To establish and validate a nomogram model for stress urinary incontinence of late pregnancy and then evaluate its effectiveness.
Single-center cross-sectional study.
From January 2025 to June 2025, 414 pregnant women in the late stage of pregnancy who established medical records at a tertiary obstetrics and gynaecology hospital in Shanghai were surveyed through questionnaire. The patients were divided into the modelling group and the validation group in a ratio of 7:3. Among them, 290 cases were used for the training set and 124 cases for the validation set. The data were collected and verified by two individuals, and then a single-factor analysis was conducted. The statistically significant variables in the training set were subjected to Lasso regression analysis to further screen out potential influential variables. Subsequently, a multivariate Logistic regression analysis was performed. Finally, six variables were included in the model. A nomogram model was established and then validated using receiver operating characteristic (ROC) curves, calibration curves, Hosmer-Lemeshow goodness of fit test, and decision curve analysis.
Six factors were included in the model, including age, history of miscarriage, pelvic floor muscle training, family history of urinary incontinence, smoking habits and coffee consumption. The AUC of the training set was 0.845 (95% CI 0.799-0.891), with specificity and sensitivity being 0.729 and 0.849 respectively, and the optimal cut-off value was 0.505. The area under the curve of the validation set was 0.805 (95% CI 0.725-0.885), with specificity and sensitivity being 0.636 and 0.870 respectively, and the optimal cut-off value was 0.469. Calibration tests and DCA demonstrated favourable discrimination and clinical practicability of the nomogram.
No patient or public representatives were involved in the design, statistical analysis or manuscript writing procedures of this research. But the established nomogram avoids complex statistical calculation, enables obstetric midwives to rapidly identify high-risk women at the prenatal clinic, and facilitates targeted pelvic floor muscle training health education and lifestyle intervention to reduce gestational SUI burden for pregnant populations.
Nursing open. 2026 Aug [Epub]
Shanshan Shan, Ying Chen, Junying Li, Xin Zhang, Yu Chen, Hui Jiang, Yaoxiang Duan
Delivery Room, Shanghai First Maternity and Infant Hospital, Shanghai, China., Outpatient Department, Shanghai First Maternity and Infant Hospital, Shanghai, China., Nursing Department, Shanghai First Maternity and Infant Hospital, Shanghai, China.