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脑卒中后急性肾损伤风险预测模型的系统评价

杨莉 秦琴 刘菡萏 李惠明 魏雪梅 崔丽君

医学新知2025,Vol.35Issue(5):562-571,10.
医学新知2025,Vol.35Issue(5):562-571,10.DOI:10.12173/j.issn.1004-5511.202411047

脑卒中后急性肾损伤风险预测模型的系统评价

A systematic review of risk prediction models for post-stroke acute kidney injury

杨莉 1秦琴 1刘菡萏 2李惠明 1魏雪梅 1崔丽君3

作者信息

  • 1. 川北医学院附属医院护理部(四川南充 637000)
  • 2. 川北医学院附属医院护理部(四川南充 637000)||川北医学院附属医院眼科(四川南充 637000)
  • 3. 川北医学院附属医院眼科(四川南充 637000)||川北医学院附属医院输血科(四川南充 637000)
  • 折叠

摘要

Abstract

Objective To systematically evaluate the risk prediction model for acute kidney injury(AKI)after stroke.Methods Studies on post-stroke AKI risk prediction models from PubMed,Web of Science,Cochrane Library,Embase,CNKI,Wanfang,VIP,and Chinese Biomedical Literature Database were searched from inception to December 23,2024.The Prediction Model Risk of Bias Assessment Tool(PROBAST)were used to evaluate the bias and applicability of studies,and descriptive methods were used to analyze model characteristics.Results A total of 15 studies were included,including 33 predictive models.11 studies(73.3%)used Logistic regression models to construct predictive models,6 studies(40.0%)selected predictive factors based on single factor analysis,3 studies(20.0%)did not report methods for handling missing data,14 studies(93.3%)presented predictive models through column charts,risk scoring scales,and regression equations.The common predictive factors included in the models included age,hypertension,serum creatinine,blood urea nitrogen,use of diuretics.11 studies(73.3%)were internally validated,and 7 studies(46.7%)were externally validated.Among the 33 models,26 models reported the area under the curve of the receiver operating characteristic curve,and 13 models(39.4%)were evaluated for calibration using calibration curves or Hosmer-Lemeshow goodness of fit tests.All included studies had a high risk of bias,and 11 studies had good applicability.Conclusion The quality of the modeling methodology for AKI risk prediction models after stroke is uneven,and the overall risk of bias is high.In the future,the development quality of prediction models should be further improved by following PROBAST standards and TRIPOD reporting standards.

关键词

脑卒中/急性肾损伤/预测模型/风险/系统评价

Key words

Stroke/Acute kidney injury/Prediction model/Risk/Systematic review

分类

临床医学

引用本文复制引用

杨莉,秦琴,刘菡萏,李惠明,魏雪梅,崔丽君..脑卒中后急性肾损伤风险预测模型的系统评价[J].医学新知,2025,35(5):562-571,10.

基金项目

南充市科学技术局项目基金(23JCYJPT0046) (23JCYJPT0046)

医学新知

1004-5511

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