Article Text

other Versions

PDF
Deriving a prediction rule for short stay admission in trauma patients admitted at a major trauma centre in Australia
  1. Michael M Dinh1,2,
  2. Kendall J Bein1,
  3. Chris M Byrne1,3,
  4. Belinda Gabbe4,
  5. Rebecca Ivers5
  1. 1Emergency Department, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
  2. 2Department of Trauma Services, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
  3. 3Division of Surgery, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia
  4. 4Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, Victoria, Australia
  5. 5Injury Division, The George Institute for Global Health, Sydney, New South Wales, Australia
  1. Correspondence to Dr Michael M Dinh, Emergency Department, Royal Prince Alfred Hospital, Missenden Road, Camperdown, Sydney, NSW 2050 Australia; Dinh.mm{at}gmail.com

Abstract

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.

  • major trauma management
  • Trauma

Statistics from Altmetric.com

Request permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.