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

Author:

Liang Surui1,Huang Shijie12,Andarini Esti12,Wang Ying12,Li Yan3,Cai Wenzhi1ORCID

Affiliation:

1. Administrative Building Shenzhen Hospital of Southern Medical University Shenzhen Guangdong China

2. School of Nursing Southern Medical University Guangzhou Guangdong China

3. School of Nursing The Hong Kong Polytechnic University Hong Kong China

Abstract

AbstractBackgroundThis 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.

Publisher

Wiley

Subject

Urology,Neurology (clinical)

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3