Differential predictive utility of preoperative cervical length for preterm birth among various indications for cervical cerclage: a retrospective cohort study

The correlation between preoperative CL and PTB varied depending on the indication(s) for cerclage, and changes in postoperative CL contributed to varying predictive utility.

Authors

Institutions

Publication Details

Journal
The Journal of Maternal-Fetal & Neonatal Medicine
Published
2025-03-20
DOI
https://doi.org/10.1080/14767058.2025.2479751
Primary Topic
Preterm Birth and Chorioamnionitis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Differential predictive utility of preoperative cervical length for preterm birth among various indications for cervical cerclage: a retrospective cohort study

Ling Feng, Nathan Long, Yangxue Fu, Zizhuo Wang et al.
The Journal of Maternal-Fetal & Neonatal Medicine
Preterm Birth and Chorioamnionitis
article

Differential predictive utility of preoperative cervical length for preterm birth among various indications for cervical cerclage: a retrospective cohort study

Ling Feng, Nathan Long, Yangxue Fu, Zizhuo Wang, Teng Ji
article en

Abstract

The correlation between preoperative CL and PTB varied depending on the indication(s) for cerclage, and changes in postoperative CL contributed to varying predictive utility.

The Journal of Maternal-Fetal & Neonatal MedicineVol. 38(1)
Tongji Hospital (CN), Huazhong University of Science and Technology (CN)
Zero hunger
Openalex Percentile: Top 92%
Preterm Birth and Chorioamnionitis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.