孕产妇压力性尿失禁预测模型的系统评价  

Systematic review of predictive models for stress urinary incontinence in pregnant and postpartum women

作　　者：梁晓英 张嘉璐 王天一 张采乐 陈洁[3] 范国荣[3] 张东颖[3] 张蒙 李依霖 薄海欣[2] Liang Xiaoying;Zhang Jialu;Wang Tianyi;Zhang Caile;Chen Jie;Fan Guorong;Zhang Dongying;Zhang Meng;Li Yilin;Bo Haixin(School of Nursing,Chinese Academy of Medical Sciences&Peking Union Medical College,Beijing 100144,China;Department of Nursing,Chinese Academy of Medical Sciences&Peking Union Medical College Hospital,Beijing 100730,China;Department of Obstetrics and Gynecology,Chinese Academy of Medical Sciences&Peking Union Medical College Hospital,Beijing 100730,China)

机构地区：[1]中国医学科学院北京协和医学院护理学院,北京100144 [2]中国医学科学院北京协和医院护理部,北京100730 [3]中国医学科学院北京协和医院妇产科,北京100730

出　　处：《中华现代护理杂志》2025年第12期1619-1627,共9页Chinese Journal of Modern Nursing

基　　金：2023年中国医学科学院临床研究基金(2023-I2M-CT-B-001)。

摘　　要：目的系统评价孕产妇压力性尿失禁(SUI)的预测模型,为相关预测模型的构建、应用及推广提供参考。方法全面检索PubMed、Embase、Web of Science、Cochrane Library、中国知网、万方数据库、中国生物医学文献数据库中关于孕产妇SUI预测模型的相关研究,检索时限为建库至2024年9月30日。2名研究人员严格按照纳入与排除标准独立筛选文献、提取数据,使用预测模型偏倚风险评价工具评价模型质量。结果共纳入23篇文献,包括31个SUI预测模型,共涉及样本量为14473名,其中孕妇SUI预测模型共构建了6个模型,产妇SUI模型共构建25个。纳入的预测因素主要分为孕产妇一般资料、分娩资料、新生儿资料、既往史、流产史、生活习惯资料、盆底肌筛查结果、二维及三维超声检查相关资料、血清学指标9种,其中年龄、分娩方式、产次、体重指数、既往SUI史、新生儿体重是较为公认的预测因素。5篇文献进行了模型的外部验证,5篇文献的偏倚风险及适用性均较好,1篇文献的偏倚风险及适用性均有待提升,其余文献均为偏倚风险高,但适用性较好。结论孕产妇SUI预测模型的建模方法学还有待提高,少有研究进行外部验证,建议今后的模型构建可以建立在大样本、前瞻性的研究设计基础上,纳入适当的预测因素,对研究人群的SUI进行分层分析,以期在临床推广应用。Objective To systematically evaluate predictive models for stress urinary incontinence(SUI)in pregnant and postpartum women,providing a reference for model development,application,and promotion.Methods A comprehensive literature search was conducted in PubMed,Embase,Web of Science,Cochrane Library,China National Knowledge Infrastructure,Wanfang Database,and China Biology Medicine disc for studies on SUI predictive models in pregnant and postpartum women.The search period was from database inception to September 30,2024.Two researchers independently screened the literature and extracted data according to inclusion and exclusion criteria.The risk of bias in the predictive models was assessed using the prediction model risk of bias assessment tool.Results A total of 23 studies were included,covering 31 predictive models for SUI,with a combined sample size of 14473 women.Among them,six models focused on predicting SUI in pregnant women,while 25 models were developed for postpartum SUI.The predictive factors identified in these models were categorized into nine groups,including:general information for pregnant and postpartum women,delivery data,neonatal data,past history,abortion history,lifestyle data,pelvic floor muscle screening results,2D and 3D ultrasound data,and serological indicators.Among these,age,mode of delivery,parity,body mass index,history of SUI,and neonatal weight were widely recognized as key predictive factors.External validation was performed in five studies.Five studies showed good applicability and low bias risk,except for one study that had limitations in both bias risk and applicability,and the remaining studies exhibited a high risk of bias but demonstrated good applicability.Conclusions The methodological quality of SUI predictive models for pregnant and postpartum women needs further improvement.External validation remains insufficient.Future model development should be based on large-sample,prospective studies,incorporating appropriate predictive factors and stratifying SUI risk in differen

关 键 词：孕产妇保健 压力性尿失禁 预测模型 系统评价 

分 类 号：R714.7[医药卫生—妇产科学]