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Prediction modelling for trauma using comorbidity and ‘true’ 30-day outcome

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Název: Prediction modelling for trauma using comorbidity and ‘true’ 30-day outcome
Autoři: Bouamra, Omar, Jacques, Richard, Edwards, Antoinette, Yates, David W, Lawrence, Thomas, Jenks, Tom, Woodford, Maralyn, Lecky, Fiona
Zdroj: Bouamra, O, Jacques, R, Edwards, A, Yates, D W, Lawrence, T, Jenks, T, Woodford, M & Lecky, F 2015, 'Prediction modelling for trauma using comorbidity and 'true' 30-day outcome', Emergency medicine journal : EMJ, vol. 32, no. 12, pp. 933-938. https://doi.org/10.1136/emermed-2015-205176
Informace o vydavateli: BMJ, 2015.
Rok vydání: 2015
Témata: Adult, Male, Comorbidity, Outcome Assessment (Health Care), Young Adult, 03 medical and health sciences, Injury Severity Score, 0302 clinical medicine, Models, Outcome Assessment, Health Care, 80 and over, Humans, Wounds and Injuries/classification, Prospective Studies, Aged, Aged, 80 and over, Models, Statistical, United Kingdom/epidemiology, Age Factors, Reproducibility of Results, Statistical, Middle Aged, Prognosis, United Kingdom, 3. Good health, Logistic Models, Area Under Curve, Wounds and Injuries, Female
Popis: BackgroundPrediction models for trauma outcome routinely control for age but there is uncertainty about the need to control for comorbidity and whether the two interact. This paper describes recent revisions to the Trauma Audit and Research Network (TARN) risk adjustment model designed to take account of age and comorbidities. In addition linkage between TARN and the Office of National Statistics (ONS) database allows patient's outcome to be accurately identified up to 30 days after injury. Outcome at discharge within 30 days was previously used.MethodsProspectively collected data between 2010 and 2013 from the TARN database were analysed. The data for modelling consisted of 129 786 hospital trauma admissions. Three models were compared using the area under the receiver operating curve (AuROC) for assessing the ability of the models to predict outcome, the Akaike information criteria to measure the quality between models and test for goodness-of-fit and calibration. Model 1 is the current TARN model, Model 2 is Model 1 augmented by a modified Charlson comorbidity index and Model 3 is Model 2 with ONS data on 30 day outcome.ResultsThe values of the AuROC curve for Model 1 were 0.896 (95% CI 0.893 to 0.899), for Model 2 were 0.904 (0.900 to 0.907) and for Model 3 0.897 (0.896 to 0.902). No significant interaction was found between age and comorbidity in Model 2 or in Model 3.ConclusionsThe new model includes comorbidity and this has improved outcome prediction. There was no interaction between age and comorbidity, suggesting that both independently increase vulnerability to mortality after injury.
Druh dokumentu: Article
Popis souboru: application/pdf
Jazyk: English
ISSN: 1472-0213
1472-0205
DOI: 10.1136/emermed-2015-205176
Přístupová URL adresa: http://eprints.whiterose.ac.uk/91235/1/Prediction%20Modelling%20for%20Trauma%20using%20Comorbidity%20and%20True%2030-Day%20Outcome.pdf
https://pubmed.ncbi.nlm.nih.gov/26493123
Přístupové číslo: edsair.doi.dedup.....78536f730abf062d1d873b76086d6b28
Databáze: OpenAIRE
Popis
Abstrakt:BackgroundPrediction models for trauma outcome routinely control for age but there is uncertainty about the need to control for comorbidity and whether the two interact. This paper describes recent revisions to the Trauma Audit and Research Network (TARN) risk adjustment model designed to take account of age and comorbidities. In addition linkage between TARN and the Office of National Statistics (ONS) database allows patient's outcome to be accurately identified up to 30 days after injury. Outcome at discharge within 30 days was previously used.MethodsProspectively collected data between 2010 and 2013 from the TARN database were analysed. The data for modelling consisted of 129 786 hospital trauma admissions. Three models were compared using the area under the receiver operating curve (AuROC) for assessing the ability of the models to predict outcome, the Akaike information criteria to measure the quality between models and test for goodness-of-fit and calibration. Model 1 is the current TARN model, Model 2 is Model 1 augmented by a modified Charlson comorbidity index and Model 3 is Model 2 with ONS data on 30 day outcome.ResultsThe values of the AuROC curve for Model 1 were 0.896 (95% CI 0.893 to 0.899), for Model 2 were 0.904 (0.900 to 0.907) and for Model 3 0.897 (0.896 to 0.902). No significant interaction was found between age and comorbidity in Model 2 or in Model 3.ConclusionsThe new model includes comorbidity and this has improved outcome prediction. There was no interaction between age and comorbidity, suggesting that both independently increase vulnerability to mortality after injury.
ISSN:14720213
14720205
DOI:10.1136/emermed-2015-205176