护理学杂志2024,Vol.39Issue(6) :58-62.DOI:10.3870/j.issn.1001-4152.2024.06.058

冠状动脉旁路移植术后患者机械通气时间延长风险预测模型的系统评价

Risk prediction models of prolonged mechanical ventilation in patients after coro-nary artery bypass grafting:a systematic review

李永刚 黄雨佳 刘庚 刘周周 吴荣
护理学杂志2024,Vol.39Issue(6) :58-62.DOI:10.3870/j.issn.1001-4152.2024.06.058

冠状动脉旁路移植术后患者机械通气时间延长风险预测模型的系统评价

Risk prediction models of prolonged mechanical ventilation in patients after coro-nary artery bypass grafting:a systematic review

李永刚 1黄雨佳 1刘庚 1刘周周 1吴荣1
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作者信息

  • 1. 中国医学科学院阜外医院成人外科恢复室一区(北京,100030)
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摘要

目的 对冠状动脉旁路移植术后患者机械通气时间延长风险预测评估模型进行系统评价,为临床实践和相关研究提供参考.方法 计算机检索PubMed、Embase、Web of Science、中国知网、万方数据等数据库中有关冠状动脉旁路移植术后患者机械通气时间延长风险预测模型的研究,检索时限为建库至2022年12月31日.由2名研究者独立筛选和提取数据,并采用预测模型偏倚评估工具对纳人文献进行偏倚和适用性评价.结果 共纳入8篇文献,包括5项预测模型开发研究和3项预测模型效能验证研究.结论 风险预测模型对冠状动脉旁路移植术后患者机械通气时间延长的预测效能一般,且整体偏倚风险较高.未来可基于大样本数据,构建低偏倚风险、高适用性的本土化预测模型.

Abstract

Objective A systematic review was performed to examine the risk prediction models for prolonged mechanical ventilation in patients after coronary artery bypass grafting(CABG),in order to provide references for clinical practice and related research.Methods A systematic search was conducted in databases including PubMed,Embase,Web of Science,CNKI,and Wanfang Data to identify studies related to risk prediction models for prolonged mechanical ventilation in patients after CABG.The search was conducted from database inception to December 31,2022.Two researchers independently screened and extracted data,and the pre-diction model risk of bias assessment tool was used to evaluate the bias and applicability of the included literature.Results A total of 8 articles were included,consisting of 5 studies on the development of prediction models and 3 studies on the validation of pre-diction model efficacy.Conclusion The predictive efficacy of risk prediction models for prolonged mechanical ventilation in patients after CABG is generally moderate,with an overall high risk of bias.Future efforts should focus on constructing locally applicable prediction models with low bias risk based on large sample data.

关键词

冠心病/冠状动脉旁路移植/机械通气/通气时间/风险预测模型/偏倚风险/系统评价

Key words

coronary heart disease/coronary artery bypass grafting/mechanical ventilation/ventilation time/risk prediction model/risk of bias/systematic review

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基金项目

中国医科院阜外医院护理部专项(HLB2022005)

出版年

2024
护理学杂志
华中科技大学同济医学院

护理学杂志

CSTPCD北大核心
影响因子:2.062
ISSN:1001-4152
参考文献量18
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