中华护理杂志 ›› 2023, Vol. 58 ›› Issue (12): 1496-1503.DOI: 10.3761/j.issn.0254-1769.2023.12.013

• 证据综合研究 • 上一篇    下一篇

肝切除术后患者肝功能衰竭风险预测模型的系统评价

王伊娜(), 徐亦虹, 柳小琳, 吴文瑾, 颜梦雅, 王美娟, 高杨, 杨丹, 潘红英(), 徐菊玲   

  1. 310000 杭州市 浙江大学医学院附属邵逸夫医院护理部(王伊娜,王美娟,高杨,潘红英),普外科(徐亦虹),骨科(杨丹);厦门医学院护理学院(柳小琳);湖州师范学院护理学院(吴文瑾,徐菊玲);浙江中医药大学护理学院(颜梦雅)
  • 收稿日期:2022-07-20 出版日期:2023-06-20 发布日期:2023-06-25
  • 通讯作者: 潘红英,E-mail:panhy@srrsh.com
  • 作者简介:王伊娜:女,本科(硕士在读),护士,E-mail:wangyina2020@163.com
  • 基金资助:
    2022年浙江省医药卫生科技临床研究应用项目(2022KY836)

A systematic review of risk prediction models for liver failure after hepatic resection

WANG Yina(), XU Yihong, LIU Xiaolin, WU Wenjin, YAN Mengya, WANG Meijuan, GAO Yang, YANG Dan, PAN Hongying(), XU Juling   

  • Received:2022-07-20 Online:2023-06-20 Published:2023-06-25

摘要:

目的 系统地检索和评价肝切除术后患者肝功能衰竭的风险预测模型,旨在为构建更高质量的肝切除术后患者肝功能衰竭的风险预测模型提供参考。 方法 检索中国知网、万方数据库、中国生物医学文献数据库、PubMed、Web of Science、Embase、Cochrane Library、CINAHL数据库中有关肝切除术后患者肝功能衰竭风险预测模型构建的研究,检索时限为建库至2022年2月26日,由2名研究者独立筛选文献,并根据预测模型研究数据提取表和偏倚风险评估工具进行资料提取以及评价纳入文献的偏倚风险和适用性。 结果 共纳入18项肝切除术后患者肝功能衰竭风险预测模型的构建研究,涉及21个模型,受试者工作特征曲线下面积为0.690~0.883。模型重复报告的独立预测因子为总胆红素浓度、剩余肝脏体积、血小板计数、凝血酶原时间、白蛋白浓度、肝硬度、肝切除范围。尚有争议的预测因子为男性、腹腔镜手术、肝-肌比率。纳入研究的偏倚风险均较高,主要原因是样本量不足、连续性变量处理方式不合理、缺乏模型性能评估以及模型过度拟合等。 结论 现有的肝切除术后患者肝功能衰竭风险预测模型尚处于发展阶段,预测因子存有一定共性与争议,未来可开展模型的验证研究或开发性能优良的本土化预测模型。

关键词: 肝切除, 肝功能衰竭, 预测, 模型, 系统评价, 护理

Abstract:

Objective We systematically retrieved and evaluated risk prediction models for liver failure after hepatic resection,so as to provide a reference for constructing higher quality risk prediction models for liver failure after hepatic resection. Methods CNKI,Wanfang,sinomed,PubMed,web of science,Embase,Cochrane Library,CINAHL databases were searched for studies on the construction of risk prediction models for liver failure after hepatectomy. The literature was independently screened by 2 researchers and the information was extracted,and the risk of bias and applicability of the included literature was evaluated according to the Predictive Modelling Study Data Extraction Form and the Risk of Bias Assessment Tool. Results A total of 18 studies on the construction of risk prediction models for liver failure after hepatectomy were included,involving 21 models with an area under the subject working characteristic curve of 0.690~0.883. The independent predictors that were repeatedly reported by the models were total bilirubin,residual liver volume,platelet count,prothrombin time,albumin concentration,liver stiffness,and extent of liver resection. Some predictors are controversial,including male,laparoscopic surgery,liver-muscle ratio. The risk of bias in all studies is high,mainly due to insufficient sample size,poor treatment of continuous variables,lack of model performance assessment and over-fitting of models. Conclusion The existing models for predicting the risk of liver failure after hepatectomy are still in the development stage,and there are certain commonalities and controversies in the predictors,which can be further improved by conducting model validation studies or developing localized prediction models with good performance in the future.

Key words: Liver Resection, Liver Failure, Forecasting, Model, Systematic Review, Nursing Care