ArticleJournal of thoracic disease2026
Risk prediction for secondary pulmonary fungal infection during acute exacerbation of chronic obstructive pulmonary disease.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Secondary fungal infections significantly affect the outcomes of patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). This study aimed to develop and validate a clinically applicable prediction model for this complication. Methods: In this retrospective cohort study, we analyzed 225 consecutive patients with AECOPD who were admitted to The Fourth Affiliated Hospital of Soochow University (July 2022-July 2024). Patients were randomly allocated to the training (n=177) and validation (n=48) sets. Through multivariable logistic regression analysis, we identified independent risk factors and constructed a nomogram. Model performance was assessed using the area under the curve (AUC), calibration plots with the Hosmer-Lemeshow test, and decision curve analysis (DCA). Results: Three independent predictors were identified: the use of systemic glucocorticoids within 3 months before admission [odds ratio (OR) 2.943], admission to the hospital due to disease aggravation within the past year (OR 2.679), and the use of antibiotics for ≥14 days (OR 3.739). The nomogram demonstrated excellent discrimination {AUC 0.82 [95% confidence interval (CI): 0.75-0.88] in the training set; 0.80 (0.65-0.95) in the validation set} and good calibration (Hosmer-Lemeshow P>0.05). DCA confirmed the clinical utility across 10-80% risk thresholds. Conclusions: This validated nomogram, which incorporates three easily obtainable clinical parameters, provides reliable, individualized risk predictions for secondary pulmonary fungal infections in patients with AECOPD, facilitating early targeted interventions.
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