CHEN Cong,NI Leyi,NI Feifei, et al. Establishment of risk prediction nomogram model for postpartum myofascial pelvic pain[J]. JOURNAL OF WEZHOU MEDICAL UNIVERSITY, 2022, 52(1): 35-40,46.
Abstract：Objective: To establish a risk prediction nomogram model for predicting the occurrence of postpartum pelvic myofascial pain. Methods: From July 2020 to September 2021, women who came to our hospital for follow-up visits 6-12 weeks after delivery, was assigned as MFPP group and non-MFPP group according to the diagnostic criteria of pelvic myofascial pain. General demographic data variables and pelvic floor EMG assessment data variables were screened by Lasso regression, and single-factor analysis was made for pelvic floor EMG assessment data. The screening variables were combined with the pelvic floor EMG assessment data commonly used in clinical diagnosis to construct the nomogram of the postpartum pelvic myofascial pain risk prediction model, and the calibration diagram was draw and adopt the consistency index (C-index) adopted to evaluate the stability and predictive power of the nomogram model. Then the clinical decision curve was drawn to analyze the quantification of the net benefit rate under different threshold probabilities in the postpartum MFPP cohort to determine the clinical applicability of the model. Results: A total of 300 postpartum followup women were collected (150 in the MFPP group and 150 in the non-MFPP group). Pregnancy, parity, delivery method, and newborn weight were related to the occurrence of postpartum MFPP. Postpartum MFPP risk prediction model nomogram C index was 0.706, with certain predictive ability. When the patient received a diagnosis threshold probability of 23%-72%, the net benefit rate of the model could be increased. Conclusion: The nomogram of the postpartum MFPP risk prediction model can effectively predict the postpartum MFPP and provide guidance for clinical evaluation.
