Ann Epidemiol. 2023 Sep 22:S1047-2797(23)00181-3. doi: 10.1016/j.annepidem.2023.09.007. Online ahead of print.
ABSTRACT
BACKGROUND: We developed a predictive model to estimate the risk of sub-optimal HIV clinical outcomes among people living with HIV and mental illness or substance use disorders in Texas.
METHODS: The Texas Medical Monitoring Project (MMP) data obtained from June 2015 to May 2020 was used to develop and internally validate the predictive model. Univariate descriptive and bivariate inferential statistics were performed to describe the characteristics of the study population and unadjusted associations with HIV clinical outcomes. Multivariable logistic regression was used to develop the prediction model. Internal validation was performed using the bootstrap method.
RESULTS: A total of 518 respondents aged 18 years and above, representing 27,255 adults living with HIV and mental illness or substance use disorders in Texas were included. Most participants were male (77.04%), less than 50 years of age (56.98%), had mild diagnosed mental illness and substance use disorder (56.59%). The risk predictive model contained 8 predictors, which together yielded an AUC of 0.727. Nonretention in care appeared to be the strongest predictor for having suboptimal HIV clinical outcome (aOR = 3.27; 95% CI = 1.45, 7.42).
CONCLUSION: The predictive model had good discrimination between persons at risk of poor HIV clinical outcomes and those not at risk.
PMID:37742879 | DOI:10.1016/j.annepidem.2023.09.007
