Observational studyInfection control and hospital epidemiology2019
Predicting probability of perirectal colonization with carbapenem-resistant Enterobacteriaceae (CRE) and other carbapenem-resistant organisms (CROs) at hospital unit admission.
Observational study in Infection control and hospital epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- Evaluation of the Association Between Gastric Acid Suppression and Risk of Intestinal Colonization With Multidrug-Resistant Microorganisms: A Systematic Review and Meta-analysis.JAMA internal medicine · 2020Pooled it
- Carbapenem-Resistant Enterobacterales (CRE) in Europe: Surveillance Challenges, Emerging Threats and Public Health Preparedness.Antibiotics (Basel, Switzerland) · 2026Review
- A public health risk model using prior healthcare exposures identifies healthcare-associated pathogen carriage.Infection control and hospital epidemiology · 2026Article
- Explainable AI for infection prevention and control: modeling CPE acquisition and patient outcomes in an Irish hospital with transformers.BMC medical informatics and decision making · 2025Article
- Microbiome and resistome characterization of patients colonized with carbapenem-resistant Enterobacterales by long-read metagenomic next-generation sequencing of rectal swabs.JAC-antimicrobial resistance · 2025Article
- Identification of Long-Term Care Facility Residence From Admission Notes Using Large Language Models.JAMA network open · 2025Observational
- Artificial Intelligence in Bacterial Infections Control: A Scoping Review.Antibiotics (Basel, Switzerland) · 2025Review
- 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
- Tackling the Antimicrobial Resistance "Pandemic" with Machine Learning Tools: A Summary of Available Evidence.Microorganisms · 2024Review
- A review of the mechanisms that confer antibiotic resistance in pathotypes ofFrontiers in cellular and infection microbiology · 2024Review
- Model-based evaluation of admission screening strategies for the detection and control of carbapenemase-producing Enterobacterales in the English hospital setting.BMC medicine · 2023Article
- Fecal carriage and genetic characteristics of carbapenem-resistant enterobacterales among adults from four provinces of China.Frontiers in epidemiology · 2023Article
- Detection of Patients at Risk of Multidrug-Resistant Enterobacteriaceae Infection Using Graph Neural Networks: A Retrospective Study.Health data science · 2023Article
- Clinical Risk Factors and Microbiological and Intestinal Characteristics of Carbapenemase-ProducingMicrobiology spectrum · 2022Article
- A Seven-Year Microbiological and Molecular Study of Bacteremias Due to Carbapenemase-ProducingAntibiotics (Basel, Switzerland) · 2022Article
- Active surveillance of carbapenem-resistant gram-negative bacteria to guide antibiotic therapy: a single-center prospective observational study.Antimicrobial resistance and infection control · 2022Observational
- Epidemiological characteristics of carbapenem-resistant Enterobacteriaceae and carbapenem-resistant Acinetobacter baumannii in a tertiary referral hospital in Korea.Osong public health and research perspectives · 2022Article
- StenoSCORE: Predicting Stenotrophomonas maltophilia Bloodstream Infections in the Hematologic Malignancy Population.Antimicrobial agents and chemotherapy · 2021Article
- Prolonged Carriage of Carbapenemase-ProducingJournal of clinical medicine · 2021Article
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
backgroundTargeted screening for carbapenem-resistant organisms (CROs), including carbapenem-resistant Enterobacteriaceae (CRE) and carbapenemase-producing organisms (CPOs), remains limited; recent data suggest that existing policies miss many carriers.
objectiveOur objective was to measure the prevalence of CRO and CPO perirectal colonization at hospital unit admission and to use machine learning methods to predict probability of CRO and/or CPO carriage.
methodsWe performed an observational cohort study of all patients admitted to the medical intensive care unit (MICU) or solid organ transplant (SOT) unit at The Johns Hopkins Hospital between July 1, 2016 and July 1, 2017. Admission perirectal swabs were screened for CROs and CPOs. More than 125 variables capturing preadmission clinical and demographic characteristics were collected from the electronic medical record (EMR) system. We developed models to predict colonization probabilities using decision tree learning.
resultsEvaluating 2,878 admission swabs from 2,165 patients, we found that 7.5% and 1.3% of swabs were CRO and CPO positive, respectively. Organism and carbapenemase diversity among CPO isolates was high. Despite including many characteristics commonly associated with CRO/CPO carriage or infection, overall, decision tree models poorly predicted CRO and CPO colonization (C statistics, 0.57 and 0.58, respectively). In subgroup analyses, however, models did accurately identify patients with recent CRO-positive cultures who use proton-pump inhibitors as having a high likelihood of CRO colonization.
conclusionsIn this inpatient population, CRO carriage was infrequent but was higher than previously published estimates. Despite including many variables associated with CRO/CPO carriage, models poorly predicted colonization status, likely due to significant host and organism heterogeneity.
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