以质量求发展，以服务铸品牌

护理学报 ›› 2023, Vol. 30 ›› Issue (19): 45-50.doi: 10.16460/j.issn1008-9969.2023.19.045

• 循证护理 • 上一篇    下一篇

老年人认知衰弱风险预测模型的系统评价

周飞洋1,2, 邓露1, 龙柯宇2, 杨婷婷2, 谢琳琳2, 吕倩1, 郭春波1   

  1. 1.中南大学湘雅二医院临床护理教研室,湖南 长沙 410011;
    2.中南大学湘雅护理学院,湖南 长沙 410013
  • 收稿日期:2023-09-10 出版日期:2023-10-10 发布日期:2023-11-07
  • 通讯作者: 郭春波（1985-）,女,湖南长沙人,硕士,主管护师。E-mail: 154780593@qq.com
  • 作者简介:周飞洋（1996-）,女,湖南岳阳人,本科学历,硕士研究生在读,护师。
  • 基金资助:
    湖南省财政厅2022年高校改革发展项目湘财教指[（2022）75号]; 中南大学湘雅二医院护理科研基金[2022-HLKY-19,院行字（2017）88号]

Risk prediction model for cognitive frailty in elderly: a systematic review

ZHOU Fei-yang1,2, DENG Lu1, LONG Ke-yu2, YANG Ting-ting2, XIE Lin-lin2, LV Qing1, GUO Chun-bo1   

  1. 1. Teaching and Research Office of Clinical Nursing, the Second Xiangya Hospital of Central South University, Changsha 410011, China;
    2. Xiangya Nursing School, Central South University, Changsha 410013, China
  • Received:2023-09-10 Online:2023-10-10 Published:2023-11-07

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摘要： 目的 系统评价老年人认知衰弱风险预测模型,以期为认知衰弱的风险预测提供证据支持。方法 系统检索PubMed、Web of Science、Cochrane Library、Embase、CINAHL、中国知网、万方数据库、中国生物医学文献数据库发表的老年人认知衰弱风险预测模型相关文献。检索时限为建库至2023年8月,语种限定为中文和英文。根据纳入与排除标准进行文献筛选,由2名研究者独立进行纳入文献的数据提取和质量评价。提取作者、发表年份、国家、随访时间、研究对象、研究类型、预测因子、模型构建方法及预测效能等数据。结果 共纳入16项研究,老年人认知衰弱等发生率为4.8%~65.3%。纳入研究的适用性较好,但总体偏倚风险较高。多个模型重复报告的预测因子有：年龄、营养、活动能力和多病等。结论 老年人认知衰弱风险预测模型尚处于发展阶段,部分模型存在显著的方法学缺陷和高偏倚风险。未来的研究中应借助大数据,构建内容全面的老年人认知衰弱风险预测模型并加以验证,形成可行性高的信息化风险预警系统。

关键词: 老年, 认知衰弱, 预测模型, 风险评估, 系统评价

Abstract: Objective To systematically review the risk prediction models of cognitive frailty in the elderly, and to provide evidence support for the risk prediction of cognitive frailty. Methods Systematic search of the literature regarding risk prediction models of cognitive frailty in the elderly in PubMed, Web of Science, the Cochrane Library, Embase, CINAHL, CNKI, Wanfang database, and SinoMed was conducted. The search time was from the inception of the database to August 2023, and the language was limited to Chinese and English. Literature screening was conducted according to the inclusion and exclusion criteria, and data extraction and quality evaluation of the included literature were carried out by two researchers independently. The information of author, year of publication, country, follow-up time, study object, study type, predictors, model construction method, and predictive efficacy was extracted. Results Sixteen studies were included, all of which were studies on model development. The prevalence of cognitive frailty in the elderly ranged from 4.8% to 65.3%. The applicability was good in included studies, but the overall risk of bias was high. Predictors reported repeatedly by multiple models were age, nutrition, activity of daily living and multimorbidity. Conclusion Risk prediction model of cognitive frailty in the elderly is still in the developmental stage, and some models have significant methodological flaws and a high risk of bias. Future research should focus on the establishment of comprehensive risk prediction models and their validation with the help of big data to form an informative risk warning system with high feasibility.

Key words: elderly people, cognitive frailty, prediction model, risk assessment, systematic review

中图分类号: 

  • R473.59
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