Prediction Score of Pseudomonas Aeruginosa Isolation in Acute Exacerbations of Chronic Obstructive Pulmonary Disease
Year: 2026
Type: article
Study design: Observational Study
Abstract: Thotsaporn Morasert,1,2 Pichaya Tantiyavarong1 1Department of Clinical Epidemiology, Faculty of Medicine, Thammasat University, Pathum Thani, 12120, Thailand; 2Pulmonary and Critical Care Medicine, Department of Medicine, Suratthani Hospital, Surat Thani, 84000, ThailandCorrespondence: Pichaya Tantiyavarong, Department of Clinical Epidemiology, Faculty of Medicine, Thammasat University, 99/209 Moo 18, Phaholyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani, 12120, Thailand, Tel +66-89-7711576, Email [email protected]: Pseudomonas aeruginosa (PA) is an important pathogen in acute exacerbations of chronic obstructive pulmonary disease (AECOPD), yet empirical anti-PA coverage is often prescribed inappropriately. Accurate prediction tools are needed to guide targeted therapy.Methods: We conducted a retrospective cohort study of hospitalized AECOPD patients at a regional referral hospital in Thailand (2015– 2018). Clinical, radiographic, and laboratory data were analyzed to identify independent predictors of PA isolation. Multivariable logistic regression was used to develop a prediction score, which was internally validated using bootstrap resampling. Model performance was assessed by the area under the receiver operating characteristic curve (AuROC).Results: Among 1,348 admissions (771 patients), P. aeruginosa was isolated in 167 cases (12.4%). A simplified prediction score was developed based on four independent predictors: home nebulizer use, prior anti-PA antibiotic exposure within 1 year, radiographic consolidation, and elevated serum bicarbonate. The prediction score achieved an AuROC of 0.66 (95% CI 0.62– 0.70) with good calibration after internal validation. Risk groups were defined as low (0– 1 points, < 12% risk), intermediate (2– 3 points, 16– 23% risk), and high (4– 6 points, ≥ 32% risk).Conclusion: This simplified prediction score, developed in hospitalized AECOPD patients, may aid clinicians in guiding empirical antibiotic selection by reducing unnecessary anti-PA coverage in low-risk cases while ensuring timely treatment for those at high risk.Keywords: AECOPD, acute exacerbations, chronic obstructive pulmonary disease, pseudomonas aeruginosa, predictive model, prediction score
Authors: Morasert T, Tantiyavarong P
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W7128668378
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