Posters
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Medical Student
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Poster
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Clinical Science
Abstract Type
Research/Clinical
Abstract
Background: The Rio Grande Valley (RGV) is a demographically unique region that is impoverished and medically underserved. Because of its unique patient population, this community may be at increased risk for bone and joint infections and the morbidity and mortality that follows. The goal of this study was to analyze individuals with osteomyelitis, septic arthritis, and periprosthetic joint infections and determine which infectious bone or joint conditions are most prevalent in the Rio Grande Valley and determine if there were any demographic disparities between the various types of bone and joint infections and healthy individuals. We hypothesized that age and BMI would be significant factors affecting bone and joint infections, specifically older age and higher BMI increasing risk for infection.
Methods: This was a retrospective chart review and data was gathered from the University of Texas Rio Grande Valley (UTRGV) UTHealth electronic database from January 1, 2017 to January 1, 2024. We collected and analyzed medical charts of individuals who were diagnosed with osteomyelitis, septic arthritis, and periprosthetic joint infections using ICD-10 diagnosis codes (ICD-10 codes): osteomyelitis (M86), septic arthritis (M00), periprosthetic joint infection (T84.5 or T84.7). Bivariate analyses and binary logistic regression models were used to statistically analyze the data. All statistical analyses were performed with R statistical software.
Results: Females are significantly less likely to have an infection than males (AOR=0.16, p<0.001), while married individuals also have reduced odds of infection (AOR=0.47, p=0.01) compared to single individuals. Obesity is associated with increased odds of infection (AOR=1.36, p=0.021), whereas overweight and underweight categories do not show significant differences. White individuals have significantly lower odds of infection compared to other races (AOR=0.44, p=0.028). Age at diagnosis slightly increases the odds of infection (AOR=1.02, p<0.001), indicating that older individuals are at a marginally higher risk. Ethnicity (Hispanic vs. non-Hispanic) and marital status categorized as "Other" did not significantly impact the odds.
Conclusion: This study highlights the importance of demographic and health-related factors such as sex, age, BMI, and race in predicting the likelihood of a bone or joint infection. These patient demographics may be targeted as areas of focus when evaluating patients in the RGV to prevent or manage orthopedic infections more effectively and improve the overall orthopedic health of individuals in this region.
Recommended Citation
Martin, Blake C.; Harris, Chloe; and Peiris, Manoj, "Bone and Joint Infections: A Retrospective Chart Review of the Medically Underserved Rio Grande Valley" (2025). Research Symposium. 37.
https://scholarworks.utrgv.edu/somrs/2025/posters/37
Included in
Bone and Joint Infections: A Retrospective Chart Review of the Medically Underserved Rio Grande Valley
Background: The Rio Grande Valley (RGV) is a demographically unique region that is impoverished and medically underserved. Because of its unique patient population, this community may be at increased risk for bone and joint infections and the morbidity and mortality that follows. The goal of this study was to analyze individuals with osteomyelitis, septic arthritis, and periprosthetic joint infections and determine which infectious bone or joint conditions are most prevalent in the Rio Grande Valley and determine if there were any demographic disparities between the various types of bone and joint infections and healthy individuals. We hypothesized that age and BMI would be significant factors affecting bone and joint infections, specifically older age and higher BMI increasing risk for infection.
Methods: This was a retrospective chart review and data was gathered from the University of Texas Rio Grande Valley (UTRGV) UTHealth electronic database from January 1, 2017 to January 1, 2024. We collected and analyzed medical charts of individuals who were diagnosed with osteomyelitis, septic arthritis, and periprosthetic joint infections using ICD-10 diagnosis codes (ICD-10 codes): osteomyelitis (M86), septic arthritis (M00), periprosthetic joint infection (T84.5 or T84.7). Bivariate analyses and binary logistic regression models were used to statistically analyze the data. All statistical analyses were performed with R statistical software.
Results: Females are significantly less likely to have an infection than males (AOR=0.16, p<0.001), while married individuals also have reduced odds of infection (AOR=0.47, p=0.01) compared to single individuals. Obesity is associated with increased odds of infection (AOR=1.36, p=0.021), whereas overweight and underweight categories do not show significant differences. White individuals have significantly lower odds of infection compared to other races (AOR=0.44, p=0.028). Age at diagnosis slightly increases the odds of infection (AOR=1.02, p<0.001), indicating that older individuals are at a marginally higher risk. Ethnicity (Hispanic vs. non-Hispanic) and marital status categorized as "Other" did not significantly impact the odds.
Conclusion: This study highlights the importance of demographic and health-related factors such as sex, age, BMI, and race in predicting the likelihood of a bone or joint infection. These patient demographics may be targeted as areas of focus when evaluating patients in the RGV to prevent or manage orthopedic infections more effectively and improve the overall orthopedic health of individuals in this region.
