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Predictors of viral load and glucose control in persons with a dual diagnosis of HIV and diabetes
Optimal control for both HIV and diabetes (DM) can be difficult, due to the complexity of the treatment required for each. The purpose of this study is to identify factors that contribute to optimal control of both DM and HIV.
Methods
This study was a retrospective review of de-identified electronic medical record (EMR) data obtained from a large urban infectious disease clinic in the Southeast. Inclusion criteria included: HIV+, over 25 years old, on ARV for 6 months and had the diagnosis of DM, identified by ICD-9 codes. Optimal control was described as a non-detectable viral load log (<1.6) and the HgA1c ≤7 (per ADA criteria). Analyses included descriptive statistics and logistic regression. Bivariate analysis determined which variables should be included in the logistic regression.
Results
190 patients fit the criteria. Five variables were entered into the logistic regression model (Over 50, African American race, PI prescription, Insulin Prescription, and weight). The full model was statistically significant, χ2 (5, N = 190) = 28.8, p <.000. Two variables made a statistically significant contribution to the model, Over 50 and over, and PI-based regimen, with an odds ratio of 3.3 and .197 respectively.
Conclusion
Significant predictors of optimal control in persons with dual diagnoses of HIV and DM were age and PI use. Those over age 50 and with a non-PI based regimen had optimal control of both. More research is needed to identify other variables (i.e., social support) that predict control that might not be easily captured by EMR review.
Learning Areas:
Advocacy for health and health educationChronic disease management and prevention
Diversity and culture
Learning Objectives:
List predictors of glucose control in persons with a dual diagnosis of HIV and DM
Describe barriers to adherence in persons with dual diagnosis of HIV and DM
Keyword(s): Adherence
Qualified on the content I am responsible for because: as the PI, I designed the study, analyzed the data, wrote up the findings.
Any relevant financial relationships? No
I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.