Predicting Risk of Multidrug-Resistant Enterobacterales Infections Among People With HIV

Author:

Henderson Heather I1ORCID,Napravnik Sonia1ORCID,Kosorok Michael R2ORCID,Gower Emily W1,Kinlaw Alan C34ORCID,Aiello Allison E1ORCID,Williams Billy5,Wohl David A1ORCID,van Duin David1ORCID

Affiliation:

1. Department of Medicine, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina , USA

2. Department of Biostatistics, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina , USA

3. Division of Pharmaceutical Outcomes and Policy, University of North Carolina School of Pharmacy , Chapel Hill, North Carolina , USA

4. Cecil G. Sheps Center for Health Services Research, University of North Carolina at Chapel Hill , Chapel Hill, North Carolina , USA

5. Clinical Microbiology Laboratory, University of North Carolina Hospitals , Chapel Hill, North Carolina , USA

Abstract

AbstractBackgroundMedically 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.MethodsWe 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.ResultsAmong 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/mm3 (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/mm3, and current CD4 cell count 201–500 cells/mm3. Female gender was the most important demographic predictor.ConclusionsPWH 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.

Funder

University of North Carolina at Chapel Hill Center for AIDS Research

National Institutes of Health

National Center for Advancing Translational Sciences

National Institute of Allergy and Infectious Diseases

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,Oncology

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