Prediction of mortality among emergency medical admissions

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.

Mortality in out-of-hours emergency medical admissions – more than just a weekend effect

“…Several studies have shown that hospital mortality can be predicted on the basis of illness severity scores calculated at the time of admission, either in the emergency department, 18,19 an assessment unit 20,21 or a medical ward. 22 None of these studies looked at whether the average early warning scores varied according to time or day of admission; although such scores are somewhat blunt tools, this analysis may be a useful next step to help our understanding of the variation in mortality we have observed.…”

Evaluation of triage methods used to select patients with suspected pandemic influenza for hospital admission: cohort study

“…25,34 Little literature exists on risk assessment of undifferentiated emergency patients, and what there is concentrates on mortality risk. [35][36][37] It appears from the international experience that obesity, 17 pre-existing comorbidity 19 and pregnancy 17,38 convey a worse prognosis during pandemic influenza infection. A single study of bacterial pneumonic superinfection in influenza from Taiwan identified shock, respiratory rate of over 24 breaths/minute, acidosis, raised creatinine and a pneumonia severity index of class IV or V as indicators of poor prognosis.…”

Comparison of APACHE II and three abbreviated APACHE II scores for predicting outcome among emergency trauma patients

“…However, heart rate and blood pressure as predictors are inconsistent in different studies. 4,13,19 One possible important explanation is that timing and quality of out-hospital resuscitation would influence these variables. Additionally, the finding that only GCS and HR predicted mortality may help understand why the scores have similar discriminatory power as both sub-components take part in each score.…”