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Comparison of measures of comorbidity for predicting disability 12-months post-injury

BACKGROUND: Understanding the factors that impact on disability is necessary to inform trauma care and enable adequate risk adjustment for benchmarking and monitoring. A key consideration is how to adjust for pre-existing conditions when assessing injury outcomes, and whether the inclusion of comorb...

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Autores principales: Gabbe, Belinda J, Harrison, James E, Lyons, Ronan A, Edwards, Elton R, Cameron, Peter A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562274/
https://www.ncbi.nlm.nih.gov/pubmed/23351376
http://dx.doi.org/10.1186/1472-6963-13-30
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author Gabbe, Belinda J
Harrison, James E
Lyons, Ronan A
Edwards, Elton R
Cameron, Peter A
author_facet Gabbe, Belinda J
Harrison, James E
Lyons, Ronan A
Edwards, Elton R
Cameron, Peter A
author_sort Gabbe, Belinda J
collection PubMed
description BACKGROUND: Understanding the factors that impact on disability is necessary to inform trauma care and enable adequate risk adjustment for benchmarking and monitoring. A key consideration is how to adjust for pre-existing conditions when assessing injury outcomes, and whether the inclusion of comorbidity is needed in addition to adjustment for age. This study compared different approaches to modelling the impact of comorbidity, collected as part of the routine hospital episode data, on disability outcomes following orthopaedic injury. METHODS: 12-month Glasgow Outcome Scale – Extended (GOS-E) outcomes for 13,519 survivors to discharge were drawn from the Victorian Orthopaedic Trauma Outcomes Registry, a prospective cohort study of admitted orthopaedic injury patients. ICD-10-AM comorbidity codes were mapped to four comorbidity indices. Cases with a GOS-E score of 7–8 were considered “recovered”. A split dataset approach was used with cases randomly assigned to development or test datasets. Logistic regression models were fitted with “recovery” as the outcome and the performance of the models based on each comorbidity index (adjusted for injury and age) measured using calibration (Hosmer-Lemshow (H-L) statistics and calibration curves) and discrimination (Area under the Receiver Operating Characteristic (AUC)) statistics. RESULTS: All comorbidity indices improved model fit over models with age and injuries sustained alone. None of the models demonstrated acceptable model calibration (H-L statistic p < 0.05 for all models). There was little difference between the discrimination of the indices for predicting recovery: Charlson Comorbidity Index (AUC 0.70, 95% CI: 0.68, 0.71); number of ICD-10 chapters represented (AUC 0.70, 95% CI: 0.69, 0.72); number of six frequent chronic conditions represented (AUC 0.70, 95% CI: 0.69, 0.71); and the Functional Comorbidity Index (AUC 0.69, 95% CI: 0.68, 0.71). CONCLUSIONS: The presence of ICD-10 recorded comorbid conditions is an important predictor of long term functional outcome following orthopaedic injury and adjustment for comorbidity is indicated when assessing risk-adjusted functional outcomes over time or across jurisdictions.
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spelling pubmed-35622742013-02-05 Comparison of measures of comorbidity for predicting disability 12-months post-injury Gabbe, Belinda J Harrison, James E Lyons, Ronan A Edwards, Elton R Cameron, Peter A BMC Health Serv Res Research Article BACKGROUND: Understanding the factors that impact on disability is necessary to inform trauma care and enable adequate risk adjustment for benchmarking and monitoring. A key consideration is how to adjust for pre-existing conditions when assessing injury outcomes, and whether the inclusion of comorbidity is needed in addition to adjustment for age. This study compared different approaches to modelling the impact of comorbidity, collected as part of the routine hospital episode data, on disability outcomes following orthopaedic injury. METHODS: 12-month Glasgow Outcome Scale – Extended (GOS-E) outcomes for 13,519 survivors to discharge were drawn from the Victorian Orthopaedic Trauma Outcomes Registry, a prospective cohort study of admitted orthopaedic injury patients. ICD-10-AM comorbidity codes were mapped to four comorbidity indices. Cases with a GOS-E score of 7–8 were considered “recovered”. A split dataset approach was used with cases randomly assigned to development or test datasets. Logistic regression models were fitted with “recovery” as the outcome and the performance of the models based on each comorbidity index (adjusted for injury and age) measured using calibration (Hosmer-Lemshow (H-L) statistics and calibration curves) and discrimination (Area under the Receiver Operating Characteristic (AUC)) statistics. RESULTS: All comorbidity indices improved model fit over models with age and injuries sustained alone. None of the models demonstrated acceptable model calibration (H-L statistic p < 0.05 for all models). There was little difference between the discrimination of the indices for predicting recovery: Charlson Comorbidity Index (AUC 0.70, 95% CI: 0.68, 0.71); number of ICD-10 chapters represented (AUC 0.70, 95% CI: 0.69, 0.72); number of six frequent chronic conditions represented (AUC 0.70, 95% CI: 0.69, 0.71); and the Functional Comorbidity Index (AUC 0.69, 95% CI: 0.68, 0.71). CONCLUSIONS: The presence of ICD-10 recorded comorbid conditions is an important predictor of long term functional outcome following orthopaedic injury and adjustment for comorbidity is indicated when assessing risk-adjusted functional outcomes over time or across jurisdictions. BioMed Central 2013-01-26 /pmc/articles/PMC3562274/ /pubmed/23351376 http://dx.doi.org/10.1186/1472-6963-13-30 Text en Copyright ©2013 Gabbe et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gabbe, Belinda J
Harrison, James E
Lyons, Ronan A
Edwards, Elton R
Cameron, Peter A
Comparison of measures of comorbidity for predicting disability 12-months post-injury
title Comparison of measures of comorbidity for predicting disability 12-months post-injury
title_full Comparison of measures of comorbidity for predicting disability 12-months post-injury
title_fullStr Comparison of measures of comorbidity for predicting disability 12-months post-injury
title_full_unstemmed Comparison of measures of comorbidity for predicting disability 12-months post-injury
title_short Comparison of measures of comorbidity for predicting disability 12-months post-injury
title_sort comparison of measures of comorbidity for predicting disability 12-months post-injury
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3562274/
https://www.ncbi.nlm.nih.gov/pubmed/23351376
http://dx.doi.org/10.1186/1472-6963-13-30
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