Open Access
Open access
volume 25 issue 1 publication number 365

Establishing a predictive model for ectopic pregnancy risk following assisted reproductive technology

Publication typeJournal Article
Publication date2025-03-28
scimago Q1
wos Q1
SJR1.069
CiteScore5.1
Impact factor2.7
ISSN14712393
Abstract
The risk of ectopic pregnancy (EP) is known to increase with assisted reproductive technology (ART), but the specific risk factors are unclear. We screened 6872 cycles for clinical data that met our study’s inclusion criteria and conducted univariate and multivariate analyses to identify factors associated with EP and develop a nomogram prediction model for its incidence. The multivariate analysis demonstrated that women with polycystic ovary syndrome (PCOS) have an over two-fold increased risk of EP (aOR = 2.07, 95% CI: 1.27–3.36, P = 0.004). Frozen embryo transfer can significantly reduce the risk of EP compared to fresh embryo transfer (aOR = 2.17, 95% CI: 1.62–2.91, P < 0.001). Male infertility factor was associated with a 1.4-fold increased risk of EP (aOR = 1.39, 95% CI: 1.05–1.85,P = 0.021). Each 1 mm increase in endometrial thickness (EMT) is associated with a 15% reduction in the odds of EP(aOR = 0.86, 95% CI: 0.77–0.93, P < 0.001). Women with EP history was associated with 1.4-fold increased risk of EP (aOR = 1.41, 95% CI: 1.01–1.97, P = 0.046). A nomographic prediction model was established based on the results above. The area under the curve (AUC) for the model predicting EP following ART is 0.624, whereas in the external validation set, it is 0.618. Our findings indicate that PCOS increases the risk of EP after ART, and fresh embryo transfer is also linked to higher EP rates. We developed a nomogram to predict and mitigate the incidence of EP. Retrospectively registered.
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Li J. et al. Establishing a predictive model for ectopic pregnancy risk following assisted reproductive technology // BMC Pregnancy and Childbirth. 2025. Vol. 25. No. 1. 365
GOST all authors (up to 50) Copy
Li J., Dai T., Liu Y., Li Y., Chen T., Chen X., Li J. Establishing a predictive model for ectopic pregnancy risk following assisted reproductive technology // BMC Pregnancy and Childbirth. 2025. Vol. 25. No. 1. 365
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TY - JOUR
DO - 10.1186/s12884-025-07455-w
UR - https://bmcpregnancychildbirth.biomedcentral.com/articles/10.1186/s12884-025-07455-w
TI - Establishing a predictive model for ectopic pregnancy risk following assisted reproductive technology
T2 - BMC Pregnancy and Childbirth
AU - Li, Jie
AU - Dai, Tiantian
AU - Liu, Yang
AU - Li, Yuanyi
AU - Chen, Tailin
AU - Chen, Xiaojun
AU - Li, Jin
PY - 2025
DA - 2025/03/28
PB - Springer Nature
IS - 1
VL - 25
SN - 1471-2393
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2025_Li,
author = {Jie Li and Tiantian Dai and Yang Liu and Yuanyi Li and Tailin Chen and Xiaojun Chen and Jin Li},
title = {Establishing a predictive model for ectopic pregnancy risk following assisted reproductive technology},
journal = {BMC Pregnancy and Childbirth},
year = {2025},
volume = {25},
publisher = {Springer Nature},
month = {mar},
url = {https://bmcpregnancychildbirth.biomedcentral.com/articles/10.1186/s12884-025-07455-w},
number = {1},
pages = {365},
doi = {10.1186/s12884-025-07455-w}
}