Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study
The mCCI-AI was a statistically significant predictor of 1-year mortality, classifying patients into different risk strata χ<sup>2</sup> (8, N = 1,245) = 30.56 (p = 0.0002). The mCCI-AI was able to discriminate between participants who died and those who survived 73% of the time.
Authors
- Elisa Lee
- Paul Rogers (ORCID: https://orcid.org/0000-0001-9420-1476)
- Joshua Xu (ORCID: https://orcid.org/0000-0001-5313-5847)
- Richardae Araojo (ORCID: https://orcid.org/0000-0002-4457-9427)
- Milena Lolic (ORCID: https://orcid.org/0000-0003-0121-2227)
- Christine Merenda (ORCID: https://orcid.org/0000-0002-0849-8013)
- Jessica A. Reese (ORCID: https://orcid.org/0000-0002-6640-6543)
- Wen Zou
- Ying Zhang (ORCID: https://orcid.org/0000-0001-6945-3743)
- Christine Lee (ORCID: https://orcid.org/0000-0001-9233-8962)
- Dong Wang (ORCID: https://orcid.org/0009-0006-6038-5338)
- Kimberly Malloy
Institutions
- National Center for Toxicological Research (US)
- United States Food and Drug Administration (US)
- Office of Minority Health and Health Equity (US)
- University of Oklahoma Health Sciences Center (US)
Publication Details
- Journal
- Journal of Racial and Ethnic Health Disparities
- Published
- 2024-12-27
- DOI
- https://doi.org/10.1007/s40615-024-02261-0
- Citations
- 1
- Primary Topic
- Chronic Disease Management Strategies
- Type
- article
- Field-Weighted Citation Impact
- 0.39