Artikel
Differences in the Predictive value of Elixhauser Comorbidity Index and the Charlson Comorbidity in Patients with Hand Infections
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Veröffentlicht: | 6. Februar 2020 |
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Gliederung
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Objectives/Interrogation: The Elixhauser and Charlson Comorbidity indices are two of the most commonly used measures of clinical prognosis. Superiority of one index over another largely depends on the condition or procedure being studied. To date, there is no analysis of a nationwide database comparing the two indices for complications of hand infections.
Methods: The Nationwide Inpatient Sample 2001-2013 database was queried for hand infections using International Classification of Diseases, Ninth Revision (ICD-9) codes for hand infections (10 codes). The Elixhauser (ECI) and Charlson (CCI) comorbidity scores were calculated based on defined sets of ICD-9 codes that have been previously validated. Primary outcomes included mortality, prolonged length of stay (defined as >95 percentile), discharge destination, and postoperative complications. Indices were compared using receiver operating characteristic (ROC) curves. If confidence intervals overlapped, statistical significance was determined using the DeLong method for correlated ROC curves. This is a previously validated, non-parametric comparison used for the calculation of the difference between two AUCs [1].
Results and Conclusions: A total of 316,397 patients were included in this study. The AUC (95% confidence interval) for mortality was 0.710 (0.699-0.720) and 0.726 (0.715-0.736) for the ECI and CCI, respectively. The differences in AUCs were uniformly significant (p<0.05 (Table 1 [Tab. 1], Table 2 [Tab. 2], Figure 1 [Fig. 1]).
There is a significant difference in the predictive value of the ECI and CCI. The CCI was superior in predicting mortality rate in the treatment of hand infections. The ECI was superior in predicting non-routine discharge, prolonged length of stay, and postoperative complications.
References
- 1.
- DeLong ER, DeLong DM, Clarke-Pearson DL. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics. 1988 Sep;44(3):837-45.