Development and Validation of a Nomogram for Predicting Multidrug-Resistant Pseudomonas Aeruginosa Pneumonia in Hospitalized Patients.
Year: 2025
Type: article
Study design: Observational Study
Abstract: Objective: (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: 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: =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.
Source: PubMed
DOI: 10.2147/idr.s527949
Authors: Zhuman Du, Dan Yang, Linhai Pan, Qianglin Zeng, Xiaoju Chen
Language: English
Subfield: Molecular Medicine
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W4412556027