Department of Biostatistics Nagoya University Graduate School of Medicine Nagoya Japan.
Department of Emergency and Critical Care Medicine, Graduate School of Biomedical and Health Sciences Hiroshima University Hiroshima Japan.
J Am Heart Assoc. 2022 Jun 21;11(12):e025048. doi: 10.1161/JAHA.121.025048. Epub 2022 Jun 14.
Background Predicting a spontaneous rhythm change from nonshockable to shockable before hospital arrival in patients with out-of-hospital cardiac arrest can help emergency medical services develop better strategies for prehospital treatment. The aim of this study was to identify predictors of spontaneous rhythm change before hospital arrival in patients with out-of-hospital cardiac arrest and develop a predictive scoring system. Methods and Results We retrospectively reviewed data of eligible patients with out-of-hospital cardiac arrest with an initial nonshockable rhythm registered in a nationwide registry between June 2014 and December 2017. We performed a multivariable analysis using a Cox proportional hazards model to identify predictors of a spontaneous rhythm change, and a ridge regression model for predicting it. The data of 25 804 patients were analyzed (derivation cohort, n=17 743; validation cohort, n=8061). The rhythm change event rate was 4.1% (724/17 743) in the derivation cohort, and 4.0% (326/8061) in the validation cohorts. Age, sex, presence of a witness, initial rhythm, chest compression by a bystander, shock with an automated external defibrillator by a bystander, and cause of the cardiac arrest were all found to be independently associated with spontaneous rhythm change before hospital arrival. Based on this finding, we developed and validated the Rhythm Change Before Hospital Arrival for Nonshockable score. The Harrell's concordance index values of the score were 0.71 and 0.67 in the internal and external validations, respectively. Conclusions Seven factors were identified as predictors of a spontaneous rhythm change from nonshockable to shockable before hospital arrival. We developed and validated a score to predict rhythm change before hospital arrival.
在院外心脏骤停患者到达医院前,预测从非颤动感心律失常到可颤动感心律失常的转变,有助于急救医疗服务制定更好的院前治疗策略。本研究旨在确定院外心脏骤停患者到达医院前自发节律转变的预测因素,并建立预测评分系统。
我们回顾性分析了 2014 年 6 月至 2017 年 12 月期间全国注册登记的初始非颤动感心律失常的院外心脏骤停患者的合格数据。我们使用 Cox 比例风险模型进行多变量分析,以确定自发节律转变的预测因素,并使用岭回归模型进行预测。共分析了 25804 例患者的数据(推导队列,n=17743;验证队列,n=8061)。推导队列中节律转变事件发生率为 4.1%(724/17743),验证队列中为 4.0%(326/8061)。年龄、性别、目击者存在、初始节律、旁观者进行胸外按压、旁观者使用自动体外除颤器进行电击以及心脏骤停的原因均与到达医院前自发节律转变独立相关。基于这一发现,我们开发并验证了非颤动感心律失常到达医院前的节律转变预测评分(Rhythm Change Before Hospital Arrival for Nonshockable score)。该评分在内部和外部验证中的 Harrell 一致性指数值分别为 0.71 和 0.67。
有 7 个因素被确定为到达医院前从非颤动感心律失常到可颤动感心律失常的自发节律转变的预测因素。我们开发并验证了一种预测到达医院前节律转变的评分。