Derivation of a risk model to predict urinary incontinence during pregnancy: a research article
摘要
The onset of urinary incontinence (UI) during pregnancy is related to urinary incontinence persistence in the postpartum and later years. We aimed to design a prediction model of urinary incontinence that could be used at the beginning of pregnancy and included clinical and ultrasound variables.
Materials and methodsDesign: Prospective cohort study.
Settings: Obstetrics and Gynecology Service of Santa Caterina’s Hospital (Girona, Spain) between 2018 and 2020.
Population: Women at 12–14 weeks’ gestation were invited to participate by consecutive sampling and a follow-up visit was carried out at 32–35 pregnancy weeks.
Methods: During the visits, we collected clinical data, measured 2D ultrasound variables, and administered the International Consultation on Incontinence Questionnaire (ICIQ-SF). We built a multivariable model to predict urinary incontinence, assessed its calibration and discrimination (with the area under the ROC curve), and performed an internal validation. All the analyses were carried out using the R software (version 4.1).
ResultsWe recruited 174 nulliparous pregnant women during the study period and designed two models to predict urinary incontinence based on the significant variables in the univariate analysis: the urethral mobility and body mass index (BMI). The OR (95% CI) for the BMI category > 30 kg/m2 was 4.24 (1.48–12.30) in the first model (introital urethral mobility and BMI) and 3.31 (1.13–9.62) in the second model (transperineal urethral mobility and BMI). The area under the ROC curve was 0.725 for the first model and 0.687 for the second model. These models were used to create an online urinary incontinence prediction calculator.
ConclusionWe built two multivariable models to predict, at the beginning of pregnancy, the individual risk of each pregnant woman to develop moderate/severe urinary incontinence in the third trimester. These models may provide a foundation for the future development of tailored primary prevention strategies.