Validation of a Clinical Decision Aid to Discontinue In-Hospital Cardiac Arrest Resuscitations
- Carl van Walraven, MD, FRCPC, MSc;
- Alan J. Forster, MD, FRCPC, MSc;
- David C. Parish, MD, MPH;
- Francis C. Dane, PhD;
- K. M. Dinesh Chandra, MD;
- Marcus D. Durham, MA;
- Candace Whaley, BBA;
- Ian Stiell, MD, FRCPC, MSc
- Author Affiliations: Department of Medicine, University of Ottawa, Ottawa, Ontario (Drs van Walraven, Forster, and Stiell); Department of Internal Medicine, Mercer University School of Medicine, Macon, Ga (Drs Parish, Dane, Chandra, Mr Durham, and Ms Whaley); Clinical Epidemiology Unit, Loeb Health Research Institute, Ottawa Hospital, Ottawa, Ontario (Drs van Walraven and Stiell); and Institute for Clinical Evaluative Sciences, Toronto, Ontario (Dr van Walraven).
Abstract
Context Most patients undergoing in-hospital cardiac resuscitation do not survive to hospital discharge. In a previous study, we developed a clinical decision aid for identifying all patients undergoing resuscitation who survived to hospital discharge.
Objective To validate our previously derived clinical decision aid.
Design, Setting, and Participants Data from a large registry of in-hospital resuscitations at a community teaching hospital in Georgia were analyzed to determine whether patients would be predicted to survive to hospital discharge (ie, whether their arrest was witnessed or their initial cardiac rhythm was either ventricular tachycardia or ventricular fibrillation or they regained a pulse during the first 10 minutes of chest compressions). Data from 2181 in-hospital cardiac resuscitation attempts in 1987-1996 involving 1884 pulseless patients were analyzed.
Main Outcome Measure Comparison of predictions based on the decision aid with whether patients were actually discharged alive from the hospital.
Results For 327 resuscitations (15.0%), the patient survived to hospital discharge. For 324 of these resuscitations, the patients were predicted to survive to hospital discharge (sensitivity = 99.1%, 95% confidence interval, 97.1%-99.8%). In 269 resuscitations, patients did not satisfy the decision aid and were predicted to have no chance of being discharged from the hospital. Only 3 of these patients (1.1%) were discharged from the hospital (negative predictive value = 98.9%), none of whom were able to live independently following discharge from the hospital.
Conclusion This decision aid can be used to help physicians identify patients who are extremely unlikely to benefit from continued resuscitative efforts.
