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| Construction of a prediction model for pelvic organ prolapse among primiparous women after vaginal delivery |
| WANG Chao, ZHANG Luping, CHEN Mengyu, HUA Xia, WANG Jing
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| Handan First Hospital, Handan, Hebei 056000, China |
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Abstract Objective To construct a prediction model for pelvic organ prolapse (POP) among primiparous women after vaginal delivery, so as to provide a basis for early screening and prevention of POP. Methods Primiparous women after vaginal delivery at the First Hospital of Handan City from January 2022 to January 2025 were selected as study participants. Basic information including age and residence, as well as clinical characteristics including neonatal birth weight and forceps-assisted delivery, were collected. POP was diagnosed according to the Chinese Guidelines for the Diagnosis and Treatment of Pelvic Organ Prolapse (2020 Edition). LASSO regression and multivariable logistic regression model were used to analyze and screen independent predictors of POP among primiparous women after vaginal delivery, and a nomogram prediction model was constructed. The predictive performance of the nomogram prediction model was evaluated using the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, accuracy, calibration curve, Hosmer-Lemeshow test, Brier score, and decision curve analysis. Results A total of 200 primiparous women after vaginal delivery were included, of whom 169 (84.50%) were aged <35 years and 149 (74.50%) had a preconception body mass index (BMI) <24 kg/m2. POP occurred in 53 cases, with an incidence of 26.50%. Multivariable logistic regression analysis showed that age (≥35 years, OR=5.300, 95%CI: 1.824-15.399), preconception BMI (≥24 kg/m2, OR=4.371, 95%CI: 1.862-10.263), forceps-assisted delivery (OR=5.001, 95%CI: 1.847-13.536), prolonged duration of the second stage of labor (OR=3.659, 95%CI: 1.415-9.464), and neonatal birth weight (OR=4.695, 95%CI: 2.332-9.450) were independent predictors of POP among primiparous women after vaginal delivery. The constructed nomogram prediction model achieved an AUC of 0.902 (95%CI: 0.842-0.962), a sensitivity of 0.811, a specificity of 0.912, and an accuracy of 0.885, indicating good discrimination. The calibration curve, Hosmer-Lemeshow test (P>0.05), and Brier score (0.081) demonstrated good calibration. Decision curve analysis showed that when the risk threshold probability ranged from 0.12 to 0.70, the net benefit was relatively high. Conclusion The nomogram prediction model for POP constructed in this study exhibits good discrimination, calibration, and clinical utility, and has certain predictive value for POP risk among primiparous women after vaginal delivery.
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Received: 24 November 2025
Revised: 13 February 2026
Published: 21 April 2026
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