Deriving a prediction rule for short stay admission in trauma patients admitted at a major trauma centre in Australia.

INTRODUCTION The aim of this study was to derive and internally validate a prediction rule for short stay admissions (SSAs) in trauma patients admitted to a major trauma centre. METHODS A retrospective study of all trauma activation patients requiring inpatient admission at a single inner city major trauma centre in Australia between 2007 and 2011 was conducted. Logistic regression was used to derive a multivariable model for the outcome of SSA (length of stay ≤2 days excluding deaths or intensive care unit admission). Model discrimination was tested using area under receiver operator characteristic curve analyses and calibration was tested using the Hosmer-Lemeshow test statistic. Validation was performed by splitting the dataset into derivation and validation datasets and further tested using bootstrap cross validation. RESULTS A total of 2593 patients were studied and 30% were classified as SSAs. Important independent predictors of SSA were injury severity score ≤8 (OR 7.8; 95% CI 5.0 to 11.9), Glasgow coma score 14-15 (OR 3.2; 95% CI 1.8 to 5.4), no need for operative intervention (OR 2.2; 95% CI 1.6 to 3.2) and age < 65 years. (OR 1.7; 95% CI 1.2 to 2.6). The overall model had an area under receiver operator characteristic curve of 0.84 (95% CI 0.82 to 0.87) for the derivation dataset. After bootstrap cross validation the area under the curve of the final model was 0.83 (95% CI 0.81 to 0.84). CONCLUSIONS We report a prediction rule that could be used to establish admission criteria for a trauma short stay unit. Further studies are required to prospectively validate the prediction rule.