WU Xueqin, JIN Rong, CAO Xia. Construction of nomogram model for predicting risk of maternal postpartum chronic low back pain[J]. Journal of Clinical Medicine in Practice, 2023, 27(16): 121-126. DOI: 10.7619/jcmp.20231835
Citation: WU Xueqin, JIN Rong, CAO Xia. Construction of nomogram model for predicting risk of maternal postpartum chronic low back pain[J]. Journal of Clinical Medicine in Practice, 2023, 27(16): 121-126. DOI: 10.7619/jcmp.20231835

Construction of nomogram model for predicting risk of maternal postpartum chronic low back pain

  • Objective To construct a predictive model for postpartum chronic low back pain and verify its prediction effect.
    Methods A total of 450 pregnant women who gave birth were selected as research objects and divided into modeling group (315 cases) and verification group (135 cases) on the basis of a ratio of 7 to 3. According to the occurrence of chronic low back pain after delivery, the modeling group was divided into pain group (n=105) and no pain group (n=210). Single factor and multiple factor Logistic regression analysis were used to screen the risk factors affecting the occurrence of postpartum chronic low back pain, and a nomogram model was drawn to predict the risk of postpartum chronic low back pain.
    Results Among the 15 pregnant women, 105 had chronic low back pain after delivery, and the incidence was 33.33%. Multivariate Logistic regression analysis showed that fetal body weight ≥4 kg (OR=2.585), the number of births ≥3 times (OR=6.144), mode of delivery was caesarean section (OR=2.015), the mother as the main caregiver of the baby (OR=2.390), a history of low back pain during pregnancy (OR=1.942) and had spinal anesthesia (OR=2.223) were independent risk factors for postpartum chronic low back pain (P < 0.05). Based on the above risk factors, a nomogram model was established to predict the risk of postpartum chronic low back pain, and the internal and external verification was carried out. The results showed that the predicted risk of postpartum chronic low back pain was basically consistent with the actual risk; receiver operating characteristic (ROC) curve analysis results showed that the area under the curve of the predictive models in the modeling group and the verification group to predict postpartum chronic low back pain was 0.803 (95%CI, 0.754 to 0.845) and 0.802 (95%CI, 0.725 to 0.866), respectively, indicating that the prediction model had good prediction ability.
    Conclusion Fetal body weight ≥4 kg, the number of births ≥3 times, delivery mode of caesarean section, the mother being the primary caregiver of the baby, history of low back pain during pregnancy and intraspinal anesthesia are risk factors affecting the occurrence of postpartum chronic low back pain. The prediction model based on the above risk factors can accurately evaluate the risk of chronic low back pain in postpartum women, with good differentiation and effectiveness.
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