Establishment of a nomogram model for predicting the risk of postpartum stress urinary incontinence based on pelvic floor ultrasound and clinical data
10.3969/j.issn.1009-8291.2023.11.003
- VernacularTitle:基于盆底超声及临床数据预测产后发生压力性尿失禁风险的列线图模型
- Author:
Jie SU
1
;
Hongmin ZHAO
1
;
Chunli WANG
1
;
Na LI
1
;
Shanshan LU
1
;
Ning LI
1
Author Information
1. Department of Ultrasound, Yihe Obstetrics and Gynecology Hospital, Cangzhou People’s Hospital, Cangzhou 061000, China
- Publication Type:Journal Article
- Keywords:
stress urinary incontinence;
pelvic floor ultrasound;
nomogram model;
postpartum urinary incontinence;
influencing factors
- From:
Journal of Modern Urology
2023;28(11):928-932
- CountryChina
- Language:Chinese
-
Abstract:
【Objective】 To analyze the risk factors of postpartum stress urinary incontinence (SUI) and to establish a nomogram model. 【Methods】 A total of 278 puerpera who gave birth at our hospital during Dec.2018 and Aug.2020 were selected as the modeling group, and 132 puerpera who gave birth during Sep.2020 and Sep.2021 were involved in the verification group. Factors affecting postpartum SUI were identified with univariate and multivariate logistic regression, and a nomogram prediction model was constructed with R software. The predictive effectiveness and discrimination of the model were assessed, and the decision curve analysis (DCA) was drawn to evaluate the clinical application value of the model. 【Results】 A total of 84 cases (30.22%) in the modeling group developed SUI 2 months after delivery. Fetal weight, delivery method, maternal age, mobility (Δhy) and rotation Angle (Δβ) were factors affecting postpartum SUI (P<0.05). Multivariate logistic regression analysis showed that increased fetal weight, normal delivery, increased Δhy, and increased Δβ were independent risk factors of postpartum SUI (P<0.05). The constructed nomogram fitted well. The H-L fit curve of the modeling group and verification group were (χ2=7.514, P=0.312) and (χ2=6.157, P=0.267), respectively. The area under the receiver operating characteristic curve of the modeling group and verification group were 0.815 and 0.760, respectively, indicating high specificity and consistency. DCA indicated that when the high-risk threshold probability of the model was between 0.06-0.80, the nomogram model had a high clinical value. 【Conclusion】 Increased fetal weight, normal delivery, increased Δhy and elevated Δβ are independent risk factors that affect postpartum SUI. The nomogram model constructed has good predictive effectiveness and discrimination, and high clinical application value.
