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<p>Maternal satisfaction with labor epidural analgesia is a clinically relevant patient-centered outcome influenced by analgesic efficacy, the care process, and perinatal complications. This retrospective cohort study analyzed de-identified clinical records and routinely collected postpartum satisfaction assessments from 2221 parturients who received labor epidural analgesia at Fujian Maternity and Child Health Hospital between July 2023 and March 2024. The cohort was randomly divided into training (n = 1555) and internal validation (n = 666) sets. Least absolute shrinkage and selection operator regression, followed by univariate and multivariable logistic regression, was used to construct a nomogram predicting maternal dissatisfaction. Fever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment were independent predictors of dissatisfaction. The model showed good discrimination in the training set (AUC 0.789, 95% CI 0.764–0.814) and validation set (AUC 0.764, 95% CI 0.720–0.809), with satisfactory calibration (Hosmer–Lemeshow χ<sup>2</sup> = 4.58, <i>P</i> = 0.205). This complication-based nomogram demonstrated acceptable internal performance for predicting maternal dissatisfaction with labor epidural analgesia; external validation is needed before wider implementation.</p>

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Development of a predictive model for maternal satisfaction with epidural analgesia based on perinatal complications

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年4月24日

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  • Yihan Zheng,
  • Haiping Zhang,
  • Xizhu Wu,
  • Wenqiang You,
  • Chuantao Lin,
  • Li Zhang

摘要

Maternal satisfaction with labor epidural analgesia is a clinically relevant patient-centered outcome influenced by analgesic efficacy, the care process, and perinatal complications. This retrospective cohort study analyzed de-identified clinical records and routinely collected postpartum satisfaction assessments from 2221 parturients who received labor epidural analgesia at Fujian Maternity and Child Health Hospital between July 2023 and March 2024. The cohort was randomly divided into training (n = 1555) and internal validation (n = 666) sets. Least absolute shrinkage and selection operator regression, followed by univariate and multivariable logistic regression, was used to construct a nomogram predicting maternal dissatisfaction. Fever, nausea and vomiting, puncture pain, lumbar soreness, and lower limb motor impairment were independent predictors of dissatisfaction. The model showed good discrimination in the training set (AUC 0.789, 95% CI 0.764–0.814) and validation set (AUC 0.764, 95% CI 0.720–0.809), with satisfactory calibration (Hosmer–Lemeshow χ2 = 4.58, P = 0.205). This complication-based nomogram demonstrated acceptable internal performance for predicting maternal dissatisfaction with labor epidural analgesia; external validation is needed before wider implementation.