Archivos espanoles de urologia · 2026
Establishment and Validation of a Nomogram Model for Predicting the Risk of Postpartum Stress Urinary Incontinence in Women during the Perinatal Period.
СтатьяВалидационное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Yu Shuwen, Yin Fengling, Fan Yihui, Qu Qiuchan
Аннотация
OBJECTIVE: This study aims to analyse factors influencing maternal postpartum stress urinary incontinence (SUI) and construct a prediction model using a nomogram.
METHODS: A retrospective analysis of clinical data was conducted on 500 women who delivered at our hospital between June 2021 and June 2024, of whom 147 developed postpartum SUI. The participants were randomly assigned to the modelling (n = 354) or validation groups (n = 146) in a 7:3 ratio. The modelling group was further subdivided on the basis of postpartum SUI occurrence: SUI (n = 106) and non-SUI groups (n = 248). Relevant factors were identified through logistic regression analysis, and a nomogram was constructed using R software. The nomogram was evaluated through receiver operating characteristic, calibration and decision curves.
RESULTS: Significant differences existed between the SUI and non-SUI groups in maternal educational attainment, newborn weight, current address, natural birth and gestation period (p < 0.05). Educational attainment (junior high school and below), increase in newborn weight, rural residence, natural birth and parity (≥ 2) were identified as risk factors for postpartum SUI (p < 0.05). The nomogram showed good predictive performance with area under the curve (AUC) values of 0.778 and 0.754 for the modelling and validation groups, respectively (p < 0.05).
CONCLUSIONS: Maternal educational attainment, newborn weight, current address, natural birth and gestation period are risk factors for postpartum SUI. Based on these factors, the proposed nomogram model is a potentially reliable tool for predicting postpartum SUI risk.
METHODS: A retrospective analysis of clinical data was conducted on 500 women who delivered at our hospital between June 2021 and June 2024, of whom 147 developed postpartum SUI. The participants were randomly assigned to the modelling (n = 354) or validation groups (n = 146) in a 7:3 ratio. The modelling group was further subdivided on the basis of postpartum SUI occurrence: SUI (n = 106) and non-SUI groups (n = 248). Relevant factors were identified through logistic regression analysis, and a nomogram was constructed using R software. The nomogram was evaluated through receiver operating characteristic, calibration and decision curves.
RESULTS: Significant differences existed between the SUI and non-SUI groups in maternal educational attainment, newborn weight, current address, natural birth and gestation period (p < 0.05). Educational attainment (junior high school and below), increase in newborn weight, rural residence, natural birth and parity (≥ 2) were identified as risk factors for postpartum SUI (p < 0.05). The nomogram showed good predictive performance with area under the curve (AUC) values of 0.778 and 0.754 for the modelling and validation groups, respectively (p < 0.05).
CONCLUSIONS: Maternal educational attainment, newborn weight, current address, natural birth and gestation period are risk factors for postpartum SUI. Based on these factors, the proposed nomogram model is a potentially reliable tool for predicting postpartum SUI risk.