Construction of an Evaluation Tool for Episiotomy and an Analysis of Its Clinical Effects

Abstract

Background: Due to differences in the perineal and fetal conditions of pregnant women, there is no international standard or guideline on the reasonable use of episiotomy that aims to minimize its use. Objectives: This study aimed to investigate the factors affecting decision-making regarding episiotomy and to establish a logistic regression prediction model. Methods: A total of 224 women who underwent vaginal delivery at the Department of Gynecology and Obstetrics of the First Affiliated Hospital of Nanchang University from May to October of 2020 were selected as subjects for this study. Basing on the and analyzing the correlation between the clinical features and episiotomy with univariate analysis, eleven influencing factors related to episiotomy were identified in the literature;the midwives participating in this study received uniform training and collected data. The risk score prediction model was established using logistic regression analysis, and the predictive effect of the model was tested by plotting the receiver operating characteristic (ROC) curve. Results: The area under the ROC curve (AUC) of the model was 0.939;When the optimal cut-off value was 0.719, the sensitivity was 0.773 and the specificity was 0.946. The parameter with the lowest regression coefficient (perineal inflammation) was used as the reference, and the other regression coefficients were divided by this coefficient to obtain the final risk score model. The individual final risk score model = 1 × perineal inflammation + 10 × perineal edema + 17 × EFW (estimated fetal weight) + 8 × fetal biparietal diameter + 21 × maternal willingness + 12 × perineal length + 33 × perineal elasticity + 5 × perineal color + 11 × perineal injury + 27 × maternal compliance + 11 × amniotic fluid properties. When an individual’s final risk score was <232.5, natural delivery without episiotomy was relatively safe and effective. External 281 subjects participated in restrictive episiotomy to verify the the accuracy of the constructed the risk score prediction model. The accuracy of the constructed the risk prediction model in the first stage and the second stage of research was 80.80% and 82.56% respectively. Conclusions: The application of this model in the second stage of labor can provide an objective reference for clinical midwives to use for episiotomy decision-making.