Background: The clinical manifestations of myofascial pelvic pain (MFPP) are mainly acute or chronic muscle pain at one or more trigger points in the pelvic cavity or pelvic floor.
Objective: This study aims to explore the predictive value of pelvic floor myoelectric parameters with respect to MFPP and the effect of its clinical treatment.
Methods: Two hundred and one women followed up in the Wenzhou People's Hospital 6-12 weeks postpartum between July 2020 and July 2021. They were divided into an MFPP group (n= 90) and a non-MFPP group (n= 102), but 9 MFPP patients without a pelvic floor electromyography evaluation were not included. The general demographic data and pelvic floor electromyography evaluation parameters of the two groups were compared; the related factors of postpartum women suffering from MFPP were analyzed, and a nomogram model of the postpartum risk of suffering from MFPP was established. The 99 patients with postpartum MFPP were divided into a treatment group (n= 10) and a control group (n= 89). The difference in visual analog scale scores between the two groups initially and after three months of treatment was compared to evaluate the effective remission rate of postpartum MFPP after treatment.
Results: A significant difference was observed in the relaxation time at the rapid contraction stage (z= 4.369, p< 0.05) and the tension contraction stage (z= 135.645, p< 0.01) between the MFPP group and the non-MFPP group. The nomogram model for predicting postpartum MFPP was established with nine variables as potential predictors. The calibration chart and C index of 0.68 (95% CI: 0.65-0.71) proved that the model had a certain degree of discrimination. The clinical decision-making curve showed that the model could increase the net benefit rate of patients. The pain relief rate in the treatment group was significantly higher than that in the control group (p< 0.01).
Conclusion: There is a significant correlation between postpartum MFPP and relaxation time at rapid contraction stage and tension contraction stage. The risk prediction nomogram model of postpartum MFPP established with nine potential predictors has a certain prediction capability, and clinical treatment can effectively relieve MFPP in postpartum patients.
Keywords: Postpartum; artificial intelligence; machine learning; manipulation therapy; myofascial pelvic pain; nomogram model; pelvic floor muscle; pelvic floor myoelectric parameter; trigger point.