Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.

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dc.contributor.authorLodise, Thomas P
dc.contributor.authorBonine, Nicole Gidaya
dc.contributor.authorYe, Jiatao Michael
dc.contributor.authorFolse, Henry J
dc.contributor.authorGillard, Patrick
dc.contributor.orcidhttps://orcid.org/0000-0002-4730-0655
dc.date.accessioned2025-02-07T19:34:55Z
dc.date.available2025-02-07T19:34:55Z
dc.date.issued8/14/2019
dc.description.abstractBACKGROUND: We developed a clinical bedside tool to simultaneously estimate the probabilities of third-generation cephalosporin-resistant Enterobacteriaceae (3GC-R), carbapenem-resistant Enterobacteriaceae (CRE), and multidrug-resistant Pseudomonas aeruginosa (MDRP) among hospitalized adult patients with Gram-negative infections. METHODS: Data were obtained from a retrospective observational study of the Premier Hospital that included hospitalized adult patients with a complicated urinary tract infection (cUTI), complicated intra-abdominal infection (cIAI), hospital-acquired/ventilator-associated pneumonia (HAP/VAP), or bloodstream infection (BSI) due to Gram-negative bacteria between 2011 and 2015. Risk factors for 3GC-R, CRE, and MDRP were ascertained by multivariate logistic regression, and separate models were developed for patients with community-acquired versus hospital-acquired infections for each resistance phenotype (N = 6). Models were converted to a singular user-friendly interface to estimate the probabilities of a patient having an infection due to 3GC-R, CRE, or MDRP when >/= 1 risk factor was present. RESULTS: Overall, 124,068 patients contributed to the dataset. Percentages of patients admitted for cUTI, cIAI, HAP/VAP, and BSI were 61.6, 4.6, 16.5, and 26.4%, respectively (some patients contributed > 1 infection type). Resistant infection rates were 1.90% for CRE, 12.09% for 3GC-R, and 3.91% for MDRP. A greater percentage of the resistant infections were community-acquired relative to hospital-acquired (CRE, 1.30% vs 0.62% of 1.90%; 3GC-R, 9.27% vs 3.42% of 12.09%; MDRP, 2.39% vs 1.59% of 3.91%). The most important predictors of having an 3GC-R, CRE or MDRP infection were prior number of antibiotics; infection site; infection during the previous 3 months; and hospital prevalence of 3GC-R, CRE, or MDRP. To enable application of the six predictive multivariate logistic regression models to real-world clinical practice, we developed a user-friendly interface that estimates the risk of 3GC-R, CRE, and MDRP simultaneously in a given patient with a Gram-negative infection based on their risk (Additional file 1). CONCLUSIONS: We developed a clinical prediction tool to estimate the probabilities of 3GC-R, CRE, and MDRP among hospitalized adult patients with confirmed community- and hospital-acquired Gram-negative infections. Our predictive model has been implemented as a user-friendly bedside tool for use by clinicians/healthcare professionals to predict the probability of resistant infections in individual patients, to guide early appropriate therapy.
dc.description.urihttps://doi.org/10.1186/s12879-019-4363-y
dc.description.urihttp://www.ncbi.nlm.nih.gov/pmc/articles/pmc6694572
dc.identifier.citationLodise TP, Bonine NG, Ye JM, Folse HJ, Gillard P. Development of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections. BMC Infect Dis. 2019 Aug 14;19(1):718. doi: 10.1186/s12879-019-4363-y. PMID: 31412809; PMCID: PMC6694572.
dc.identifier.issn1471-2334
dc.identifier.other31412809
dc.identifier.urihttps://hdl.handle.net/20.500.14303/711
dc.language.isoen
dc.publisherBioMed Central
dc.relation.ispartofBMC Infectious Diseases
dc.rightsThis Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s). http://rightsstatements.org/vocab/InC/1.0/
dc.subjectAnti-Bacterial Agents/therapeutic use
dc.subjectBacteremia/drug therapy/epidemiology/microbiology
dc.subjectCarbapenem-Resistant Enterobacteriaceae/drug effects/pathogenicity
dc.subjectCross Infection/drug therapy/epidemiology/microbiology
dc.subjectDecision Making, Computer-Assisted
dc.subjectDrug Resistance, Bacterial/drug effects
dc.subjectGram-Negative Bacteria/drug effects
dc.subjectGram-Negative Bacterial Infections/drug therapy/epidemiology/microbiology
dc.subjectHospitals/statistics & numerical data
dc.subjectPneumonia, Ventilator-Associated/drug therapy/epidemiology/microbiology
dc.subjectPoint-of-Care Systems
dc.subjectPrevalence
dc.subjectProbability
dc.subjectRetrospective Studies
dc.subjectUnited States/epidemiology
dc.subjectUrinary Tract Infections/drug therapy/epidemiology/microbiology
dc.subjectUser-Computer Interface
dc.titleDevelopment of a bedside tool to predict the probability of drug-resistant pathogens among hospitalized adult patients with gram-negative infections.
dc.typeArticle
local.departmentprogramDepartment of Pharmacy Practice
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