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

Michael M Dinh, Kendall J Bein, Chris Byrne, Belinda Jane Gabbe, Rebecca Ivers

Research output: Contribution to journalArticleResearchpeer-review

2 Citations (Scopus)

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.
Original languageEnglish
Pages (from-to)263 - 267
Number of pages5
JournalEmergency Medicine Journal
Volume31
Issue number4
DOIs
Publication statusPublished - 2014

Cite this

Dinh, Michael M ; Bein, Kendall J ; Byrne, Chris ; Gabbe, Belinda Jane ; Ivers, Rebecca. / Deriving a prediction rule for short stay admission in trauma patients admitted at a major trauma centre in Australia. In: Emergency Medicine Journal. 2014 ; Vol. 31, No. 4. pp. 263 - 267.
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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.",
author = "Dinh, {Michael M} and Bein, {Kendall J} and Chris Byrne and Gabbe, {Belinda Jane} and Rebecca Ivers",
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Deriving a prediction rule for short stay admission in trauma patients admitted at a major trauma centre in Australia. / Dinh, Michael M; Bein, Kendall J; Byrne, Chris; Gabbe, Belinda Jane; Ivers, Rebecca.

In: Emergency Medicine Journal, Vol. 31, No. 4, 2014, p. 263 - 267.

Research output: Contribution to journalArticleResearchpeer-review

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T1 - Deriving a prediction rule for short stay admission in trauma patients admitted at a major trauma centre in Australia

AU - Dinh, Michael M

AU - Bein, Kendall J

AU - Byrne, Chris

AU - Gabbe, Belinda Jane

AU - Ivers, Rebecca

PY - 2014

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N2 - 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.

AB - 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.

UR - http://www.ncbi.nlm.nih.gov/pubmed/23407379

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EP - 267

JO - Emergency Medicine Journal

JF - Emergency Medicine Journal

SN - 1472-0205

IS - 4

ER -