Evidence map›Paper›PMID 41107515›Full record

ArticleArchives of gynecology and obstetrics2025

Predictive model for preterm premature rupture of membranes following fetal endoscopy laser coagulation in twin-to-twin transfusion syndrome surgery.

Xi Ye, Yuling Wu, Tian Le, Zhiqing Song, Yanjie Cao, Yanyue Zhang, Xuanxuan Hong, Le Yu, Liehong Wang

Abstract read
In one paragraph

Article in Archives of gynecology and obstetrics, 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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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Xi YeQinghai University Affiliated Clinical Medical College, Xining City, Qinghai Province, People's Republic of China.
Yuling WuObstetrics and Gynecology Department, Qinghai Red Cross Hospital, Xining City, Qinghai Province, People's Republic of China.
Tian LeObstetrics and Gynecology Department, Anhui Province Maternal and Child Health Hospital, Hefei City, Anhui Province, People's Republic of China.
Zhiqing SongObstetrics and Gynecology Department, The Sixth People's Hospital Affiliated With Shanghai Jiao Tong University, Shanghai City, People's Republic of China.
Yanjie CaoObstetrics and Gynecology Department, Shanghai Changning District Maternity and Child Health Hospital Associated With East China Normal University, Shanghai City, People's Republic of China.
Yanyue ZhangObstetrics and Gynecology Department, Peking University Third Hospital, Beijing City, People's Republic of China.
Xuanxuan HongQinghai University Affiliated Clinical Medical College, Xining City, Qinghai Province, People's Republic of China.
Le YuQinghai University Affiliated Clinical Medical College, Xining City, Qinghai Province, People's Republic of China.
Liehong Wang, Xining City, People's Republic of China. a121009@correo.umm.edu.mx.

Funding

clinical medical research center for obstetrics and gynecology diseases in Qinghai Province 2024-SF-L03
6 · The paper itself

Abstract

objectiveTo develop a risk prediction model for preterm premature rupture of membranes (PPROM) after fetal endoscopy laser coagulation (FLC) for Twin-to-Twin Transfusion Syndrome (TTTS), identifying related influencing factors.

methodsA retrospective analysis was conducted on 414 parturients from six Chinese hospitals treated with FLC for TTTS between January 2016 and January 2025. Patients were divided into non-occurrence (n = 263) and occurrence groups (n = 151) based on PPROM during pregnancy. Logistic regression identified predictors, establishing the risk prediction model.

resultsUnivariate and multivariate logistic analyses revealed postoperative amniotic fluid leakage, operation time, and intraoperative amniotic fluid reduction rate as risk factors, while preoperative cervical canal length and Trocar insertion distance from the internal cervical OS were associated with reduced risk (all P < 0.05). ROC curve analysis showed an area under the curve of 0.802 (95% CI: 0.700-0.904), indicating good predictive efficacy. The goodness-of-fit test (P = 0.165 > 0.05) confirmed model fit, and calibration curves demonstrated acceptable accuracy. Clinical decision curves indicated net benefit.

conclusionThis model, incorporating postoperative amniotic fluid leakage, operation time, intraoperative amniotic fluid reduction rate, preoperative cervical canal length, and Trocar insertion distance, effectively predicts PPROM risk after FLC for TTTS. It can assess risks clinically and guide interventions to prolong pregnancy and improve outcomes.

Indexed as

Fetofetal TransfusionFetoscopyLaser CoagulationPostoperative ComplicationsPremature Rupture of Fetal MembranesAdultChinaFemaleHumansLogistic ModelsPregnancyRetrospective StudiesRisk AssessmentRisk FactorsROC CurveFetal endoscopy laser coagulationPrediction modelPreterm premature rupture of membranesRegression analysisTwin-to-twin transfusion syndrome

Identifiers

PMID41107515
PMCPMC12705759

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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.