{"doi":"10.1093/ofid/ofac487","title":"Predicting Risk of Multidrug-Resistant Enterobacterales Infections Among People With HIV","abstract":"Abstract 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/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. 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.","journal":"Open Forum Infectious Diseases","year":2022,"id":252094,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":24,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9394,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":340146,"name":"Sonia Napravnik","orcid":"0000-0002-9032-3713","position":1,"is_corresponding":false},{"id":367010,"name":"Michael R. Kosorok","orcid":"0000-0002-6070-9738","position":2,"is_corresponding":false},{"id":420429,"name":"Emily W. Gower","orcid":"0000-0003-1016-9910","position":3,"is_corresponding":false},{"id":449236,"name":"Alan C. Kinlaw","orcid":"0000-0002-4279-8685","position":4,"is_corresponding":false},{"id":109254,"name":"Allison E. Aiello","orcid":"0000-0001-7029-2537","position":5,"is_corresponding":false},{"id":728125,"name":"Billy Williams","orcid":null,"position":6,"is_corresponding":false},{"id":340150,"name":"David A. Wohl","orcid":"0000-0002-7764-0212","position":7,"is_corresponding":false},{"id":232741,"name":"David van Duin","orcid":"0000-0003-4784-3227","position":8,"is_corresponding":false},{"id":727645,"name":"Heather Henderson","orcid":"0000-0002-2197-3149","position":0,"is_corresponding":true}],"reference_count":44,"raw_metadata":null,"created_at":"2026-07-19T00:24:46.226372Z","pmid":"36225740","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}