Malycha James, Bonnici Tim, Sebekova Katarina, Petrinic Tatjana, Young Duncan, Watkinson Peter
Kadoorie Centre for Critical Care Research and Education, John Radcliffe Hospital, Level 3, Headley Way, Oxford, OX3 9DU, UK.
University of Oxford, Bodleian Health Care Libraries, Academic Centre, John Radcliffe Hospital, Level 3, Headley Way, Oxford, OX3 9DU, UK.
Syst Rev. 2017 Mar 28;6(1):67. doi: 10.1186/s13643-017-0456-0.
Failure to promptly identify deterioration in hospitalised patients is associated with delayed admission to intensive care units (ICUs) and poor outcomes. Existing vital sign-based Early Warning Score (EWS) algorithms do not have a sufficiently high positive predictive value to be used for automated activation of an ICU outreach team. Incorporating additional patient data might improve the predictive power of EWS algorithms; however, it is currently not known which patient data (or variables) are most predictive of ICU admission. We describe the protocol for a systematic review of variables associated with ICU admission.
METHODS/DESIGN: MEDLINE, EMBASE, CINAHL and the Cochrane Library, including Cochrane Database of Systematic Reviews and the Cochrane Central Register of Controlled Trials (CENTRAL) will be searched for studies that assess the association of routinely recorded variables associated with subsequent unplanned ICU admission. Only studies involving adult patients admitted to general ICUs will be included. We will extract data relating to the statistical association between ICU admission and predictor variables, the quality of the studies and the generalisability of the findings.
The results of this review will aid the development of future models which predict the risk of unplanned ICU admission.
PROSPERO: CRD42015029617.
未能及时识别住院患者病情恶化与重症监护病房(ICU)延迟收治及不良预后相关。现有的基于生命体征的早期预警评分(EWS)算法阳性预测值不够高,无法用于自动启动ICU外展团队。纳入更多患者数据可能会提高EWS算法的预测能力;然而,目前尚不清楚哪些患者数据(或变量)对ICU收治最具预测性。我们描述了一项关于与ICU收治相关变量的系统评价方案。
方法/设计:将检索MEDLINE、EMBASE、CINAHL和Cochrane图书馆,包括Cochrane系统评价数据库和Cochrane对照试验中心注册库(CENTRAL),以查找评估与随后计划外ICU收治相关的常规记录变量之间关联的研究。仅纳入涉及入住普通ICU成年患者的研究。我们将提取与ICU收治和预测变量之间的统计学关联、研究质量及研究结果可推广性相关的数据。
本评价结果将有助于未来预测计划外ICU收治风险模型的开发。
PROSPERO:CRD42015029617。