Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team

David A. Harrison*, Krishna Patel, Edel Nixon, Jasmeet Soar, Gary B. Smith, Carl Gwinnutt, Jerry P. Nolan, Kathryn M. Rowan

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

34 Citations (Scopus)

Abstract

Aim: The National Cardiac Arrest Audit (NCAA) is the UK national clinical audit for in-hospital cardiac arrest. To make fair comparisons among health care providers, clinical indicators require case mix adjustment using a validated risk model. The aim of this study was to develop and validate risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team in UK hospitals. Methods: Risk models for two outcomes-return of spontaneous circulation (ROSC) for greater than 20. min and survival to hospital discharge-were developed and validated using data for in-hospital cardiac arrests between April 2011 and March 2013. For each outcome, a full model was fitted and then simplified by testing for non-linearity, combining categories and stepwise reduction. Finally, interactions between predictors were considered. Models were assessed for discrimination, calibration and accuracy. Results: 22,479 in-hospital cardiac arrests in 143 hospitals were included (14,688 development, 7791 validation). The final risk model for ROSC. >. 20. min included: age (non-linear), sex, prior length of stay in hospital, reason for attendance, location of arrest, presenting rhythm, and interactions between presenting rhythm and location of arrest. The model for hospital survival included the same predictors, excluding sex. Both models had acceptable performance across the range of measures, although discrimination for hospital mortality exceeded that for ROSC. >. 20. min (c index 0.81 versus 0.72). Conclusions: Validated risk models for ROSC. >. 20. min and hospital survival following in-hospital cardiac arrest have been developed. These models will strengthen comparative reporting in NCAA and support local quality improvement.

Original languageEnglish
Pages (from-to)993-1000
Number of pages8
JournalResuscitation
Volume85
Issue number8
DOIs
Publication statusPublished - Aug 2014

Bibliographical note

Funding Information:
This project was supported by internal funding from the Resuscitation Council (UK) and the Intensive Care National Audit & Research Centre, and by the National Institute for Health Research Health Services and Delivery Research (NIHR HS&DR) programme (project number 09/2000/65). Visit the HS&DR website for more information. The views and opinions expressed therein are those of the authors and do not necessarily reflect those of the HS&DR Programme, NIHR, NHS or the Department of Health.

Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.

Keywords

  • Cardiopulmonary resuscitation
  • Heart arrest
  • Hospital mortality
  • Models
  • Risk adjustment
  • Statistical

Fingerprint

Dive into the research topics of 'Development and validation of risk models to predict outcomes following in-hospital cardiac arrest attended by a hospital-based resuscitation team'. Together they form a unique fingerprint.

Cite this