Development and internal validation of a risk prediction model for stress urinary incontinence throughout pregnancy: A multicenter retrospective longitudinal study in Indonesia

被引:0
作者
Liang, Surui [1 ]
Huang, Shijie [1 ,2 ]
Andarini, Esti [1 ,2 ]
Wang, Ying [1 ,2 ]
Li, Yan [3 ]
Cai, Wenzhi [1 ,4 ]
机构
[1] Southern Med Univ, Shenzhen Hosp, Adm Bldg, Shenzhen, Guangdong, Peoples R China
[2] Southern Med Univ, Sch Nursing, Guangzhou, Guangdong, Peoples R China
[3] Hong Kong Polytech Univ, Sch Nursing, Hong Kong, Peoples R China
[4] Southern Med Univ, Shenzhen Hosp, Adm Bldg,Room 815,Xinhu Rd 1333, Shenzhen, Guangdong, Peoples R China
关键词
Indonesia; pregnant women; risk prediction model; stress urinary incontinence; CALIBRATION; PREVALENCE; NOMOGRAM; WOMEN;
D O I
10.1002/nau.25364
中图分类号
R5 [内科学]; R69 [泌尿科学(泌尿生殖系疾病)];
学科分类号
1002 ; 100201 ;
摘要
BackgroundThis study aimed to develop a risk prediction model for stress urinary incontinence (SUI) throughout pregnancy in Indonesian women.MethodsWe conducted a multicenter retrospective longitudinal study involving pregnant women in Indonesia, who sought care at obstetrics clinics from January 2023 to March 2023, encompassing all stages of pregnancy. We collected data on their predictive factors and SUI outcome. SUI was diagnosed based on responses to the "leaks when you are physically active/exercising" criterion in the ICIQ-UI-SF questionnaire during our investigation of the participants. The models underwent internal validation using a bootstrapping method with 1000 resampling iterations to assess discrimination and calibration.ResultsA total of 660 eligible pregnant women were recruited from the two study centers, with an overall SUI prevalence of 39% (258/660). The final model incorporated three predictive factors: BMI during pregnancy, constipation, and previous delivery mode. The area under the curve (AUROC) was 0.787 (95% CI: 0.751-0.823). According to the max Youden index, the optimal cut-off point was 44.6%, with a sensitivity of 79.9% and specificity of 65.9%. A discrimination slope of 0.213 was found.ConclusionThe developed risk prediction model for SUI in pregnant women offers a valuable tool for early identification and intervention among high-risk SUI populations in Indonesian pregnant women throughout their pregnancies. These findings challenge the assumption that a high BMI and multiple previous deliveries are predictors of SUI in Indonesian women. Further research is recommended to validate the model in diverse populations and settings.
引用
收藏
页码:354 / 363
页数:10
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