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ENGLISH ABSTRACT
JOURNAL ARTICLE
[Establishment of a prognostic model for preterm delivery in women after cervical conization].
Zhejiang da Xue Xue Bao. Yi Xue Ban = Journal of Zhejiang University. Medical Sciences 2018 Februrary 26
OBJECTIVE: To establish a prognostic model for preterm birth in women after cervical conization, and to evaluate its effectiveness.
METHODS: Seventy three women after cervical conization in Women's Hospital of Zhejiang University were included for this retrospective study. The influencing factors of preterm delivery were analyzed by Logistic regression analysis and a prognostic model was created. Receiver operating characteristic (ROC) curve was used for evaluation of the predictive ability of the model. Forty five women who underwent cervical conization were included for testing the validity of the model.
RESULTS: For women after cervical conization, mother's age ( OR =1.20, 95% CI :1.01-1.43, P <0.05) and cervical length during middle pregnancy ( OR =0.06, 95% CI :0.01-0.21, P <0.01) were independent predictors for preterm birth. The regression model was Logit ( P )=1.408-2.903×cervical length+0.186×age. The areas under the ROC curve (AUC) of the training dataset was 0.93 (95% CI :0.87-0.99). The sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV) and accuracy with the cutoff value of -1.512 were 91.7%, 81.5%, 0.732, 68.8%, 95.7% and 84.5% respectively. The AUC of the testing dataset was 0.94 (95% CI :0.86-1.00). The sensitivity, specificity, Youden index, PPV, NPV and accuracy with the cutoff value of -0.099 were 92.9%, 90.3%, 0.832, 81.3%, 96.5% and 91.1%, respectively.
CONCLUSIONS: The model based on the age and cervical length during middle pregnancy can effectively predict preterm delivery in pregnant women after cervical conization.
METHODS: Seventy three women after cervical conization in Women's Hospital of Zhejiang University were included for this retrospective study. The influencing factors of preterm delivery were analyzed by Logistic regression analysis and a prognostic model was created. Receiver operating characteristic (ROC) curve was used for evaluation of the predictive ability of the model. Forty five women who underwent cervical conization were included for testing the validity of the model.
RESULTS: For women after cervical conization, mother's age ( OR =1.20, 95% CI :1.01-1.43, P <0.05) and cervical length during middle pregnancy ( OR =0.06, 95% CI :0.01-0.21, P <0.01) were independent predictors for preterm birth. The regression model was Logit ( P )=1.408-2.903×cervical length+0.186×age. The areas under the ROC curve (AUC) of the training dataset was 0.93 (95% CI :0.87-0.99). The sensitivity, specificity, Youden index, positive predictive value (PPV), negative predictive value (NPV) and accuracy with the cutoff value of -1.512 were 91.7%, 81.5%, 0.732, 68.8%, 95.7% and 84.5% respectively. The AUC of the testing dataset was 0.94 (95% CI :0.86-1.00). The sensitivity, specificity, Youden index, PPV, NPV and accuracy with the cutoff value of -0.099 were 92.9%, 90.3%, 0.832, 81.3%, 96.5% and 91.1%, respectively.
CONCLUSIONS: The model based on the age and cervical length during middle pregnancy can effectively predict preterm delivery in pregnant women after cervical conization.
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