evaluate the diagnostic accuracy of intracranial translucency (IT) in the detection of spina bifida (SB) in the first trimester of pregnancy.
METHODS: We included study assessing the accuracy of sonographic measurements of IT in a mid-sagittal view of the fetal face in prediction of SB in the first trimester of pregnancy. The primary outcome was the accuracy of IT in prediction of spina bifida. Summary estimates of sensitivity, specificity, positive and negative likelihood ratios (LR), and diagnostic odds ratio for the overall predictive accuracy of IT were computed.
RESULTS: Nine studies (21 070 fetuses) were included in the analysis. IT was successfully assessed in the majority of fetuses 97.8% (95% CI 97.6-98.0). The diagnostic performance of IT in detecting SB was as follows: sensitivity: 53.5% (95% CI 42.4-64.3), specificity: 99.7% (95% CI 99.6-99.8), positive LR: 62.1 (95% CI 12.2-317), negative LR:0.55 (95% CI 0.45-0.68), and diagnostic odds ratio: 223 (95% CI 25-2039).
CONCLUSIONS: Intracranial translucency had low diagnostic accuracy in prediction of open spina bifida, thus questioning its role as a screening marker for open SB in an unselected population. When looking at the individual study data, it appears that IT assessment for open SB prediction can be affected by a high rate of false positive results potentially leading to unnecessary parental anxiety. © 2016 John Wiley & Sons, Ltd.
Volume
36
Issue
11
First Page
991
Last Page
996
ISSN
1097-0223
Published In/Presented At
Maruotti, G. M., Saccone, G., D'Antonio, F., Berghella, V., Sarno, L., Morlando, M., Giudicepietro, A., & Martinelli, P. (2016). Diagnostic accuracy of intracranial translucency in detecting spina bifida: a systematic review and meta-analysis. Prenatal diagnosis, 36(11), 991–996. https://doi.org/10.1002/pd.4883
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
27500985
Department(s)
Administration and Leadership
Document Type
Article