International journal of chronic obstructive pulmonary disease · 2026
Prediction Score of Pseudomonas Aeruginosa Isolation in Acute Exacerbations of Chronic Obstructive Pulmonary Disease.
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Morasert Thotsaporn, Tantiyavarong Pichaya
Аннотация
BACKGROUND: 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.
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.