Construction and validation of a nomogram prediction model for the risk of pregnant women's fear of childbirth
Objective To construct and verify the nomogram prediction model of pregnant women's fear of childbirth.Methods A convenient sampling method was used to select 675 pregnant women in tertiary hospital in Tangshan City,Hebei Province from July to September 2022 as the modeling group,and 290 pregnant women in secondary hospital in Tangshan City from October to December 2022 as the verification group.The risk factors were determined by logistic regression analysis,and the nomogram was drawn by R 4.1.2 software.Results Six predictors were entered into the model:prenatal education,education level,depression,pregnancy complications,anxiety and preference for delivery mode.The areas under the ROC curves of the modeling group and the verification group were 0.834 and 0.806,respectively.The optimal critical values were 0.113 and 0.200,respectively,with sensitivities of 67.2％and 77.1％,the specificities were 87.3％ and 74.0％,and the Jordan indices were 0.545 and 0.511,respectively.The calibration charts of the modeling group and the verification group showed that the coincidence degree between the actual curve and the ideal curve was good.The results of Hosmer-Lemeshow goodness of fit test were x2=6.541(P=0.685)and x2=5.797(P=0.760),and Brier scores were 0.096 and 0.117,respectively.DCA in modeling group and verification group showed that when the threshold probability of fear of childbirth were 0.00 to 0.70 and 0.00 to 0.70,it had clinical practical value.Conclusion The nomogram model has good discrimination,calibration and clinical applicability,which can effectively predict the risk of pregnant women's fear of childbirth and provide references for early clinical identification of high-risk pregnant women and targeted intervention.
Fear of childbirthPregnant womenRisk factorNomogramPrediction model
万方数据
维普
