期刊
OPEN FORUM INFECTIOUS DISEASES
卷 9, 期 10, 页码 -出版社
OXFORD UNIV PRESS INC
DOI: 10.1093/ofid/ofac487
关键词
multidrug resistance; HIV; Enterobacterales; gram-negative; machine learning
资金
- University of North Carolina at Chapel Hill Center for AIDS Research, a National Institutes of Health [P30 AI50410]
- National Center for Advancing Translational Sciences, National Institutes of Health [TL1TR002491]
- National Institute of Allergy and Infectious Diseases [T32 AI070114, AI007001]
HIV-infected individuals are more susceptible to MDR-E infections due to HIV-specific factors. We conducted an observational study and developed a predictive model using machine learning algorithms to identify clinical and demographic predictors of MDR-E infection among PWH.
Background Medically vulnerable individuals are at increased risk of acquiring multidrug-resistant Enterobacterales (MDR-E) infections. People with HIV (PWH) experience a greater burden of comorbidities and may be more susceptible to MDR-E due to HIV-specific factors. Methods We performed an observational study of PWH participating in an HIV clinical cohort and engaged in care at a tertiary care center in the Southeastern United States from 2000 to 2018. We evaluated demographic and clinical predictors of MDR-E by estimating prevalence ratios (PRs) and employing machine learning classification algorithms. In addition, we created a predictive model to estimate risk of MDR-E among PWH using a machine learning approach. Results Among 4734 study participants, MDR-E was isolated from 1.6% (95% CI, 1.2%-2.1%). In unadjusted analyses, MDR-E was strongly associated with nadir CD4 cell count <= 200 cells/mm(3) (PR, 4.0; 95% CI, 2.3-7.4), history of an AIDS-defining clinical condition (PR, 3.7; 95% CI, 2.3-6.2), and hospital admission in the prior 12 months (PR, 5.0; 95% CI, 3.2-7.9). With all variables included in machine learning algorithms, the most important clinical predictors of MDR-E were hospitalization, history of renal disease, history of an AIDS-defining clinical condition, CD4 cell count nadir <= 200 cells/mm(3), and current CD4 cell count 201-500 cells/mm(3). Female gender was the most important demographic predictor. Conclusions PWH are at risk for MDR-E infection due to HIV-specific factors, in addition to established risk factors. Early HIV diagnosis, linkage to care, and antiretroviral therapy to prevent immunosuppression, comorbidities, and coinfections protect against antimicrobial-resistant bacterial infections.
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