Literature DB >> 16627839

Prediction of mortality among emergency medical admissions.

S Goodacre1, J Turner, J Nicholl.   

Abstract

BACKGROUND: The Rapid Acute Physiology Score (RAPS) and Rapid Emergency Medicine Score (REMS) are risk adjustment methods for emergency medical admissions developed for use in audit, research, and clinical practice. Each predicts in hospital mortality using four (RAPS) or six (REMS) variables that can be easily recorded at presentation. We aimed to evaluate the predictive value of REMS, RAPS, and their constituent variables.
METHODS: Age, heart rate, respiratory rate, blood pressure, Glasgow Coma Score (GCS) and oxygen saturation were recorded for 5583 patients who were transported by emergency ambulance, admitted to hospital and then followed up to determine in hospital mortality. The discriminant power of each variable, RAPS, and REMS were compared using the area under the receiver operator characteristic curve (AROCC). Multivariate analysis was used to identify which variables were independent predictors of mortality.
RESULTS: REMS (AROCC 0.74; 95% CI 0.70 to 0.78) was superior to RAPS (AROCC 0.64; 95% CI 0.59 to 0.69) as a predictor of in hospital mortality. Although all the variables, except blood pressure, were associated with mortality, multivariate analysis showed that only age (odds ratio 1.74, p < 0.001), GCS (2.10, p < 0.001), and oxygen saturation (OR 1.36, p = 0.01) were independent predictors. A combination of age, oxygen saturation, and GCS (AROCC 0.80, 95% CI 0.77 to 0.83) was superior to REMS in our population.
CONCLUSION: REMS is a better predictor of mortality in emergency medical admissions than RAPS. Age, GCS, and oxygen saturation appear to be the most useful predictor variables. Inclusion of other variables in risk adjustment scores, particularly blood pressure, may reduce their value.

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Year:  2006        PMID: 16627839      PMCID: PMC2564087          DOI: 10.1136/emj.2005.028522

Source DB:  PubMed          Journal:  Emerg Med J        ISSN: 1472-0205            Impact factor:   2.740


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