• Department of Respiratory Medicine, The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan 610500, P. R. China;
HUANG Na, Email: 717308813@qq.com
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Objective  To investigate the risk factors for secondary pulmonary fungal infection in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD). And a visual tool using nomogram was developed and validated to assist in the clinical prediction of the probability of pulmonary fungal infection occurrence in AECOPD patients. Methods  A retrospective cohort study method was used to collect AECOPD patients hospitalized in the Department of Respiratory, The First Affiliated Hospital of Chengdu Medical College from January 2021 to December 2021 as a training set. And AECOPD patients between January 2020 and December 2020 were collected as a validation set. Independent risk factors were determined through univariate, Lasso regression analyses. and multivariable logistic, A nomogram prediction model was constructed with these independent risk factors, and the nomogram was evaluated by receiver operating characteristic area under the curve (AUC), calibration curve, and decision curve analysis (DCA). Results  The use of glucocorticoid, combined use of antibiotics, duration of antibiotic use and hypoalbuminemia were independent risk factors for secondary pulmonary fungal infection in AECOPD patients (all P<0.05). The training set and validation set of the constructed prediction model had an AUC value of 0.915 [95%CI: 0.891 - 0.940] and 0.830 [95%CI: 0.790 - 0.871], respectively. The calibration curve showed that the predicted probability was in good agreement with the actual observed probability of pulmonary fungal infection in AECOPD patients. The corresponding decision curve analysis (DCA) indicated the nomogram had relatively ideal clinical utility. Conclusions  The result showed that the use of glucocorticoid, combined use of antibiotics, prolonged antibiotic therapy and hypoalbuminemia was independent risk factors for pulmonary fungal infection in AECOPD patients. The clinical prediction model for secondary pulmonary fungal infection in AECOPD patients constructed in this study has strong predictive power and clinical practicability.

Citation: LIN Xi, HUANG Na. A nomogram for predicting secondary pulmonary fungal infection in patients with acute exacerbations of chronic obstructive pulmonary disease. Chinese Journal of Respiratory and Critical Care Medicine, 2024, 23(2): 77-85. doi: 10.7507/1671-6205.202208055 Copy

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