Evidence map›Paper›PMID 41254542›Full record

ArticleBMC pregnancy and childbirth2025

Prediction of adverse maternal outcomes associated with preeclampsia in twin pregnancies.

Shuisen Zheng, Wei Zheng, Yuting Gao, Xiaoling Chen, Na Lin, Qing Han

Abstract read
In one paragraph

Article in BMC pregnancy and childbirth, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Shuisen Zheng *Department of Obstetrics, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Wei Zheng *Department of Gastrointestinal Surgery, The First Affiliated Hospital of Fujian Medical University, Fuzhou, China.
Yuting GaoDepartment of Obstetrics, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Xiaoling ChenDepartment of Obstetrics, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China.
Na LinMedical Genetic Diagnosis and Therapy Center, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China. linna1088@fjmu.edu.cn.
Qing HanDepartment of Obstetrics, Fujian Maternity and Child Health Hospital College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, China. hanqing@fjmu.edu.cn.

Funding

Fujian Provincial Natural Science Foundation of China 2023J011213Joint Funds for the Innovation of Science and Technology, Fujian Province 2021Y9178
6 · The paper itself

Abstract

backgroundWe aimed to investigate risk factors of adverse maternal outcomes associated with preeclampsia (PE) in twin pregnancies and develop a simplified clinical prediction model.

methodWe recruited pregnant women with preeclampsia who were hospitalized in Fujian Maternal and Child Health Hospital from January 2014 to December 2021, including singleton and twin pregnancies. We further divided twin pregnancies into adverse outcome group and non-adverse outcome group. We performed univariate analysis, the least absolute shrinkage and selection operator (LASSO) and multivariate logistic regression analysis to identify factors influencing adverse maternal outcomes associated with preeclampsia in twin pregnancies, then established a predictive model. The predictive performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, calibration plots and decision curve analysis (DCA).

resultsTwin pregnancies with PE showed a higher prevalence of adverse outcomes compared with singleton pregnancies (17.4% VS 13.6%). Gestational age at admission less than 32 + 0 week gestational age, multipara, peak systolic blood pressure, creatinine, neutrophil/high-density lipoprotein ratio (NHR)and decreased platelet count were independent risk factors for the development of adverse outcomes of PE in twin pregnancies. The area under the ROC curve of the prediction model was 0.798 and the calibration curve indicated that adverse maternal outcomes rate predicted by the model was consistent with the actual outcome.

conclusionsThe predictive model can identify women at increased risk of adverse maternal outcomes associated with preeclampsia in twin pregnancies, which can provide suggestion for preeclampsia in twin pregnancies and intervening timely.

Indexed as

Pre-EclampsiaPregnancy OutcomePregnancy, TwinAdultChinaFemaleGestational AgeHumansLogistic ModelsPrediction AlgorithmsPregnancyRisk AssessmentRisk FactorsROC CurveAdverse maternal outcomePreeclampsiaRisk factors; predictionTwins

Identifiers

PMID41254542
PMCPMC12625484

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.