We aimed to develop and validate a nomogram integrating clinical and sonographic characteristics for the individualized SUI risk evaluation in the early postpartum stage.
This was a prospective cross-sectional study. From June 2020 to September 2022, singleton primiparas who underwent TPUS examination at 6-8 weeks postpartum were recruited. They were divided into the training and validation cohorts at a ratio of 8:2 according to the temporal split. All subjects were interviewed before TPUS examination. Univariate and multivariate logistic analyses were performed to develop three models: the clinical, sonographic, and combined models. The ROC curve was plotted to evaluate model discrimination ability. Finally, the combined model was selected to establish the nomogram. The nomogram's discrimination, calibration, and clinical usefulness were evaluated in the training and validation cohorts.
The performance of the combined model was better than that of the clinical and sonographic models. Six predictors (BMI, delivery mode, lateral episiotomy, SUI during pregnancy, cystocele, and bladder neck funneling) remained in the combined model. The nomogram based on the combined model had good discrimination with AUCs of 0.848 (95% CI: 0.796-0.900) and 0.872 (95% CI: 0.789-0.955) in the training and validation cohorts, respectively, and the calibration curve showed good efficiency in assessing postpartum SUI. Decision curve analysis showed that the nomogram was clinically useful.
The nomogram based on clinical and sonographic characteristics showed good efficiency in assessing postpartum SUI risk and can be a convenient and reliable tool for individual SUI risk assessment.
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine. 2023 Jun 21 [Epub ahead of print]
Ting Xiao, Yunqing Cao, Chaojiong Zhen, Ziman Chen, Weijun Huang, Zhongzhen Su
Department of Ultrasound, Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, China., Department of Ultrasound, The First People's Hospital of Foshan, Foshan, China., Department of Health Technology and Informatics, Hong Kong Polytechnic University, Kowloon, Hong Kong.