Development of a Novel Nomogram for Predicting Premature Rupture of Membrane in Pregnant Women With Vulvovaginal Candidiasis.
Development of a Novel Nomogram for Predicting Premature Rupture of Membrane in Pregnant Women With Vulvovaginal Candidiasis.
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开发一种新的列线图来预测患有外阴阴道念珠菌病的孕妇膜过早破裂
DOI:
10.3389/fmed.2021.717978
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发表时间:
2021
影响因子:
3.9
通讯作者:
Luo S
中科院分区:
文献类型:
--
作者:
Yang L;Wang H;Li Y;Zeng C;Lin X;Gao J;Luo S
Objective: The aim of this study was to develop a nomogram to predict the risk of premature rupture of membrane (PROM) in pregnant women with vulvovaginal candidiasis (VVC). Patients and methods: We developed a prediction model based on a training dataset of 417 gravidas with VVC, the data were collected from January 2013 to December 2020. The least absolute shrinkage and selection operator regression model was used to optimize feature selection for the model. Multivariable logistic regression analysis was applied to build a prediction model incorporating the feature selected in the least absolute shrinkage and selection operator regression model. Discrimination, calibration, and clinical usefulness of the prediction model were assessed using the C-index, calibration plot, and decision curve analysis. Internal validation was assessed using bootstrapping validation. Results: Predictors contained in the prediction nomogram included age, regular perinatal visits, history of VVC before pregnancy, symptoms with VVC, cured of VVC during pregnancy, and bacterial vaginitis. The model displayed discrimination with a C-index of 0.684 (95% confidence interval: 0.631–0.737). Decision curve analysis showed that the PROM nomogram was clinically useful when intervention was decided at a PROM possibility threshold of 13%. Conclusion: This novel PROM nomogram incorporating age, regular perinatal visits, history of VVC before pregnancy, symptoms with VVC, cured of VVC during pregnancy, and bacterial vaginitis could be conveniently used to facilitate PROM risk prediction in gravidas.
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影响因子:
4.6
作者:
Getaneh T;Asres A;Hiyaru T;Lake S
通讯作者:
Lake S
影响因子:
2
作者:
Pencina, MJ;D'Agostino, RB
通讯作者:
D'Agostino, RB
DOI:
10.1177/0954411912468557
发表时间:
2013-01-01
影响因子:
1.8
作者:
Micili, Serap C.;Valter, Markus;Artmann, Aysegul T.
通讯作者:
Artmann, Aysegul T.
影响因子:
3.1
作者:
Assefa NE;Berhe H;Girma F;Berhe K;Berhe YZ;Gebreheat G;Werid WM;Berhe A;Rufae HB;Welu G
通讯作者:
Welu G
影响因子:
1.6
作者:
Liang, Haifeng;Xie, Zhiqiang;Zhao, Guanghui
通讯作者:
Zhao, Guanghui