Systematic review of risk prediction models for ventilator-associated pneumonia in mechanically ventilated patients in Intensive Care Unit
温慧 1聂清梅 1孙莉莉 1鲍月月 1张莹莹 1刘培 1曹荣荣1
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作者信息
1. 潍坊市人民医院急诊部,潍坊 261000
折叠
摘要
目的 对ICU呼吸机相关性肺炎的风险预测模型进行系统性的检索和评价,以期为构建更高质量的呼吸机相关性肺炎风险预测模型提供参考.方法 检索中国生物医学文献数据库、万方数据库、中国知网、Embase、PubMed、CINAHL、Web of Science、Cochrane Library 数据库中的相关文献,检索时限为建库至2023年9月30日,限定语种为英文和中文.由2名研究者独立筛选文献和提取数据,并应用PROBAST工具对纳入研究的偏倚风险和适用性进行评价.结果 共纳入15项呼吸机相关性肺炎的风险预测模型构建研究,15个模型的受试者工作特征曲线下面积为0.722～0.982,涉及最多的预测因子是年龄、机械通气时间、ICU住院时间及合并COPD.整体适应性较好,偏倚风险较高,偏倚主要来自样本量不足、未选择合适的数据来源、缺乏模型性能评估和对缺失数据关注不足等.结论 呼吸机相关性肺炎风险预测模型研究偏倚风险较高,正处于发展阶段;未来研究应关注对不同风险评估方法有效性的研究,构建偏倚风险低、预测性能优良、符合我国临床实践实施的风险预测模型.
Abstract
Objective To systematically search and evaluate risk prediction models for ventilator-associated pneumonia(VAP)of ICU in order to provide references for developing higher-quality VAP risk prediction models.Methods Relevant literature was retrieved from databases including China Biology Medicine disc,WanFang data,China National Knowledge Infrastructure,Embase,PubMed,CINAHL,Web of Science,and Cochrane Library.The search timeframe was from the establishment of the databases to September 30,2023,limited to English and Chinese languages.Two researchers independently screened the literature and extracted data,and the PROBAST tool was used to evaluate the risk of bias and applicability of the included studies.Results A total of 15 studies on VAP risk prediction models were included.The area under the receiver operating characteristic curve for the 15 models ranged from 0.722 to 0.982.The most frequently involved predictors were age,duration of mechanical ventilation,ICU length of stay,and comorbid chronic obstructive pulmonary disease.The overall adaptability was good,but the risk of bias was high.The main sources of bias included insufficient sample size,inappropriate data sources,lack of model performance evaluation,and inadequate attention to missing data.Conclusions The risk of bias in studies on VAP risk prediction models is high,indicating that the field is still developing.Future research should focus on the effectiveness of different risk assessment methods to construct models with low bias,excellent predictive performance,and suitability for clinical practice in China.
关键词
重症监护病房/呼吸机相关性肺炎/预测模型/系统评价
Key words
Intensive Care Unit/Ventilator-associated pneumonia/Prediction model/Systematic review
维普
万方数据