The dataset of 448 multiparous women cases

A retrospective case-control study was used in this research, the hospitalization information was abstracted from the electrical medical records of multiparous women who underwent vaginal delivery at the obstetric department from 1st January 2022 to 31th December 2023. The medical records of multiparous women who labored in hospital were collected by using the system of clinical information, the total number of data entried 23, the meaning of row headers contained: (1) Demographic features included the age(years old), height(cm), antepartum weight(kg), BMI of pre-pregnancy(kg/cm2), education of maternal. (2) Obstetrics-related features included the frequency of pregnancy, labor and abortion, degree of gestational weight gain, gestational age(weeks), interpregnancy interval(years), hypertensive disorders of pregnancy and premature rupture of membranes. (3) Use of drugs: Induction of labor, including spontaneous, oxytocin and other pharmacological induction which included transfer cervical balloon, dinoprostone, misoprostol and combined labor induction, the utilization of antispasmodic drugs after regular contractions. (4) Neonatal characteristics included the weight of newborn(kg). (5) Medical history characteristics included history of the precipitate delivery, the prematurity, the macrosomia, the abnormal second stage and the mode of previous labor and the variable of outcome(precipitate delivery). The meaning of column headers was every single patient.SPSS 26.0 was employed for statistical analysis. Quantitative data that conformed to or approximated a normal distribution were described as mean ± standard deviation. The independent samples t-test was used for comparison between two groups. If else, it was described as M (P25, P75) and the Mann-Whitney U test was used for comparison between two groups. Qualitative data were described as cases (%) and group comparison was performed using the c2 or Fisher test. The Boruta package of R4.3.3 was employed to identify pertinent variables and these were integrated with variables exhibiting a p value of less than 0.05 from univariate analysis to serve as the independent variables in the multicollinearity analysis. The VIF was utilized to access the potential multicollinearity, with a VIF exceeding 5 indicating the presence of covariance among the variables. Subsequently, logistic regression analysis was conducted to identify the influencing factors, with a p< 0.05 considered statistically significant.In this dataset, the NCA package of R4.3.3 was initially to employed to analyze the necessity of the factors affecting the occurrence of precipitate delivery in multiparous women. Subsequently, fsQCA4.1 was applicated to explore the key conditional configurations of precipitate delivery in multiparous women by using the crisp-set qualitative comparative analysis(csQCA).