[1]刘思琴,刘姗姗,王可,等.肝性脑病风险预测模型建立与验证的系统评价[J].军事护理,2021,38(02):60-63.[doi:10.3969/j.issn.1008-9993.2021.02.016]
　LIU Siqin,LIU Shanshan,WANG Ke,et al.Development and Validation of Hepatic Encephalopathy Risk Prediction Models: A Systematic Review[J].Nursing Journal Of Chinese People's Laberation Army,2021,38(02):60-63.[doi:10.3969/j.issn.1008-9993.2021.02.016]
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肝性脑病风险预测模型建立与验证的系统评价
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《军事护理》[ISSN:2097-1826/CN:31-3186/R]

卷:
38
期数:
2021年02期
页码:
60-63
栏目:
循证护理
出版日期:
2021-02-15

文章信息/Info

Title:
Development and Validation of Hepatic Encephalopathy Risk Prediction Models: A Systematic Review
文章编号:
1008-9993(2021)02-0060-05
作者:
刘思琴; 刘姗姗; 王可; 王小梅
(重庆医科大学附属第二医院 肝胆外科,重庆 400010)
Author(s):
LIU Siqin; LIU Shanshan; WANG Ke; WANG Xiaomei
(Department of Hepatobiliary Surgery,The Second Affiliated Hospital of Chongqing Medical University Chongqing 400010,China)
关键词:
肝性脑病;  预测模型;  系统评价
Keywords:
hepatic encephalopathy;  prediction model;  systematic review
分类号:
R47
DOI:
10.3969/j.issn.1008-9993.2021.02.016
文献标志码:
A
摘要:
目的 系统评价肝性脑病风险预测模型建立与验证情况。方法 采用主题词和自由词结合,计算机检索PubMed、Embase、Cochrane、中国知网、万方医学网、维普等数据库建库至2020年5月发表的肝性脑病风险预测模型相关文献,由2名研究者独立阅读并筛选文献,采用临床预测模型的偏倚风险评估工具CHARMS清单对纳入文献进行质量评价。结果 共纳入11个研究,其中6个为前瞻性研究; 5个模型进行了外部验证,4个模型未进行内部或外部验证; 纳入研究的方法学质量评价偏倚风险较小; 纳入模型最常见的诱发因素和易感因素分别为肝性脑病病史和肝功能下降,白蛋白是常见的保护因子; 模型曲线下面积为0.68～0.93。结论 纳入的模型具有良好的预测效能,可帮助医护人员早期识别肝性脑病的高风险人群,但模型预测效果的外推性未得到有效评价,未来需开展进一步研究对模型进行外部验证。
Abstract:
Objective To systematically review the development and validation of hepatic encephalopathy risk prediction models.Methods The Cochrane Library,PubMed,Embase,CNKI,VIP,and Wan Fang Databases were electronically searched to collect studies on hepatic encephalopathy risk prediction model from inception to May 2020. Two reviewers independently screened and analysis the literature,evaluated the included studies according to the CHARMS checklist.Results A total of 11 studies were included,of which 6 were prospective studies. 5 models were externally verified,while 4 models were not internally or externally verified. The methodological quality evaluation of the included studies had low bias.The most common predisposing and precipitating factors included in the model were the history of hepatic encephalopathy and the decline in liver function. Albumin was a common protective factor. All studies reported the area under receiver of characteristic curve(AUROC)0.68-0.93.Conclusions The included model has good predictive performance and can help medical staff to identify high-risk groups of hepatic encephalopathy in early stage, but the extrapolation of the model's predictive effect has not been effectively evaluated, and further research is needed to verify the model externally in the future.

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(本文编辑:郁晓路)

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备注/Memo

备注/Memo:
【 收稿日期 】 2020-10-28 【 修回日期 】 2021-01-09
【 基金项目 】 重庆市技术创新与应用发展项目(cstc2019jscx-msxmX0117)
【 作者简介 】 刘思琴,硕士在读,护师,从事慢性肝病管理研究
【 通讯作者 】 王小梅,电话:023-62887551
更新日期/Last Update: 2021-02-15