Pre-resuscitation factors associated with mortality in 49,130 cases of in-hospital cardiac arrest: a report from the National Registry for Cardiopulmonary Resuscitation

Resuscitation. 2010 Mar;81(3):302-11. doi: 10.1016/j.resuscitation.2009.11.021. Epub 2010 Jan 4.


Aim: 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.

Methods: 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).

Results: 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.

Conclusions: Predictive pre-resuscitation factors may supplement patient-specific information available at bedside to assist in revising resuscitation plans during the patient's hospitalization.

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Aged, 80 and over
  • Cardiopulmonary Resuscitation*
  • Cohort Studies
  • Female
  • Heart Arrest / complications
  • Heart Arrest / mortality*
  • Heart Arrest / therapy*
  • Hospital Mortality*
  • Humans
  • Inpatients*
  • Logistic Models
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Patient Care Planning
  • Predictive Value of Tests
  • Registries
  • Risk Factors
  • Young Adult