Prediction of postpartum pelvic floor dysfunction with a nomogram model based on big data collected during pregnancy

Background: Pregnancy and childbirth are the main causes of pelvic floor dysfunction (PFD). Although muscle tension is typically measured at 42 days postpartum to assess severity PFD provide timely rehabilitation, it still impossible predict take targeted preventive measures in clinical practice. A prediction model based on big data obtained prenatal check-ups was established this study allow formulation personalized strategies reduce incidence PFD.