PT - JOURNAL ARTICLE AU - Lorenzo Azzalini AU - Malorie Chabot-Blanchet AU - Danielle A. Southern AU - Anna Nozza AU - Stephen B. Wilton AU - Michelle M. Graham AU - Guillaume Marquis Gravel AU - Jean-Pierre Bluteau AU - Jean-Lucien Rouleau AU - Marie-Claude Guertin AU - E. Marc Jolicoeur TI - A disease-specific comorbidity index for predicting mortality in patients admitted to hospital with a cardiac condition AID - 10.1503/cmaj.181186 DP - 2019 Mar 18 TA - Canadian Medical Association Journal PG - E299--E307 VI - 191 IP - 11 4099 - http://www.cmaj.ca/content/191/11/E299.short 4100 - http://www.cmaj.ca/content/191/11/E299.full SO - CMAJ2019 Mar 18; 191 AB - BACKGROUND: Comorbidity indexes derived from administrative databases are essential tools of research in global health. We sought to develop and validate a novel cardiac-specific comorbidity index, and to compare its accuracy with the generic Charlson–Deyo and Elixhauser comorbidity indexes.METHODS: We derived the cardiac-specific comorbidity index from consecutive patients who were admitted to hospital at a tertiary-care cardiology hospital in Quebec. We used logistic regression analysis and incorporated age, sex and 22 clinically relevant comorbidities to build the index. We compared the cardiac-specific comorbidity index with refitted Charlson–Deyo and Elixhauser comorbidity indexes using the C-statistic and net reclassification improvement to predict in-hospital death, and the Akaike information criterion to predict length of stay. We validated our findings externally in an independent cohort obtained from a provincial registry of coronary disease in Alberta.RESULTS: The novel cardiac-specific comorbidity index outperformed the refitted generic Charlson–Deyo and Elixhauser comorbidity indexes for predicting in-hospital mortality in the derivation population (n = 10 137): C-statistic 0.95 (95% confidence interval [CI] 0.94–0.9) v. 0.81 (95% CI 0.77–0.84) and 0.86 (95% CI 0.82–0.89), respectively. In the validation population (n = 17 877), the cardiac-specific comorbidity index was similarly better: C-statistic 0.92 (95% CI 0.89–0.94) v. 0.76 (95% CI 0.71–0.81) and 0.82 (95% CI 0.78–0.86), respectively, and also numerically outperformed the Charlson–Deyo and Elixhauser comorbidity indexes for predicting 1-year mortality (C-statistic 0.78 [95% CI 0.76–0.80] v. 0.75 [95% CI 0.73–0.77] and 0.77 [95% CI 0.75–0.79], respectively). Similarly, the cardiac-specific comorbidity index showed better fit for the prediction of length of stay. The net reclassification improvement using the cardiac-specific comorbidity index for the prediction of death was 0.290 compared with the Charlson–Deyo comorbidity index and 0.192 compared with the Elixhauser comorbidity index.INTERPRETATION: The cardiac-specific comorbidity index predicted in-hospital and 1-year death and length of stay in cardiovascular populations better than existing generic models. This novel index may be useful for research of cardiology outcomes performed with large administrative databases.