ArticleOpen forum infectious diseases2019
Predicting Carbapenem-Resistant
Article in Open forum infectious diseases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Prospective validation and implementation of a model to identify patients with carbapenem-resistant Enterobacterales (CRE) carriage on admission to acute care hospitals.Infection control and hospital epidemiology · 2026Article
- A public health risk model using prior healthcare exposures identifies healthcare-associated pathogen carriage.Infection control and hospital epidemiology · 2026Article
- Risk factors associated with rectal carriage of carbapenem resistant Enterobacterales in northern Nigeria: a hospital surveillance.BMC infectious diseases · 2025Article
- Beyond patient contact: combined short- and long read sequencing reveals continuous occurrence of genomically related carbapenemase-producing Enterobacterales and plasmid mobility in a hospital, Germany, 2018 to 2021.Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin · 2025Article
- A multi-center validation of the electronic health record admission source and discharge location fields against the clinical notes for identifying inpatients with long-term care facility exposure.Infection control and hospital epidemiology · 2024Article
- The ICU-CARB score: a novel clinical scoring system to predict carbapenem-resistant gram-negative bacteria carriage in critically ill patients upon ICU admission.Antimicrobial resistance and infection control · 2023Article
- Cefiderocol, a Siderophore Cephalosporin, as a Treatment Option for Infections Caused by Carbapenem-Resistant Enterobacterales.Infectious diseases and therapy · 2023Review
- Development of a Risk Prediction Model of Subsequent Bloodstream Infection After Carbapenem-Resistant Enterobacteriaceae Isolated from Perianal Swabs in Hematological Patients.Infection and drug resistance · 2023Article
- Identification and infection control of carbapenem-resistant Enterobacterales in intensive care units.Acute and critical care · 2021Article
- Carbapenem-Resistant Enterobacterales in Long-Term Care Facilities: A Global and Narrative Review.Frontiers in cellular and infection microbiology · 2021Review
- Active screening and interfacility communication of carbapenem-resistant Enterobacteriaceae (CRE) in a tertiary-care hospital.Infection control and hospital epidemiology · 2018Observational
- The Rapid Prediction of Carbapenem Resistance in Patients WithOpen forum infectious diseases · 2018Article
- Assessing the Ability of Hospital Diagnosis Codes to Detect Inpatient Exposure to Antibacterial Agents.Infection control and hospital epidemiology · 2018Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundTimely identification of patients likely to harbor carbapenem-resistant
methodsWe performed a case-control study using the Illinois hospital discharge database. From a 2014-2015 patient cohort, we defined cases as index adult patient hospital encounters with a positive CRE culture collected within the first 3 days of hospitalization, as reported to the Illinois XDRO registry; controls were all patient admissions from the same hospital and month. We split the data into training (~60%) and validation (~40%) sets and developed a logistic regression model to estimate coefficients for predictors of interest.
resultsWe identified 486 index cases and 340 005 controls. Independent risk factors for CRE at the time of admission were age, number of short-term acute care hospital (STACH) hospitalizations in the prior 365 days, mean STACH length of stay, number of long-term acute care hospital (LTACH) hospitalizations in the prior 365 days, mean LTACH length of stay, current admission to LTACH, and prior hospital admission with an infection diagnosis code. When applying the model to the validation data set, the area under the receiver operating characteristic curve was 0.84.
conclusionsA prediction model utilizing prior health care exposure information could discriminate patients who were likely to harbor CRE at the time of hospital admission.
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