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Reproductive Health

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Open Access 01-12-2023 | Premature Birth | Research

Development and validation of a prediction model on spontaneous preterm birth in twin pregnancy: a retrospective cohort study

Authors: Xiaofeng Yang, Qimei Zhong, Li Li, Ya Chen, Chunyan Tang, Ting Liu, Shujuan Luo, Jing Xiong, Lan Wang

Published in: Reproductive Health | Issue 1/2023

Abstract

Background

This study was conducted to develop and validate an individualized prediction model for spontaneous preterm birth (sPTB) in twin pregnancies.

Methods

This a retrospective cohort study included 3845 patients who gave birth at the Chongqing Maternal and Child Health Hospital from January 2017 to December 2022. Both univariable and multivariable logistic regression analyses were performed to find factors associated with sPTB. The associations were estimated using the odds ratio (OR) and the 95% confidence interval (CI). Model performance was estimated using sensitivity, specificity, accuracy, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

Results

A total of 1313 and 564 cases were included in the training and testing sets, respectively. In the training set, univariate and multivariate logistic regression analysis indicated that age ≥ 35 years (OR, 2.28; 95% CI 1.67–3.13), pre-pregnancy underweight (OR, 2.36; 95% CI 1.60–3.47), pre-pregnancy overweight (OR, 1.67; 95% CI 1.09–2.56), and obesity (OR, 10.45; 95% CI, 3.91–27.87), nulliparity (OR, 0.58; 95% CI 0.41–0.82), pre-pregnancy diabetes (OR, 5.81; 95% CI 3.24–10.39), pre-pregnancy hypertension (OR, 2.79; 95% CI 1.44–5.41), and cervical incompetence (OR, 5.12; 95% CI 3.08–8.48) are independent risk factors for sPTB in twin pregnancies. The AUC of the training and validation set was 0.71 (95% CI 0.68–0.74) and 0.68 (95% CI 0.64–0.73), respectively. And then we integrated those risk factors to construct the nomogram.

Conclusions

The nomogram developed for predicting the risk of sPTB in pregnant women with twins demonstrated good performance. The prediction nomogram serves as a practical tool by including all necessary predictors that are readily accessible to practitioners.

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Title: Development and validation of a prediction model on spontaneous preterm birth in twin pregnancy: a retrospective cohort study
Authors: Xiaofeng Yang
Qimei Zhong
Li Li
Ya Chen
Chunyan Tang
Ting Liu
Shujuan Luo
Jing Xiong
Lan Wang
Publication date: 01-12-2023
Publisher: BioMed Central
Keywords: Premature Birth
Underweight
Underweight
Published in: Reproductive Health / Issue 1/2023
Electronic ISSN: 1742-4755
DOI: https://doi.org/10.1186/s12978-023-01728-3

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Development and validation of a prediction model on spontaneous preterm birth in twin pregnancy: a retrospective cohort study

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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