Predicting In-Hospital Mortality in Elderly Patients With Cervical Spine Fractures

A Comparison of the Charlson and Elixhauser Comorbidity Measures

Abstract

Study Design. 

Retrospective analysis of nationally representative data collected for the National Hospital Discharge Survey.

Objective. 

To compare the performance of the Charlson and Elixhauser comorbidity-based measures for predicting in-hospital mortality after cervical spine fractures.

Summary of Background Data. 

Mortality occurring as a consequence of cervical spine fractures is very high in the elderly. The Charlson comorbidity measure has been associated with an increased risk of mortality, but its predictive accuracy has yet to be compared with the more recent and increasingly used Elixhauser measure.

Methods. 

Using the National Hospital Discharge Survey for the years 1990 through 2007, we identified all patients aged 65 years or older hospitalized with a diagnosis of cervical spine fracture. The association of each Charlson and Elixhauser comorbidity with mortality was assessed in bivariate analysis using χ² tests. Two main multivariable logistic regression models were constructed, with in-hospital mortality as the dependent variable and 1 of the 2 comorbidity-based measures (as well as age, sex, and year of admission) as independent variables. A base model that included only age, sex, and year of admission was also evaluated. The discriminative ability of the models was quantified using the area under the receiver operating characteristic curve (AUC).

Results. 

Among an estimated 111,564 patients admitted for cervical spine fractures, 7.6% died in the hospital. Elixhauser comorbidity adjustment provided better prediction of in-hospital case mortality (AUC = 0.852, 95% confidence interval: 0.848–0.856) than the Charlson model (AUC = 0.823, 95% confidence interval: 0.819–0.828) and the base model with no comorbidities (AUC = 0.785, 95% confidence interval: 0.781–0.790). In terms of relative improvement in predictive ability, the Elixhauser model performed 43% better than the Charlson model.

Conclusion. 

The Elixhauser comorbidity risk adjustment method performed numerically better than the widely used Charlson measure in predicting in-hospital mortality after cervical spine fractures.

Level of Evidence: N/A

In Brief

We assessed and compared the discriminative ability of the Charlson and Elixhauser comorbidity measures for predicting in-hospital mortality in elderly patients admitted with cervical spine fractures. The Elixhauser comorbidity risk adjustment method performed numerically better than the widely used Charlson measure in predicting inpatient death after cervical spine fractures.