Marx Tania, Khelifi Nada, Xu Isabelle, Ouellet Laurie, Poirier Annie, Huard Benoit, Mallet Myriam, Bergeron Frédéric, Boissinot Maurice, Bergeron Michel G, Berthelot Simon
Axe Santé des Populations et Pratiques Optimales en Santé, Centre de Recherche du CHU de Québec-Université Laval, Québec, Qc, Canada.
Bibliothèque-Direction des Services-conseils, Université Laval, Québec, Qc, Canada.
Heliyon. 2023 Dec 3;10(1):e23227. doi: 10.1016/j.heliyon.2023.e23227. eCollection 2024 Jan 15.
To identify tools that predict the risk of complications for patients presenting to an outpatient clinic or an emergency department (ED) with influenza-like illness.
We searched Medline, Embase, Cochrane Library and CINAHL from inception to July 2023. We included articles reporting on the derivation or validation of a score or algorithm used to stratify the risk of hospitalization or mortality among patients with influenza-like illness in the ED or outpatient clinic.
Twelve articles reporting on eight scores and six predictive models were identified. For predicting the need for hospitalization, the area under the curve (AUC) of the PMEWS and the CURB-65 ranged respectively from 0.76 to 0.94, and 0.65 to 0.88. The Community Assessment Tool had an AUC of 0.62. For predicting inpatient mortality, AUC was 0.66 for PMEWS and 0.79 for CURB-65, 0.79 for the SIRS criteria and 0.86 for the qSOFA score. Two scores were developed without external validation during the Covid-19 pandemic. The CovHos score and the Canadian Covid discharge score had an AUC ranged from 0.70 to 0.91. The predictive models performed adequately (AUC from 0.76 to 0.92) but will require external validation for clinical use. Tool diversity and study population heterogeneity precluded meta-analysis.
Although the CURB, PMEWS and qSOFA scores appear to predict accurately the risk of complications of influenza-like illness, none were reliable enough to justify their widespread ED use. Refinement of an existing tool or development of a new tool to optimize the management of these patients is needed.
识别可预测门诊或急诊科出现流感样疾病患者并发症风险的工具。
我们检索了从创刊至2023年7月的Medline、Embase、Cochrane图书馆和CINAHL数据库。我们纳入了报告用于对急诊科或门诊流感样疾病患者住院或死亡风险进行分层的评分或算法的推导或验证的文章。
共识别出12篇报告8种评分和6种预测模型的文章。对于预测住院需求,PMEWS和CURB - 65的曲线下面积(AUC)分别为0.76至0.94以及0.65至0.88。社区评估工具的AUC为0.62。对于预测住院死亡率,PMEWS的AUC为0.66,CURB - 65为0.79,全身炎症反应综合征(SIRS)标准为0.79,快速序贯器官衰竭评估(qSOFA)评分为0.86。在新冠疫情期间,有两种评分未进行外部验证就得以开发。CovHos评分和加拿大新冠出院评分的AUC范围为0.70至0.91。这些预测模型表现良好(AUC为0.76至0.92),但临床应用还需外部验证。工具的多样性和研究人群的异质性使得无法进行荟萃分析。
尽管CURB、PMEWS和qSOFA评分似乎能准确预测流感样疾病的并发症风险,但它们都不够可靠,无法证明在急诊科广泛使用的合理性。需要改进现有工具或开发新工具,以优化对这些患者的管理。