[1]毛怡君,范惠,张维,等.脑卒中患者吞咽障碍风险预测模型的系统评价[J].军事护理,2023,40(10):96-100106.[doi:10.3969/j.issn.2097-1826.2023.10.023]
　MAO Yijun,FAN Hui,ZHANG Wei,et al.Risk Prediction Models for Dysphagia in Stroke Patients: A Systematic Review[J].Nursing Journal Of Chinese People's Laberation Army,2023,40(10):96-100106.[doi:10.3969/j.issn.2097-1826.2023.10.023]
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脑卒中患者吞咽障碍风险预测模型的系统评价
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《军事护理》[ISSN:2097-1826/CN:31-3186/R]

卷:
40
期数:
2023年10期
页码:
96-100106
栏目:
循证护理
出版日期:
2023-10-15

文章信息/Info

Title:
Risk Prediction Models for Dysphagia in Stroke Patients: A Systematic Review
文章编号:
2097-1826(2023)10-0096-06
作者:
毛怡君1; 范惠2; 张维1; 李尔清3; 鱼丽荣2
(1.咸阳市中心医院 神经内科,陕西 咸阳 712000; 2.咸阳市中心医院 护理部; 3.咸阳市中心医院 介入导管室)
Author(s):
MAO Yijun1; FAN Hui2; ZHANG Wei1; LI Erqing3; YU Lirong2
(1.Department of Neurology,Xianyang Central Hospital,Xianyang 712000,Shaanxi Province,China; 2.Department of Nursing,Xianyang Central Hospital; 3.Interventional Catheterization Room,Xianyang Central Hospital)
关键词:
脑卒中;  吞咽障碍;  危险因素;  预测;  系统评价;  护理
Keywords:
stroke;  dysphagia;  risk factor;  prediction;  systematic review;  nursing
分类号:
R47-05
DOI:
10.3969/j.issn.2097-1826.2023.10.023
文献标志码:
A
摘要:
目的 系统评价脑卒中患者吞咽障碍风险预测模型,以期为临床实践提供参考依据。方法 检索中国知网、万方、PubMed、Cochrane和Embase数据库中脑卒中患者吞咽障碍风险预测模型相关文献,对文献特征、研究类型、预测因子、模型构建方法和结果等进行分析和比较。结果 共纳入11项研究,7项为模型的开发研究,4项为模型的开发和验证研究。受试者工作特征曲线下面积(the area under curve,AUC)均>0.7,模型区分度较好; 5项研究报告了校准度,拟合优度检验结果均P>0.05,提示模型有较好的校准能力。模型适用性较好,但偏倚风险较高,主要原因为样本量不合理、直接剔除缺失数据、基于单因素分析法筛选预测因子、缺乏模型性能评估等。结论 脑卒中患者吞咽障碍风险预测模型的研究尚处于发展阶段,未来可结合机器学习算法,开发本土化、预测性能良好、使用简便的预测模型。
Abstract:
Objective To systematically evaluate the risk prediction models of dysphagia in stroke patients,so as to provide a reference for clinical practice.Methods CNKI,Wanfang,PubMed,Cochrane and Embase databases were searched for literature related to risk prediction models of dysphagia in stroke patients.The literature characteristics,study types,predictors,model construction methods and results were analyzed and compared.Results A total of 11 studies were included,with 7 studies on model development and 4 studies on model development and validation.The area under the area under curve(AUC)was greater than 0.7,indicating that the model had good discrimination.Five studies reported the calibration degree,and the goodness-of-fit test results were all P> 0.05,indicating that the model had good calibration ability.The model had good applicability,but had a high risk of bias,mainly due to unreasonable sample size,direct exclusion of missing data,screening of predictors based on univariate analysis,and lack of model performance evaluation.Conclusion The research on risk prediction models of dysphagia in stroke patients is still in the development stage.In the future,machine learning algorithms can be combined to develop localized prediction models with good prediction performance and user-friendly features.

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备注/Memo

备注/Memo:
【收稿日期】2023-02-24【修回日期】2023-09-11
【作者简介】毛怡君,硕士,主管护师,电话:029-33284031
【通信作者】张维,电话:029-33284091
更新日期/Last Update: 2023-10-15