120017
论文已发表
注册即可获取德孚的最新动态
IF 收录期刊
- 3.6 Breast Cancer (Dove Med Press)
- 4.3 Clin Epidemiol
- 2.6 Cancer Manag Res
- 3.2 Infect Drug Resist
- 4.1 Clin Interv Aging
- 6.1 Drug Des Dev Ther
- 4.1 Int J Chronic Obstr
- 8.7 Int J Nanomed
- 2.5 Int J Women's Health
- 3.2 Neuropsych Dis Treat
- 2.4 OncoTargets Ther
- 2.6 Patient Prefer Adher
- 2.6 Ther Clin Risk Manag
- 3.1 J Pain Res
- 3.5 Diabet Metab Synd Ob
- 4.5 Psychol Res Behav Ma
- 3.4 Nat Sci Sleep
- 2.4 Pharmgenomics Pers Med
- 2.6 Risk Manag Healthc Policy
- 4.6 J Inflamm Res
- 2.3 Int J Gen Med
- 3.9 J Hepatocell Carcinoma
- 3.3 J Asthma Allergy
- 2.5 Clin Cosmet Investig Dermatol
- 3.0 J Multidiscip Healthc
已发表论文
硬膜外分娩镇痛产妇头位难产风险预测模型的建立与验证
Authors Han Y, Liu Z, Gan Y, Tan X, Diao Q, Cao Y, Shi Q
Received 13 August 2025
Accepted for publication 3 January 2026
Published 24 January 2026 Volume 2026:18 560398
DOI https://doi.org/10.2147/IJWH.S560398
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Everett Magann
Yu Han,* Zengying Liu,* Yanqiong Gan, Xinlin Tan, Qiuyue Diao, Yuting Cao, Qi Shi
Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Qi Shi, Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, No. 63, Wenhua Road, Shunqing District, Nanchong, Sichuan, 637000, People’s Republic of China, Tel +86-15983789947, Email shiqistone@163.com
Background: While effectively relieving labor pain, epidural analgesia may decrease signs of cephalic dystocia, delaying timely diagnosis and intervention.
Objective: Develop and validate a prediction model for cephalic dystocia risk under epidural analgesia.
Methods: Between January 2021 and October 2024, 855 women who gave birth at the Obstetrics Department of the Affiliated Hospital of North Sichuan Medical College and received epidural analgesia were included in this study. To identify independent risk factors, univariate and multivariate logistic regression analyses were conducted and R software was used to construct a nomogram prediction model. ROC curve analysis, Hosmer-Lemeshow (H-L) tests, calibration plots, and decision curve analysis were used to evaluate the predictive ability of the model. Bootstrap resampling was used for internal validation.
Results: The following factors were found to be independent predictors of cephalic dystocia under epidural analgesia: premature rupture of membranes (OR: 2.73, 95% CI: 1.46– 5.11), prolonged latent phase (OR: 13.82, 95% CI: 7.51– 25.42),fetal abdominal circumference (OR: 5.13, 95% CI: 2.22– 11.81), maternal age (OR:3.87, 95% CI:1.29– 11.59), parity (OR: 16.16, 95% CI: 2.95– 88.55), fetal presentation at the early stage of the active phase (OR: 2.82, 95% CI: 1.63– 4.88), and fetal position at the early stage of the active phase (OR:8.4, 95% CI:4.83– 14.59). The area under the curve (AUC) for this predictive model was 0.910 (95% CI: 0.878– 0.941). The Hosmer-Lemeshow goodness-of-fit test and calibration curve results showed that (P=0.992 > 0.05). Within the clinical decision curve, the net benefit of the nomogram model is higher across the threshold probability range of 0.05 to 0.83.
Conclusion: This risk prediction model can identify high-risk cephalic dystocia post-epidural analgesia during the early active phase of labor, providing an instant assessment tool for timely intervention and better outcomes.
Keywords: cephalic dystocia, epidural labor analgesia, predictive model, nomogram
Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, Nanchong, 637000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Qi Shi, Department of Obstetrics, The Affiliated Hospital of North Sichuan Medical College, No. 63, Wenhua Road, Shunqing District, Nanchong, Sichuan, 637000, People’s Republic of China, Tel +86-15983789947, Email shiqistone@163.com
Background: While effectively relieving labor pain, epidural analgesia may decrease signs of cephalic dystocia, delaying timely diagnosis and intervention.
Objective: Develop and validate a prediction model for cephalic dystocia risk under epidural analgesia.
Methods: Between January 2021 and October 2024, 855 women who gave birth at the Obstetrics Department of the Affiliated Hospital of North Sichuan Medical College and received epidural analgesia were included in this study. To identify independent risk factors, univariate and multivariate logistic regression analyses were conducted and R software was used to construct a nomogram prediction model. ROC curve analysis, Hosmer-Lemeshow (H-L) tests, calibration plots, and decision curve analysis were used to evaluate the predictive ability of the model. Bootstrap resampling was used for internal validation.
Results: The following factors were found to be independent predictors of cephalic dystocia under epidural analgesia: premature rupture of membranes (OR: 2.73, 95% CI: 1.46– 5.11), prolonged latent phase (OR: 13.82, 95% CI: 7.51– 25.42),fetal abdominal circumference (OR: 5.13, 95% CI: 2.22– 11.81), maternal age (OR:3.87, 95% CI:1.29– 11.59), parity (OR: 16.16, 95% CI: 2.95– 88.55), fetal presentation at the early stage of the active phase (OR: 2.82, 95% CI: 1.63– 4.88), and fetal position at the early stage of the active phase (OR:8.4, 95% CI:4.83– 14.59). The area under the curve (AUC) for this predictive model was 0.910 (95% CI: 0.878– 0.941). The Hosmer-Lemeshow goodness-of-fit test and calibration curve results showed that (P=0.992 > 0.05). Within the clinical decision curve, the net benefit of the nomogram model is higher across the threshold probability range of 0.05 to 0.83.
Conclusion: This risk prediction model can identify high-risk cephalic dystocia post-epidural analgesia during the early active phase of labor, providing an instant assessment tool for timely intervention and better outcomes.
Keywords: cephalic dystocia, epidural labor analgesia, predictive model, nomogram