B H Cuthbertson1, M Boroujerdi, G Prescott. 1. Department of Critical Care Medicine, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario, Canada. brian.cuthbertson@sunnybrook.ca
Abstract
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) and respiratory rate (RR) were significantly higher--and oxygen saturation (SaO₂) significantly lower--in the medical-ICU group as compared with the medical non-ICU group, and in the respiratory-ICU group as compared with [corrected] the respiratory-non 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.
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) and respiratory rate (RR) were significantly higher--and oxygen saturation (SaO₂) significantly lower--in the medical-ICU group as compared with the medical non-ICU group, and in the respiratory-ICU group as compared with [corrected] the respiratory-non 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.
Authors: Matthew M Churpek; Trevor C Yuen; Michael T Huber; Seo Young Park; Jesse B Hall; Dana P Edelson Journal: Chest Date: 2011-11-03 Impact factor: 9.410
Authors: Matthew M Churpek; Trevor C Yuen; Christopher Winslow; Ari A Robicsek; David O Meltzer; Robert D Gibbons; Dana P Edelson Journal: Am J Respir Crit Care Med Date: 2014-09-15 Impact factor: 21.405
Authors: Matthew M Churpek; Trevor C Yuen; Seo Young Park; David O Meltzer; Jesse B Hall; Dana P Edelson Journal: Crit Care Med Date: 2012-07 Impact factor: 7.598
Authors: Stephen Gerry; Timothy Bonnici; Jacqueline Birks; Shona Kirtley; Pradeep S Virdee; Peter J Watkinson; Gary S Collins Journal: BMJ Date: 2020-05-20
Authors: Michael J Jones; Christopher P Neal; Wee Sing Ngu; Ashley R Dennison; Giuseppe Garcea Journal: Langenbecks Arch Surg Date: 2017-04-22 Impact factor: 3.445