Pathogenic Factors of Bacterial Vaginitis and Construction of Nomogram Prediction Model

Abstract

Background: This study aims to explore the risk factors inducing bacterial vaginosis (BV) and establish a nomogram prediction model. Methods: Single-factor analysis and multivariate logistic regression were used to analyze the risk factors affecting the onset of BV. The selected risk factors were incorporated into the R software to establish a nomogram prediction model. The effectiveness of the proposed model was evaluated. Results: The cleanliness of vaginal secretions above grade III accounted for 90.86% (169/186) of the cases. Multivariate logistic regression analysis showed that the use of nursing pads during non-menstrual periods, history of miscarriage ≥1 time, self-vaginal douche, and frequency of sexual activity ≥5 time per week were identified as risk factors for the incidence of BV (p < 0.05). Using condoms as a method of contraception was identified as a protective factor for the incidence of BV (p < 0.05); A nomogram prediction model was established based on the aforementioned risk factors, and the area under the receiver operating characteristic (ROC) curve was 0.789 (95% confidence interval (CI): 0.751–0.827), indicating that the nomogram had a good degree of discrimination. The slope of the calibration curve was close to 1. Decision curve analysis (DCA) shows that it has good clinical value. Conclusions: The nomogram prediction model established based on BV risk factors has good discrimination and high degree of consistency.