Authors
Rong Chen, Ying Shao, Junming Huang, Laifeng Luo, Jincai Zhong, Jianqing Lin, Baohui Hong
Published in
Journal of anesthesia. Oct 20, 2026. Epub Oct 20, 2026.
Abstract
To develop and validate a risk prediction model for postpartum urinary retention (PUR) among parturients receiving epidural analgesia (EA) during vaginal delivery, to support individualized bladder management.
This dual-center retrospective cohort study analyzed electronic medical records from two hospitals (2022-2024). Least absolute shrinkage and selection operator (LASSO) regression was used to select independent predictors from demographic, labor, and analgesia-related variables. A clinical nomogram was developed. The model underwent internal and external validation; performance was assessed using calibration, discrimination (area under the receiver operating characteristic curve [AUC]), and decision curve analysis (DCA).
Among 1019 parturients receiving EA (PUR incidence 16.09%), prolonged analgesia duration and prolonged second-stage labor were independently associated with PUR, whereas higher intermittent catheterization frequency (ICF) was associated with a lower rate of recorded PUR. The model demonstrated excellent discrimination, satisfactory calibration, and clinical net benefit across validation cohorts.
The validated nomogram provides real-time, individualized estimates of PUR risk during late labor. By identifying parturients at elevated risk, it offers an evidence-based basis for risk-adaptive bladder monitoring and individualized care; however, whether such model-guided management ultimately reduces PUR incidence remains to be established in prospective interventional studies.
PMID:
42900381
Bibliographic data and abstract were imported from PubMed on 21 Oct 2026.
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