Background: Complex infectious disease processes, including serious musculoskeletal infections, may result in differential health disparities at successive phases in a clinical course. Previously, our group proposed the application of cyclical continuum modeling to the study of these complex clinical processes.
Methods: Using a retrospective cohort of over 1600 adult patients in the University of New Mexico Health System with serious musculoskeletal infections, including septic arthritis, osteomyelitis, and/or infectious myositis, we performed preliminary proof-of-concept cyclical continuum modeling analyses. The experiences of patients in different racial/ethnic groups were compared using a logistic regression model adjusted for age and sex. Outcomes in multiple categories were reviewedprimary risk factors for limb loss (e.g., diabetes mellitus and peripheral vascular disease), secondary risk factors for limb loss (e.g., osteomyelitis and multiple musculoskeletal infection types), and outcomes or complications of infection (e.g., sepsis, antibiotic use, and amputation). Preliminary cyclical visualization tools were used to demonstrate differences in health outcomes across racial/ethnic groups.
Results: Although significantly younger than other members of the cohort, American Indian/Alaskan Native patients (17.7% of cohort) had high odds of primary and secondary risk factors yet low odds of amputation. Hispanic patients (40.2% of cohort) tended to have high odds of primary and secondary factors as well as amputation. Black non-Hispanic patients (2.6% of cohort) had high odds of primary risk factors and low odds of osteomyelitis, yet Black non-Hispanic patients were most likely to undergo an amputation. Initial cyclical visualization techniques showed promise for comparing the relative distribution of racial/ethnic disparities across the clinical course.
Conclusion: Health disparities encountered by patients with serious musculoskeletal infections may be studied using a process-based approach. Future development of cyclical continuum modeling methods should focus on applications of both relative and absolute epidemiological measures and cyclical visualization methods.
K. Page, None