摘要
目的:系统评价心血管疾病病人衰弱发生风险预测模型。方法:系统检索中国知网、中国生物医学文献数据库、万方数据库、维普数据库、PubMed、Embase、the Cochrane Library、Web of Science数据库中关于心血管疾病病人衰弱发生风险预测模型的研究,同时对检索到的文献进行溯源,检索时限为建库至2024年2月29日。由2名研究员独立筛选文献、提取资料并评价纳入研究的偏倚风险。结果:共纳入8项研究,共8个心血管疾病病人衰弱发生风险预测模型,研究总样本量为346~1654例,发生衰弱事件数为98~560例。8个模型均未行外部验证,6个模型仅行内部验证,模型受试者工作特征曲线下面积为0.781~0.991。所纳入预测模型中常见的心血管疾病病人衰弱发生易感因素和速发因素分别为合并症、年龄、日常生活能力、失眠以及营养不良。结论:当前心血管疾病病人衰弱发生风险的预测模型在效能上表现优异,展现出较高的区分度及适用性。然而,模型质量仍有提升空间。在未来的研究中,研究者们需重点关注数据来源的可靠性、预测因素选择的精确性及其测量的标准性,同时妥善处理缺失数据,并全面评价模型性能。此外,对现有模型进行外部验证至关重要,以确保模型的可移植性和可泛化性,使其能够更有效地指导临床实践。
Objective:To systematically evaluate the risk prediction model for frailty in cardiovascular disease patients.Methods:Systematically searched for studies on risk prediction models for cardiovascular disease patients in CNKI,Chinese Biomedical Literature Database,Wanfang,VIP,PubMed,Embase,the Cochrane Library and Web of Science.At the same time,the retrieved documents were traced,and the search time was from the establishment of the database to February 29,2024.Two researchers independently screened the literature,extracted data,and assessed the risk of bias in the included studies.Results:A total of 8 studies were included,with a total of 8 fateful risk prediction models for cardiovascular disease patients.The total sample size of the study ranged from 346 to 1654 cases,and the number of fateful events ranged from 98 to 560 cases.None of the 8 models were verified externally,and only the 6 models were verified internally.The area under the working characteristic curves of the subjects of the models ranged from 0.781 to 0.991.The most common risk factors for frailty in cardiovascular disease patients were comorbidities,age,ability of daily living,insomnia,and malnutrition.Conclusions:Current models for predicting frailty risk in patients with cardiovascular disease perform well in performance,showing high differentiation and applicability.However,there is still room for improvement.In future studies,researchers need to focus on the reliability of data sources,the accuracy of the selection of predictors,and the standardization of measurements,as well as the proper handling of missing data,and the overall evaluation of model performance.In addition,external validation of existing models is critical to ensure their portability and generalizability,enabling them to guide clinical practice more effectively.
作者
刘柳
李转珍
孟海英
寇小康
牛少琼
LIU Liu;LI Zhuanzhen;MENG Haiying;KOU Xiaokang;NIU Shaoqiong(Henan University of Science and Technology,School of Nursing,Henan 461500 China)
出处
《全科护理》
2024年第18期3382-3387,共6页
Chinese General Practice Nursing
基金
河南省医学科技攻关计划项目,编号:LHGJ20210584。
关键词
衰弱
心血管系统
风险预测
模型
系统评价
frailty
cardiovascular system
risk prediction
model
systematic review
