围手术期非计划性低体温风险预测模型的系统评价

Systematic review of Inadvertent Perioperative Hypothermia risk prediction model

目的:系统评价围手术期非计划性低体温(IPH)风险预测模型。方法:检索PubMed、Embase、Cochrane Library、CHINAL、Web of Science、知网、万方、维普和中国生物医学文献数据库中发表的IPH风险预测模型相关文献,检索时限为建库至2021年11月1日。2名研究者独立筛选文献、提取资料,并采用PROBAST工具对纳入文献进行质量评价。结果:共纳入12篇文献,包括13个模型,BMI、基线温度、年龄、手术室室温、液体量、麻醉时间和手术时间为模型主要预测因子;10个模型的受试者工作特征曲线下面积(AUC)在建模人群中均>0.7(0.789~0.936),其中3个模型同时报道了验模人群的AUC,均>0.7(0.771~0.914);1篇研究采用内部验证,7篇研究采用外部验证。所有研究均存在一定的偏倚风险,但总体适用性较好。结论:IPH风险预测模型预测性能较好,但偏倚风险较高。应审慎选择已有模型进一步验证,或开展大样本、多病种前瞻性临床研究,构建本土IPH最优风险预测模型,以尽早识别、预防IPH。

Objective:To systematically review the risk prediction model of Inadvertent Perioperative Hypothermia(IPH).Methods:A literature search was performed in the PubMed,Embase,Cochrane Library,CHINAL,Web of Science,CNKI,Wanfang,VIP and Chinese biomedical database to identify IPH risk prediction model relevant studies from inception of databases to November 1,2021.Two researchers independently screened the literatures,extracted the data and evaluated the quality of the included studies based on PROBAST tool.Results:Totally 12 literatures were included,including 13 models.BMI,baseline temperature,age,operating room temperature,fluid volume,anesthesia time and operation time were the main predictors of IPH model.The area under the receiver operating characteristic curve(AUC)of 10 models were>0.7(0.789-0.936)in the modeling population,and the AUC of 3 models in the testing population were>0.7(0.771-0.914).One model was internally validated and seven models were external validated.All studies had certain bias risks,but the overall applicability was relatively good.Conclusion:The IPH risk prediction model has good predictive performance,but high risk of bias.Existing models should be prudently selected for further validation,or we could carry out large sample and multiple disease prospective clinical studies to construct native IPH optimal risk prediction model,in order to identify and prevent IPH as early as possible.