维持性血液透析病人肌少症风险预测模型的系统评价  

Risk prediction models for Sarcopeniain maintenance hemodialysis patients:a systematic review

作　　者：熊玲玲 谷续洁 黎芮彤 岳玉川[2] XIONG Lingling;GU Xujie;LI Ruitong;YUE Yuchuan(Chengdu University of Traditional Chinese Medicine,Sichuan 610032 China)

机构地区：[1]成都中医药大学护理学院,610032 [2]成都市第四人民医院,610036

出　　处：《全科护理》2024年第23期4380-4385,共6页Chinese General Practice Nursing

摘　　要：目的:系统评价维持性血液透析病人肌少症风险预测模型,为临床实践提供依据。方法:检索中国知网(CNKI)、万方数据库(WanFang)、维普数据库(VIP)、CBM、The Cochrane Library、PubMed、Web of Science、Embase数据库中有关维持性血液透析病人肌少症风险预测模型的研究,检索时限为建库至2023年11月30日,由2名研究者独立筛选文献,并根据CHARMS清单和PROBAST评估工具进行资料提取及评价纳入文献偏倚风险和适用性。结果:共纳入14篇文献,包含19个模型,曲线下面积(AUC)为0.712~0.955,进入模型次数最多的预测因子是年龄、性别、体质指数、握力、营养状况等,纳入研究偏倚风险都较高,模型适用性方面,1篇为低适用性。结论:我国维持性血液透析病人肌少症风险预测模型研究处于快速发展阶段,预测性能较好,但偏倚风险较高,未来应注重模型开发的规范性,注重外部验证和临床实践转化研究,以期为临床提供优化、便利的个性化预测模型。Objective:To systematically evaluate the sarcopenia risk prediction model for maintenance hemodialysis patients and provide a basis for clinical practice.Methods:The studies on sarcopenia risk prediction models for maintenance hemodialysis patients were retrieved from CNKI,WanFang,VIP,CBM,The Cochrane Library,Pubmed,Web of Scinence,and Embase databases from the establishment of the database to November 30,2023.Two researchers independently screened the literature,extracted data,and evaluated the risk of bias and applicability of the included literature according to the CHARMS checklist and PROBAST assessment tool.Results:A total of 14 papers were included,including 19 models,with an area under curve(AUC)of 0.712-0.955.Age,sex,body mass index,grip strength,and nutritional status were the predictors that entered the model most frequently,and the risk of bias was high in the included studies.In terms of model applicability,one paper had low applicability.Conclusions:The research on risk prediction model of sarcopenia in maintenance hemodialysis patients in China is in a rapid development stage,with good predictive performance,but high risk of bias.In the future,attention should be paid to the normalization of model development,external validation and clinical practice transformation research,in order to provide an optimized and convenient personalized prediction model for clinical practice.

关 键 词：维持性血液透析 肌少症 预测模型 系统评价 

分 类 号：R473.5[医药卫生—护理学]