Background: Early warning scores (EWS) are widely used to allow early recognition of the deteriorating patient. We aimed to test their ability to predict major deterioration in medical patients.
Methods: Two cohorts were prospectively identified who were admitted to an acute medical admissions unit and to the respiratory unit but not admitted to the intensive care unit (ICU): medical-non ICU and respiratory-non ICU groups. Two further cohorts were retrospectively identified that required ICU admission from these units (medical-ICU and respiratory-ICU groups). Discriminant analysis and receiver operating characteristic curves were used to discriminate between groups, and time relationships were analysed.
Results: Heart rate (HR), respiratory rate (RR) and oxygen saturation (SaO2) were significantly higher in the medical-ICU group than the medical-non ICU group and significantly higher in the respiratory-ICU group than in the respiratorynon ICU group. Discriminant functions incorporating HR, RR and SaO2 performed at least as well as existing EWS systems in predicting ICU admission.
Conclusions: Commonly used physiological parameters and existing EWS systems are useful at identifying sick patients. The discriminant functions described here appear to have a role in this setting but require validation in future studies.
Keywords Early warning scores, intensive care, medicine, risk prediction, scoring systems
Declarat ion of Interests This work was funded by a grant from the Chief Scientist’s Office for Scotland.
