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Updated: Oct 22, 2025

The WinCF Model - An Inexpensive and Tractable Microcosm of a Mucus Plugged Bronchiole to Study the Microbiology of Lung Infections
Published on: May 8, 2017
New Insights in Microbial Species Predicting Lung Function Decline in CF: Lessons from the MucoFong Project
Florence Francis1,2, Raphael Enaud3,4,5, Perrine Soret2,6,7
1CHU de Bordeaux, Department of Public Health, F-33000 Bordeaux, France.
Abstract:
Several predictive models have been proposed to understand the microbial risk factors associated with cystic fibrosis (CF) progression. Very few have integrated fungal airways colonisation, which is increasingly recognized as a key player regarding CF progression. To assess the association between the percent predicted forced expiratory volume in 1 s (ppFEV1) change and the fungi or bacteria identified in the sputum, 299 CF patients from the "MucoFong" project were included and followed-up with over two years. The relationship between the microorganisms identified in the sputum and ppFEV1 course of patients was longitudinally analysed. An adjusted linear mixed model analysis was performed to evaluate the effect of a transient or chronic bacterial and/or fungal colonisation at inclusion on the ppFEV1 change over a two-year period. Pseudomonas aeruginosa, Achromobacter xylosoxidans, Stenotrophomonas maltophilia, and Candida albicans were associated with a significant ppFEV1 decrease. No significant association was found with other fungal colonisations. In addition, the ppFEV1 outcome in our model was 11.26% lower in patients presenting with a transient colonisation with non-pneumoniae Streptococcus species compared to other patients. These results confirm recently published data and provide new insights into bacterial and fungal colonisation as key factors for the assessment of lung function decline in CF patients.
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