ISSN 2097-6046（网络）
ISSN 2096-7446（印刷）
CN 10-1655/R
主管：中国科学技术协会
主办：中华护理学会
中华急危重症护理杂志

中华急危重症护理杂志 ›› 2026, Vol. 7 ›› Issue (9): 1132-1139.doi: 10.3761/j.issn.2096-7446.2026.09.018

• 证据综合研究 • 上一篇    下一篇

脑卒中患者误吸风险预测模型的系统评价

李相濡1(), 周红1,*(), 耿敬1, 毛方菊2, 周娟2, 徐晨阳3, 刘强1   

  1. 1 长江大学医学部 湖北省荆州市 434023
    2 长江大学附属第一医院神经重症监护室 湖北省荆州市 434023
    3 华中科技大学同济医学院附属同济医院康复科 武汉市 430030
  • 收稿日期:2025-09-20 出版日期:2026-09-10 发布日期:2026-08-31
  • 通讯作者: *周红，E-mail：1059634547@qq.com
  • 作者简介:李相濡：女，本科（硕士在读），护士，E-mail：1831463605@qq.com
    作者贡献声明

    李相濡：资料整理分析、论文撰写；周红、耿敬：研究指导、论文修改；毛方菊：质量控制；周娟、徐晨阳、刘强：文献检索、筛选及质量评价

  • 基金资助:
    湖北省科技创新专项项目(2021CFB601)

Systematic review of aspiration risk prediction models for stroke patients

LI Xiangru1(), ZHOU Hong1,*(), GENG Jing1, MAO Fangju2, ZHOU Juan2, XU Chenyang3, LIU Qiang1   

  1. 1 Yangtze University Health Science Center， Jingzhou， Hubei Province 434023， China
    2 Neurological Intensive Care Unit， the First Affiliated Hospital of Yangtze University，Jingzhou， Hubei Province 434023， China
    3 Department of Rehabilitation Medicine， Tongji Hospital，Tongji Medical College，Huazhong University of Science and Technology， Wuhan 430030， China
  • Received:2025-09-20 Online:2026-09-10 Published:2026-08-31
  • Contact: * ZHOU Hong，E-mail：1059634547@qq.com
  • Supported by:
    Hubei Provincial Science and Technology Innovation Special Project(2021CFB601)

RichHTML

PDF下载

补充材料

1

摘要：

目的 系统评价脑卒中患者误吸风险预测模型，为临床早期识别高危患者提供循证依据。方法 系统检索万方数据库、维普数据库、中国知网、中国生物医学文献数据库、Web of Science、PubMed和Embase等数据库，检索时限从建库至2025年1月20日。由2名研究者独立完成文献筛选、数据提取，并采用预测模型偏倚风险评估工具进行质量评价。结果 共纳入18项研究，包含25个预测模型，受试者操作特征曲线下面积为0.715~0.955。16项研究具有较好适用性，2项研究适用性较差。18项研究均存在高偏倚风险，主要来源包括数据来源选择不当、样本量不足、缺失数据处理不充分、变量筛选不合理及模型效能验证缺乏等。结论 现有脑卒中患者误吸风险预测模型临床适用性较好，但偏倚风险较高，未来需优化研究设计、加强外部验证，并进一步验证其临床应用价值。

关键词: 误吸, 脑卒中, 预测模型, 系统评价, 护理

Abstract:

Objective To systematically evaluate aspiration risk prediction models for stroke patients and provide evidence-based support for the early identification of high-risk patients in clinical practice. Methods A comprehensive search was conducted in multiple databases，including Wan fang，VIP，CNKI，China Biomedical Literature Database，Web of Science，PubMed，and Embase，with a search period from database inception to January 20，2025. Literature screening and data extraction were independently performed by two researchers，and the Prediction Model Risk of Bias Assessment Tool（PROBAST） was used for quality assessment. Results A total of 18 studies was included，encompassing 25 prediction models. The area under the receiver operating characteristic curve ranged from 0.715 to 0.955. Sixteen studies demonstrated good applicability，while two studies had poor applicability. All 18 studies exhibited a high risk of bias，mainly due to inappropriate data source selection，small sample size，insufficient handling of missing data，unreasonable variable selection，and a lack of model efficacy validation. Conclusion The existing stroke aspiration risk prediction models show good clinical applicability but are associated with a high risk of bias. Future research should focus on optimizing study design，enhancing external validation，and further assessing their clinical application value.

Key words: Aspiration, Stroke, Prediction Model, Systematic Review, Nursing Care