Yale University School of Medicine, New Haven, CT, United States.
Resuscitation. 2010 Mar;81(3):302-11. doi: 10.1016/j.resuscitation.2009.11.021. Epub 2010 Jan 4.
To evaluate key pre-arrest factors and their collective ability to predict post-cardiopulmonary arrest mortality. CPR is often initiated indiscriminately after in-hospital cardiopulmonary arrest. Improved understanding of pre-arrest factors associated with mortality may inform advance care planning.
A cohort of 49,130 adults who experienced pulseless cardiopulmonary arrest from January 2000 to September 2004 was obtained from 366 US hospitals participating in the National Registry for Cardiopulmonary Resuscitation (NRCPR). Logistic regression with bootstrapping was used to model in-hospital mortality, which included those discharged in unfavorable and severely worsened neurologic state (Cerebral Performance Category >/=3).
Overall in-hospital mortality was 84.1%. Advanced age, black race, non-cardiac, non-surgical illness category, pre-existing malignancy, acute stroke, trauma, septicemia, hepatic insufficiency, general floor or Emergency Department location, and pre-arrest use of vasopressors or assisted/mechanical ventilation were independently predictive of in-hospital mortality. Retained peri-arrest factors including cardiac monitoring, and shockable initial pulseless rhythms, were strongly associated with survival. The validation model's AUROC curve (0.77) revealed fair performance.
Predictive pre-resuscitation factors may supplement patient-specific information available at bedside to assist in revising resuscitation plans during the patient's hospitalization.
评估关键的心脏骤停前因素及其对心脏骤停后死亡率的综合预测能力。心肺复苏(CPR)通常在院内心脏骤停后不加区分地进行。更好地了解与死亡率相关的心脏骤停前因素可能有助于预先制定护理计划。
从 2000 年 1 月至 2004 年 9 月参与国家心肺复苏登记处(NRCPR)的 366 家美国医院获得了 49,130 名经历无脉性心肺骤停的成年患者队列。使用带有自举的逻辑回归对院内死亡率进行建模,包括出院时神经功能状态不良和严重恶化(脑功能分类≥3)的患者。
总体院内死亡率为 84.1%。高龄、黑种人、非心脏、非手术疾病类别、预先存在的恶性肿瘤、急性中风、创伤、败血症、肝功能不全、普通病房或急诊室位置,以及心脏骤停前使用血管加压素或辅助/机械通气是院内死亡率的独立预测因素。保留的心脏骤停前因素,包括心脏监测和可除颤的初始无脉节律,与生存密切相关。验证模型的 AUROC 曲线(0.77)显示出良好的性能。
预测性的心脏骤停前因素可以补充床边患者特定信息,以帮助修订患者住院期间的复苏计划。