PDF(Pubmed)
Abstract：
BACKGROUND: Many rapid response system (RRS) events are activated using multiple triggers. However, the patterns in which multiple RRS triggers occur together to activate RRS events are unknown. The purpose of this study was to identify these patterns (RRS trigger clusters) and determine their association with outcomes among hospitalized adult patients.
METHODS: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry\'s MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson\'s chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes.
RESULTS: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p < 0.01). All clusters had an increased risk of mortality (p < 0.01).
CONCLUSIONS: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events.
METHODS: RRS events among adult patients from January 2015 to December 2019 in the Get With The Guidelines- Resuscitation registry\'s MET module were examined (n = 134,406). Cluster analysis methods were performed to identify RRS trigger clusters. Pearson\'s chi-squared and ANOVA tests were used to examine differences in patient characteristics across RRS trigger clusters. Multilevel logistic regressions were used to examine the associations between RRS trigger clusters and outcomes.
RESULTS: Six RRS trigger clusters were identified. Predominant RRS triggers for each cluster were: tachypnea, new onset difficulty in breathing, decreased oxygen saturation (Cluster 1); tachypnea, decreased oxygen saturation, staff concern (Cluster 2); respiratory depression, decreased oxygen saturation, mental status changes (Cluster 3); tachycardia, staff concern (Cluster 4); mental status changes (Cluster 5); hypotension, staff concern (Cluster 6). Significant differences in patient characteristics were observed across clusters. Patients in Clusters 3 and 6 had an increased likelihood of in-hospital cardiac arrest (p < 0.01). All clusters had an increased risk of mortality (p < 0.01).
CONCLUSIONS: We discovered six novel RRS trigger clusters with differing relationships to adverse patient outcomes. RRS trigger clusters may prove crucial in clarifying the associations between RRS events and adverse outcomes and aiding in clinician decision-making during RRS events.
摘要：
背景：许多快速反应系统（RRS）事件是使用多个触发器激活的。然而,多个RRS触发器一起发生以激活RRS事件的模式是未知的。这项研究的目的是识别这些模式（RRS触发簇），并确定其与住院成年患者预后的关联。
方法：检查了2015年1月至2019年12月GetWithTheGuidelines-Resuscitation注册表MET模块中成人患者的RRS事件（n=134,406）。采用聚类分析方法识别RRS触发簇。使用Pearson卡方检验和方差分析检验不同RRS触发簇患者特征的差异。使用多水平逻辑回归来检查RRS触发簇与结果之间的关联。
结果：确定了6个RRS触发簇。每个集群的主要RRS触发因素是：呼吸急促，新发作的呼吸困难，血氧饱和度降低(1组);呼吸急促,氧饱和度降低,员工关注(集群2)；呼吸抑制，氧饱和度降低,精神状态变化（第3组）；心动过速，员工关注(第4组)；精神状态变化(第5组)；低血压，工作人员关注(第6组)。在不同的集群中观察到患者特征的显著差异。第3组和第6组患者发生院内心脏骤停的可能性增加(p<0.01)。所有集群的死亡风险增加(p<0.01)。
结论：我们发现了6个新的RRS触发簇，它们与患者的不良结局有不同的关系。RRS触发簇可能对于澄清RRS事件与不良后果之间的关联以及在RRS事件期间帮助临床医生做出决策至关重要。
方法：检查了2015年1月至2019年12月GetWithTheGuidelines-Resuscitation注册表MET模块中成人患者的RRS事件（n=134,406）。采用聚类分析方法识别RRS触发簇。使用Pearson卡方检验和方差分析检验不同RRS触发簇患者特征的差异。使用多水平逻辑回归来检查RRS触发簇与结果之间的关联。
结果：确定了6个RRS触发簇。每个集群的主要RRS触发因素是：呼吸急促，新发作的呼吸困难，血氧饱和度降低(1组);呼吸急促,氧饱和度降低,员工关注(集群2)；呼吸抑制，氧饱和度降低,精神状态变化（第3组）；心动过速，员工关注(第4组)；精神状态变化(第5组)；低血压，工作人员关注(第6组)。在不同的集群中观察到患者特征的显著差异。第3组和第6组患者发生院内心脏骤停的可能性增加(p<0.01)。所有集群的死亡风险增加(p<0.01)。
结论：我们发现了6个新的RRS触发簇，它们与患者的不良结局有不同的关系。RRS触发簇可能对于澄清RRS事件与不良后果之间的关联以及在RRS事件期间帮助临床医生做出决策至关重要。
