A Validated Prediction Tool for Initial Survivors of In-Hospital Cardiac Arrest

Authors:
  • RBRobert A. Berg
    Robert A. Berg
  • YLYan Li
    Yan Li
Open Access
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Abstract
In-hospital cardiac arrests are common and associated with poor survival, despite immense efforts to treat them. To improve prognostication, several risk models have been developed over the past 2 decades,1-3 but for several reasons these have had limited clinical application. First, prior models were developed in all patients with in-hospital cardiac arrest, including those who never survive the initial event. Because cardiac arrests are medical emergencies in which rapid decision-making is required, these models are impractical to use in the midst of an acute resuscitation. After the resuscitation, they are unlikely to be valid, because survival rates and patient characteristics among those who are successfully resuscitated differ significantly from those of the initial sample of patients with cardiac arrest in whom these models were developed. Another concern is that earlier models examined survival to discharge and did not routinely consider neurological status, which is very important to patients and families. Finally, most studies have not translated their models into meaningful and valid tools that can assist with clinical prognostication at the bedside.

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