Citation

Thompson HJ, Rivara FP, Nathens A, Wang J, Jurkovich GJ, MacKenzie EJ. Ann. Surg. 2010; 252(2): 370-375.

Affiliation

From the *Department of Biobehavioral Nursing and Health Systems, Harborview Injury Prevention and Research Center, The University of Washington School of Nursing, Seattle, WA; daggerDepartment of Pediatrics, Harborview Injury Prevention and Research Center, University of Washington School of Medicine, Seattle, WA; double daggerSystems of Trauma Care Division, St. Michael's Hospital, Ontario, Canada; section signHarborview Injury Prevention & Research Center, University of Washington School of Medicine, Seattle, WA; paragraph signDepartment of Surgery, University of Washington School of Medicine, Seattle, WA; and parallelDepartment of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD.

Copyright

(Copyright © 2010, Lippincott Williams and Wilkins)

DOI

10.1097/SLA.0b013e3181df03d6

PMID

20622665

PMCID

PMC3039002

Abstract

OBJECTIVE:: The aim of this study was to develop and validate a comorbidity index to predict the risk of mortality associated with chronic health conditions following a traumatic injury. SUMMARY BACKGROUND DATA:: Currently available comorbidity adjustment tools do not account for certain chronic conditions, which may influence outcome following traumatic injury or they have not been fully validated for trauma. Controlling for comorbidity in trauma patients is becoming increasingly important as the population ages and elderly patients are more active, as well as to adjust for bias in trauma mortality studies. METHODS:: Cohort study using data from the National Study on the Costs and Outcome of Trauma. Subject pool (N = 4644/Weighted Number = 14,069) was randomly divided in half; the first half of subjects was used to derive the risk scale, the second to validate the instrument. To construct the Mortality Risk Score for Trauma (MoRT), univariate analysis and odds ratios were performed to determine relative risk of mortality at hospital discharge comparing those persons with a comorbid condition to those without. Conditions significantly associated with mortality (P < 0.05) were included in the multivariate model. The variables in the final model were used to build the MoRT. The predictive ability of the MoRT and the Charlson Comorbidity Index (CCI) for discharge and 1-year mortality were estimated using the c-statistic in the validation sample. RESULTS:: Six comorbidity factors were independently associated with the risk of mortality and formed the basis for the MoRT: severe liver disease, myocardial infarction, cerebrovascular disease, cardiac arrhythmias, dementia, and depression. The MoRT had a similar overall discrimination as the CCI for mortality at hospital discharge in injured adults (c-statistic: 0.56 vs. 0.56) although neither by itself performed well. The addition of age and gender improved the predictive ability of the MoRT (0.59; 95% CI: 0.56, 0.62) and the CCI (0.59; 0.56, 0.62). Similar results were seen at 1-year postinjury. The further addition of Injury Severity Score significantly improved the predictive ability of the MoRT (0.77, 95% CI: 0.74, 0.79) and the CCI (0.77, 95% CI: 0.75, 0.80). CONCLUSIONS:: The MoRTs primary advantage over current instruments is its parsimony, containing only 6 items. In the present study, the comorbid conditions found to be predictive of mortality had some overlap with the CCI, but this study identified 2 novel predictors: cardiac arrhythmias and depression. Inclusion and reporting of these items within trauma registries would therefore be an important step to allow further validation and use of the MoRT.

Language: en