Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients

Zhuman Du,1 Dan Yang,2 Linhai Pan,1 Qianglin Zeng,1 Xiaoju Chen1 1Department of Respiratory and Critical Care Medicine, Clinical Medicine College & Affiliated Hospital of Chengdu University, Chengdu, People’s Republic of China; 2Center of Gerontology and Geriatrics, West China Hospital, Sich...

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Main Authors: Du Z, Yang D, Pan L, Zeng Q, Chen X
Format: Article
Language:English
Published: Dove Medical Press 2025-07-01
Series:Infection and Drug Resistance
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Online Access:https://www.dovepress.com/development-and-validation-of-a-nomogram-for-predicting-multidrug-resi-peer-reviewed-fulltext-article-IDR
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author Du Z
Yang D
Pan L
Zeng Q
Chen X
author_facet Du Z
Yang D
Pan L
Zeng Q
Chen X
author_sort Du Z
collection DOAJ
description Zhuman Du,1 Dan Yang,2 Linhai Pan,1 Qianglin Zeng,1 Xiaoju Chen1 1Department of Respiratory and Critical Care Medicine, Clinical Medicine College & Affiliated Hospital of Chengdu University, Chengdu, People’s Republic of China; 2Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of ChinaCorrespondence: Qianglin Zeng; Xiaoju Chen, Department of Respiratory and Critical Care Medicine, Clinical Medicine College & Affiliated Hospital of Chengdu University, No. 82 North Section 2, Second Ring Road, Chengdu, Sichuan Province, People’s Republic of China, Email qlzeng@hotmail.com; cxj9592@163.comObjective: The management of multidrug-resistant Pseudomonas aeruginosa (MDR-PA) pneumonia remains challenging due to increasing antibiotic resistance and high mortality rates. Current prediction models often neglect three critical factors: comorbidities, medical interventions, and prior antibiotic exposure. This study created a practical risk assessment tool incorporating these clinical elements.Methods: This retrospective study collected 3132 bronchoalveolar lavage fluid specimens from a large tertiary comprehensive hospital in southwestern China over a two-year period (20232024). A total of 209 patients with Pseudomonas aeruginosa pneumonia were ultimately enrolled, including 94 cases of multidrug-resistant and 115 drug-sensitive cases. Data included demographics, comorbidities, invasive procedures, antibiotic histories, and laboratory findings. Key predictors were selected using LASSO regression, followed by logistic regression to build a predictive model. Performance was evaluated through ROC analysis, calibration tests, and bootstrap validation.Results: Thirteen predictors were identified: Age, prolonged hospitalization; Cor pulmonale, cardiac insufficiency, old cerebral infarction, chronic renal failure; ventilation, tracheostomy, nasogastric intubation; Cefoperazone-sulbactam, aminoglycosides, antifungals; Hemoglobin levels. The model showed strong predictive accuracy with AUC values of 0.853 (95% CI 0.793– 0.914) in training and 0.972 (0.931– 1.000) in validation cohorts. Calibration demonstrated excellent consistency (Hosmer-Lemeshow P=0.989).Conclusion: In this study, we developed and validated a predictive model for MDR-PA pneumonia risk by integrating host comorbidities, iatrogenic interventions, and antimicrobial exposure. The model demonstrates potential utility in early identification of high-risk patients and may inform antimicrobial stewardship strategies in regions with predominant cephalosporin/aminoglycoside resistance patterns.Keywords: pseudomonas aeruginosa, multidrug resistance, nomogram, risk factor
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spelling doaj-art-e08bcbd3652049ed81589b70ca6628a32025-08-20T02:39:48ZengDove Medical PressInfection and Drug Resistance1178-69732025-07-01Volume 18Issue 135433559104878Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized PatientsDu Z0Yang D1Pan L2Zeng Q3Chen X4Department of Respiratory and Critical Care MedicineCenter of Gerontology and GeriatricsDepartment of Respiratory and Critical Care MedicineDepartment of Respiratory and Critical Care MedicineDepartment of Respiratory and Critical Care MedicineZhuman Du,1 Dan Yang,2 Linhai Pan,1 Qianglin Zeng,1 Xiaoju Chen1 1Department of Respiratory and Critical Care Medicine, Clinical Medicine College & Affiliated Hospital of Chengdu University, Chengdu, People’s Republic of China; 2Center of Gerontology and Geriatrics, West China Hospital, Sichuan University, Chengdu, People’s Republic of ChinaCorrespondence: Qianglin Zeng; Xiaoju Chen, Department of Respiratory and Critical Care Medicine, Clinical Medicine College & Affiliated Hospital of Chengdu University, No. 82 North Section 2, Second Ring Road, Chengdu, Sichuan Province, People’s Republic of China, Email qlzeng@hotmail.com; cxj9592@163.comObjective: The management of multidrug-resistant Pseudomonas aeruginosa (MDR-PA) pneumonia remains challenging due to increasing antibiotic resistance and high mortality rates. Current prediction models often neglect three critical factors: comorbidities, medical interventions, and prior antibiotic exposure. This study created a practical risk assessment tool incorporating these clinical elements.Methods: This retrospective study collected 3132 bronchoalveolar lavage fluid specimens from a large tertiary comprehensive hospital in southwestern China over a two-year period (20232024). A total of 209 patients with Pseudomonas aeruginosa pneumonia were ultimately enrolled, including 94 cases of multidrug-resistant and 115 drug-sensitive cases. Data included demographics, comorbidities, invasive procedures, antibiotic histories, and laboratory findings. Key predictors were selected using LASSO regression, followed by logistic regression to build a predictive model. Performance was evaluated through ROC analysis, calibration tests, and bootstrap validation.Results: Thirteen predictors were identified: Age, prolonged hospitalization; Cor pulmonale, cardiac insufficiency, old cerebral infarction, chronic renal failure; ventilation, tracheostomy, nasogastric intubation; Cefoperazone-sulbactam, aminoglycosides, antifungals; Hemoglobin levels. The model showed strong predictive accuracy with AUC values of 0.853 (95% CI 0.793– 0.914) in training and 0.972 (0.931– 1.000) in validation cohorts. Calibration demonstrated excellent consistency (Hosmer-Lemeshow P=0.989).Conclusion: In this study, we developed and validated a predictive model for MDR-PA pneumonia risk by integrating host comorbidities, iatrogenic interventions, and antimicrobial exposure. The model demonstrates potential utility in early identification of high-risk patients and may inform antimicrobial stewardship strategies in regions with predominant cephalosporin/aminoglycoside resistance patterns.Keywords: pseudomonas aeruginosa, multidrug resistance, nomogram, risk factorhttps://www.dovepress.com/development-and-validation-of-a-nomogram-for-predicting-multidrug-resi-peer-reviewed-fulltext-article-IDRpneumoniaPseudomonas aeruginosamultidrug resistancenomogram;
spellingShingle Du Z
Yang D
Pan L
Zeng Q
Chen X
Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
Infection and Drug Resistance
pneumonia
Pseudomonas aeruginosa
multidrug resistance
nomogram;
title Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
title_full Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
title_fullStr Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
title_full_unstemmed Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
title_short Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients
title_sort development and validation of a nomogram for predicting multidrug resistant pseudomonas aeruginosa pneumonia in hospitalized patients
topic pneumonia
Pseudomonas aeruginosa
multidrug resistance
nomogram;
url https://www.dovepress.com/development-and-validation-of-a-nomogram-for-predicting-multidrug-resi-peer-reviewed-fulltext-article-IDR
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