Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients

ABSTRACT Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses one of the major challenges in clinical anti-infective therapy worldwide. This retrospective cohort study at a tertiary general hospital in Wuhan aimed to identify risk factors for hospital-acquired CRKP infections among 1,113 patients...

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Main Authors: Tingting Xu, Yuxin Shi, Xiongjing Cao, Lijuan Xiong
Format: Article
Language:English
Published: American Society for Microbiology 2025-01-01
Series:Microbiology Spectrum
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Online Access:https://journals.asm.org/doi/10.1128/spectrum.02170-24
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author Tingting Xu
Yuxin Shi
Xiongjing Cao
Lijuan Xiong
author_facet Tingting Xu
Yuxin Shi
Xiongjing Cao
Lijuan Xiong
author_sort Tingting Xu
collection DOAJ
description ABSTRACT Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses one of the major challenges in clinical anti-infective therapy worldwide. This retrospective cohort study at a tertiary general hospital in Wuhan aimed to identify risk factors for hospital-acquired CRKP infections among 1,113 patients. All participants were aged 18 years and above, and had confirmed positive cultures for KP isolated within 48 hours post-hospitalization. Independent risk factors were identified using LASSO logistic regression and incorporated into a predictive nomogram. The factors included in the nomogram were prior carbapenem exposure, prior β-lactams–β-lactamase inhibitor combination (BLBLI) exposure, prior intensive care unit (ICU) stay, and prior mechanical ventilation. The areas under the receiver operating characteristic curve (AUC) for the nomogram were 0.793 in the training group (70% of patients) and 0.788 in the validation group (30% of patients), demonstrating its discriminatory power and predictive accuracy. The P values for the Hosmer-Lemeshow test were 0.333 and 0.684, indicating good calibration. The clinical utility of the nomogram was further supported by decision curve analysis (DCA) and clinical impact curve (CIC), demonstrating its potential to guide clinical decision-making. Our retrospective analysis identified key risk factors for CRKP infection and developed a nomogram that could effectively predict CRKP infections in hospitalized patients. Although the single-center nature of this study limits generalizability, the nomogram provides a foundation for future prospective, multicenter validations.IMPORTANCEWe established a nomogram scoring system that incorporates four key risk factors: prior carbapenem exposure, prior β-lactams–β-lactamase inhibitor combination (BLBLI) exposure, prior intensive care unit (ICU) stay, and prior mechanical ventilation. This nomogram demonstrated strong discriminatory power, excellent calibration, and significant clinical utility. This study highlights the critical risk factors associated with hospital-acquired carbapenem-resistant Klebsiella pneumoniae (CRKP) infections, providing valuable insights for clinicians to identify high-risk patients.
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spelling doaj-art-da196df93d0b4c969a8ff3b2ca6c8db42025-01-07T14:05:19ZengAmerican Society for MicrobiologyMicrobiology Spectrum2165-04972025-01-0113110.1128/spectrum.02170-24Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patientsTingting Xu0Yuxin Shi1Xiongjing Cao2Lijuan Xiong3Department of Infectious Disease, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Nosocomial Infection Management, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Nosocomial Infection Management, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Infectious Disease, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaABSTRACT Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses one of the major challenges in clinical anti-infective therapy worldwide. This retrospective cohort study at a tertiary general hospital in Wuhan aimed to identify risk factors for hospital-acquired CRKP infections among 1,113 patients. All participants were aged 18 years and above, and had confirmed positive cultures for KP isolated within 48 hours post-hospitalization. Independent risk factors were identified using LASSO logistic regression and incorporated into a predictive nomogram. The factors included in the nomogram were prior carbapenem exposure, prior β-lactams–β-lactamase inhibitor combination (BLBLI) exposure, prior intensive care unit (ICU) stay, and prior mechanical ventilation. The areas under the receiver operating characteristic curve (AUC) for the nomogram were 0.793 in the training group (70% of patients) and 0.788 in the validation group (30% of patients), demonstrating its discriminatory power and predictive accuracy. The P values for the Hosmer-Lemeshow test were 0.333 and 0.684, indicating good calibration. The clinical utility of the nomogram was further supported by decision curve analysis (DCA) and clinical impact curve (CIC), demonstrating its potential to guide clinical decision-making. Our retrospective analysis identified key risk factors for CRKP infection and developed a nomogram that could effectively predict CRKP infections in hospitalized patients. Although the single-center nature of this study limits generalizability, the nomogram provides a foundation for future prospective, multicenter validations.IMPORTANCEWe established a nomogram scoring system that incorporates four key risk factors: prior carbapenem exposure, prior β-lactams–β-lactamase inhibitor combination (BLBLI) exposure, prior intensive care unit (ICU) stay, and prior mechanical ventilation. This nomogram demonstrated strong discriminatory power, excellent calibration, and significant clinical utility. This study highlights the critical risk factors associated with hospital-acquired carbapenem-resistant Klebsiella pneumoniae (CRKP) infections, providing valuable insights for clinicians to identify high-risk patients.https://journals.asm.org/doi/10.1128/spectrum.02170-24carbapenem resistanceKlebsiella pneumoniaenomogramrisk factor
spellingShingle Tingting Xu
Yuxin Shi
Xiongjing Cao
Lijuan Xiong
Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
Microbiology Spectrum
carbapenem resistance
Klebsiella pneumoniae
nomogram
risk factor
title Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
title_full Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
title_fullStr Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
title_full_unstemmed Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
title_short Development and validation of a nomogram-based risk prediction model for carbapenem-resistant Klebsiella pneumoniae in hospitalized patients
title_sort development and validation of a nomogram based risk prediction model for carbapenem resistant klebsiella pneumoniae in hospitalized patients
topic carbapenem resistance
Klebsiella pneumoniae
nomogram
risk factor
url https://journals.asm.org/doi/10.1128/spectrum.02170-24
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