ArticleBMJ open2015
The Deyo-Charlson and Elixhauser-van Walraven Comorbidity Indices as predictors of mortality in critically ill patients.
Article in BMJ open, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 4 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
68 citing papers in PubMed, 4 syntheses or guidelines pooled it.
- A Systematic Review and Multilevel Regression Analysis Reveals the Comorbidity Prevalence in Cancer.Cancer research · 2023Pooled it
- Vitamins C and D and COVID-19 Susceptibility, Severity and Progression: An Evidence Based Systematic Review.Medicina (Kaunas, Lithuania) · 2022Pooled it
- Proposing a "Brain Health Checkup (BHC)" as a Global Potential "Standard of Care" to Overcome Reward Dysregulation in Primary Care Medicine: Coupling Genetic Risk Testing and Induction of "Dopamine Homeostasis".International journal of environmental research and public health · 2022Pooled it
- Clinical and laboratory findings of COVID-19: A systematic review and meta-analysis.Journal of the Formosan Medical Association = Taiwan yi zhi · 2021Pooled it
- Trajectories of antidepressant dispensing among privately insured transgender people in the United States.Scientific reports · 2026Article
- Comparative performance of APACHE II, SOFA, and Charlson Comorbidity Index in sepsis mortality prediction.Biomolecules & biomedicine · 2026Observational
- Fluid Balance is Associated with Differential Effects on Respiratory Failure between Critically Ill and Noncritically Ill Adults with SARS-CoV-2: a Retrospective Cohort Study.Shock (Augusta, Ga.) · 2026Article
- Nicotine dependence among critically ill COVID-19 patients: A population-based cohort study.PloS one · 2026Article
- Improving containment and prevention strategies using a patient transfer network representative of patients with multidrug-resistant organisms.Infection control and hospital epidemiology · 2025Article
- Considerations for selecting and implementing comorbidity indices when using secondary data sources: a guide for health researchers.International journal of population data science · 2025Review
- Factors influencing the length of hospital stay of people experiencing homelessness.Frontiers in public health · 2025Article
- Article
- The value of Age-adjusted Charlson and Elixhauser-Van Walraven comorbidity index in predicting prognosis for patients undergoing heart valve surgery.Journal of cardiothoracic surgery · 2024Article
- Mechanical Ventilation in Older Adults With Dementia: Opportunities to Promote Goal-Concordant Care.Journal of pain and symptom management · 2024Article
- Article
- Survival and treatment in older patients with ewing sarcoma: an analysis of the national cancer database.European journal of medical research · 2024Article
- Treatment at Twilight: An Analysis of Therapy Patterns and Outcomes in Adults 80 Years and Older With Advanced or Metastatic NSCLC.JTO clinical and research reports · 2023Article
- Article
- Association of Glucose-6-Phosphate Dehydrogenase Deficiency With Outcomes in US Veterans With COVID-19.JAMA network open · 2023Article
- Age-adjusted Charlson Comorbidity Index as effective predictor for in-hospital mortality of patients with cardiac arrest: a retrospective study.BMC emergency medicine · 2023Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
objectivesOur primary objective was to compare the utility of the Deyo-Charlson Comorbidity Index (DCCI) and Elixhauser-van Walraven Comorbidity Index (EVCI) to predict mortality in intensive care unit (ICU) patients.
settingObservational study of 2 tertiary academic centres located in Boston, Massachusetts.
participantsThe study cohort consisted of 59,816 patients from admitted to 12 ICUs between January 2007 and December 2012. PRIMARY AND SECONDARY OUTCOME: For the primary analysis, receiver operator characteristic curves were constructed for mortality at 30, 90, 180, and 365 days using the DCCI as well as EVCI, and the areas under the curve (AUCs) were compared. Subgroup analyses were performed within different types of ICUs. Logistic regression was used to add age, race and sex into the model to determine if there was any improvement in discrimination.
resultsAt 30 days, the AUC for DCCI versus EVCI was 0.65 (95% CI 0.65 to 0.67) vs 0.66 (95% CI 0.65 to 0.66), p=0.02. Discrimination improved at 365 days for both indices (AUC for DCCI 0.72 (95% CI 0.71 to 0.72) vs AUC for EVCI 0.72 (95% CI 0.72 to 0.72), p=0.46). The DCCI and EVCI performed similarly across ICUs at all time points, with the exception of the neurosciences ICU, where the DCCI was superior to EVCI at all time points (1-year mortality: AUC 0.73 (95% CI 0.72 to 0.74) vs 0.68 (95% CI 0.67 to 0.70), p=0.005). The addition of basic demographic information did not change the results at any of the assessed time points.
conclusionsThe DCCI and EVCI were comparable at predicting mortality in critically ill patients. The predictive ability of both indices increased when assessing long-term outcomes. Addition of demographic data to both indices did not affect the predictive utility of these indices. Further studies are needed to validate our findings and to determine the utility of these indices in clinical practice.
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