ArticleJournal of intensive care2023
A deep learning model for predicting multidrug-resistant organism infection in critically ill patients.
Article in Journal of intensive care, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Risk Prediction of Multidrug-Resistant Infections in Pediatric Burn Patients with Hospital-Acquired Infections: A Retrospective Cohort Study.Plastic and reconstructive surgery · 2026Article
- Development and Prospective Validation of a Machine Learning Tool for Predicting Multidrug-resistant Organism Infections in an Indian Critical Care Unit.Indian journal of critical care medicine : peer-reviewed, official publication of Indian Society of Critical Care Medicine · 2026Article
- Development and validation of an interpretable machine learning model for predicting multidrug-resistant infections in ICU patients.Frontiers in cellular and infection microbiology · 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
- Episode- and Hospital-Level Modeling of Pan-Resistant Healthcare-Associated Infections (2020-2024) Using TabTransformer and Attention-Based LSTM Forecasting.Diagnostics (Basel, Switzerland) · 2025Article
- Artificial Intelligence in Bacterial Infections Control: A Scoping Review.Antibiotics (Basel, Switzerland) · 2025Review
- Analysis of the etiological characteristics of multidrug-resistant organisms and prognostic factors in ICU patients.Frontiers in physiology · 2025Article
- Association Between Malnutrition and Multi-Drug Resistant Bacterial Infections in Neurosurgical Intensive Care Unit Patients.Infection and drug resistance · 2025Article
- Development and validation of machine learning models to predict MDRO colonization or infection on ICU admission by using electronic health record data.Antimicrobial resistance and infection control · 2024Article
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10 authors.
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Abstract
backgroundThis study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients.
methodsThis study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy.
resultsIn the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852-0.925), 0.919 (95% CI 0.856-0.983), and 0.811 (95% CI 0.731-0.891), respectively.
conclusionsThis study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.
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