ORIGINAL RESEARCH article
Front. Med.
Sec. Pulmonary Medicine
Volume 12 - 2025 | doi: 10.3389/fmed.2025.1594934
Development of a novel model for accurate prediction of secondary Candida pneumonia in patients with acute exacerbation of chronic obstructive pulmonary disease
Provisionally accepted
Xiaodan Zhu1
Changxing Shen2*- 1Yiwu Central Hospital, Yiwu, China
- 2Shanghai Baoshan Luodian Hospital, Shanghai, China
Select one of your emails
You have multiple emails registered with Frontiers:
Notify me on publication
Please enter your email address:
If you already have an account, please login
You don't have a Frontiers account ? You can register here
Given the increased risk factors such as the wide application of various dose forms of corticosteroids and broad-spectrum antibiotics in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) in recent years, the incidence of invasive Candida pneumonia secondary to AECOPD tends to increase. However, Candida infections secondary to AE COPD are often neglected in clinical practice, or even misdiagnosed as bacterial infections, resulting in disease deterioration due to delayed diagnosis. Knowing that early diagnosis and timely treatment can obviously improve the prognosis of pulmonary c andidiasis, improving the early diagnosis rate is the key to reduce the mortality of AECOPD-associated candidiasis. The present study was intended to develop a new model that can early and accurately predict the occurrence of Candida infections secondary to AECOPD. Methods ： Clinical data of 164 hospitalized patients with AECOPD who received treatment in the department of respiratory medicine of Yiwu Central Hospital between January 2022 and January 2024 were reviewed retrospectively, Results: Of the 164 AE COPD patients, 87 were male and 77 were female, with a mean age of 77.28±8.10 years. The model group consisted of 127 AECOPD patients, including 64 with candidiasis secondary to AE COPD and 63 with no candida infection; the validation group consisted of 37 patients, including 14 with secondary candidiasis and 23 with no Candida infection. Single factor logistic regression analysis of the patients in the model group showed that BMI, use of antibiotics ≧2 weeks, cancer chemoradiotherapy and pulmonary function grade were four independent predictors for the occurrence of secondary candida infection. The weigh factor of the four risk factors was further determined by Multivariate logistic regression analysis as follows: Probability of infection (P) = EXP (-17.7063452+1.8265388*pulmonary function grade+1.8443357*cancer chemoradiotherapy+4. 1749059*use of antibiotics≥2weeks+0.4527216*BMI), and P>0.5 suggests the probability of developing secondary candidiasis in the AECOPD patient.
Keywords: AE COPD-associated candidiasis, novel model for accurate prediction, Infection, Cancer, pulmonary function grade
Received: 19 Mar 2025; Accepted: 09 Jul 2025.
Copyright: © 2025 Zhu and Shen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Changxing Shen, Shanghai Baoshan Luodian Hospital, Shanghai, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.