A systematic review of risk prediction models for frailty in patients with cardiovascular disease

LIU Liu; LI Zhuanzhen; MENG Haiying; KOU Xiaokang; NIU Shaoqiong

doi:10.12104/j.issn.1674-4748.2024.18.004

Abstract：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 1 654 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.