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| 硬膜外分娩镇痛产后尿潴留风险的列线图预测模型 |
| Nomogram prediction model for the risk of postpartum urinary retention following epidural labor analgesia |
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| DOI：10.12089/jca.2025.11.008 |
| 中文关键词: 硬膜外镇痛 阴道分娩 产后尿潴留 预测模型 |
| 英文关键词: Epidural analgesia Vaginal delivery Postpartum urinary retention Prediction model |
| 基金项目:福建中医药大学校管课题临床专项资助（XB2023079） |
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| 中文摘要: |
目的：筛选硬膜外分娩镇痛产后尿潴留（PUR）的影响因素，构建PUR风险列线图预测模型并验证。
方法：回顾性收集2022年1月至2024年1月接受硬膜外分娩镇痛的624例产妇的病历资料，包括一般资料、妊娠情况、产时情况、分娩期间用药情况及镇痛情况。通过多因素Logistic回归初步筛选PUR的影响因素,基于筛选结果构建列线图预测模型，绘制受试者工作特征（ROC）曲线评估模型预测效能，采用校准曲线验证预测一致性，采用决策曲线分析量化临床净获益。采用Bootstrap自抽样1 000次进行内部验证。
结果：有42例（6.73%）产妇出现PUR。多因素Logistic回归分析显示，镇痛持续时间延长（OR=1.182， 95%CI 1.079～1.296）、会阴撕裂（OR=20.599， 95%CI 3.123～135.874）、会阴切开（OR=19.283， 95% CI 2.895～128.426）和产时间歇导尿（OR=0.095， 95%CI 0.042～0.214）是PUR的影响因素。基于以上因素构建列线图预测模型，该模型ROC曲线下面积（AUC）为0.912（95%CI 0.878～0.945），敏感性为0.833，特异性为0.861。校准曲线显示，预测概率与实际概率较为一致，效果良好。决策曲线显示，在相应风险阈值范围内具有正向临床净获益。内部验证的AUC为0.912 （95%CI 0.873～0.943），提示模型的预测能力较稳定。
结论：镇痛持续时间延长、会阴撕裂及会阴切开是硬膜外镇痛下阴道分娩产妇发生PUR的独立危险因素，而产时间歇导尿可显著降低风险。基于上述因素构建的列线图模型可预测PUR的发生，可为临床识别高危产妇及制定个体化管理策略提供参考。 |
| 英文摘要: |
Objective: To screen the factors affecting postpartum urinary retention (PUR) during vaginal delivery under epidural analgesia (EA), and construct and verify the risk prediction nomogram model.
Methods: A total of 624 parturients who underwent EA vaginal delivery from January 2022 to January 2024 were retrospectively collected. Population characteristics, pregnancy data, intrapartum variables, medication during delivery and analgesia were included. Independent predictors were screened by multivariate logistic regression, a nomogram model was constructed. The receiver operating characteristic (ROC) curve was plotted to evaluate the predictive performance of the model, and a calibration curve was used to verify the predictive consistency, and decision curve analysis (DCA) was conducted to quantify the clinical net benefit. Bootstrap self-sampled 1 000 times for internal verification.
Results: PUR was observed in 42 patients (6.73%). The multivariate logistic regression analysis showed that prolonged duration of analgesia (OR = 1.182, 95% CI 1.079-1.296), perineal laceration (OR = 20.599, 95% CI 3.123-135.874), episiotomy (OR = 19.283, 95% CI 2.895-128.426), and intermittent catheterization during labor (OR = 0.095, 95% CI 0.042-0.214) are influencing factors of PUR. Construct a nomogram prediction model based on the above factors. The model demonstrated excellent discriminative ability with an area under the curve (AUC) of 0.912 (95% CI 0.878-0.945), with a sensitivity of 0.833, specificity of 0.861. Calibration analysis revealed good agreement between predicted and observed probabilities. Decision curve analysis showed positive net clinical benefits within relevant risk threshold ranges. Internal validation yielded an AUC of 0.912 (95% CI 0.873-0.943), indicating stable predictive performance of the model.
Conclusion: Prolonged duration of analgesia, perineal trauma, and episiotomy independently increase PUR risk, whereas intermittent catheterization confers protection. The high-performance nomogram provides a quantitative tool for identifying high-risk parturients and formulating individualized management strategies. |
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