Joffrey Hamam1,2, Jean-Christophe Navellou1, Anne-Pauline Bellanger3,4, Stéphane Bretagne5,6, Hadrien Winiszewski1, Emeline Scherer3,4, Gael Piton1, Laurence Millon7,8. 1. Medical Intensive Care Unit, University Hospital of Besançon, 25000, Besancon, France. 2. Intensive Care Unit, Libourne Hospital, 33500, Libourne, France. 3. Parasitology-Mycology Department, University Hospital of Besançon, 25000, Besançon, France. 4. UMR 6249 CNRS Chrono-Environnement, University of Bourgogne Franche-Comté, 25000, Besançon, France. 5. Institut Pasteur, CNRS, Unité de Mycologie Moléculaire, Centre National de Référence Mycoses Invasives et Antifongiques, UMR 2000, Paris, France. 6. Université de Paris, Laboratoire de Parasitologie-Mycologie, Hôpital Saint Louis, AP-HP, Paris, France. 7. Parasitology-Mycology Department, University Hospital of Besançon, 25000, Besançon, France. lmillon@chu-besancon.fr. 8. UMR 6249 CNRS Chrono-Environnement, University of Bourgogne Franche-Comté, 25000, Besançon, France. lmillon@chu-besancon.fr.
Abstract
BACKGROUND: The classification of invasive pulmonary aspergillosis (IPA) issued by the European Organization for the Research and Treatment of Cancer/Mycoses Study Group Education and Research Consortium (EORTC/MSGERC) is used for immunocompromised patients. An alternative algorithm adapted to the intensive care unit (ICU) population has been proposed (AspICU), but this algorithm did not include microbial biomarkers such as the galactomannan antigen and the Aspergillus quantitative PCR. The objective of the present pilot study was to evaluate a new algorithm that includes fungal biomarkers (BM-AspICU) for the diagnosis of probable IPA in an ICU population. PATIENTS AND METHODS: Data from 35 patients with pathology-proven IPA according to European Organization for the Research and Treatment of Cancer/Mycosis Study Group (EORTC/MSGERC)-2008 criteria were extracted from the French multicenter database of the Invasive Fungal Infections Surveillance Network (RESSIF). The patients were investigated according to the AspICU algorithm, and the BM-AspICU algorithm in analyzing the clinical, imaging, and biomarker data available in the records, without taking into account the pathology findings. RESULTS: Eight patients had to be excluded because no imaging data were recorded in the database. Among the 27 proven IPAs with complete data, 16 would have been considered as putative IPA with the AspICU algorithm and 24 would have been considered as probable IPA using the new algorithm BM-AspICU. Seven out of the 8 patients with probable BM-AspICU IPA (and not classified with the AspICU algorithm) had no host factors and no Aspergillus-positive broncho-alveolar lavage fluid (BALF) culture. Three patients were non-classifiable with any of the two algorithms, because they did not have any microbial criteria during the course of the infection, and diagnosis of proven aspergillosis was done using autopsy samples. CONCLUSION: Inclusion of biomarkers could be effective to identify probable IPA in the ICU population. A prospective study is needed to validate the routine application of the BM-AspICU algorithm in the ICU population.
BACKGROUND: The classification of invasive pulmonary aspergillosis (IPA) issued by the European Organization for the Research and Treatment of Cancer/Mycoses Study Group Education and Research Consortium (EORTC/MSGERC) is used for immunocompromised patients. An alternative algorithm adapted to the intensive care unit (ICU) population has been proposed (AspICU), but this algorithm did not include microbial biomarkers such as the galactomannan antigen and the Aspergillus quantitative PCR. The objective of the present pilot study was to evaluate a new algorithm that includes fungal biomarkers (BM-AspICU) for the diagnosis of probable IPA in an ICU population. PATIENTS AND METHODS: Data from 35 patients with pathology-proven IPA according to European Organization for the Research and Treatment of Cancer/Mycosis Study Group (EORTC/MSGERC)-2008 criteria were extracted from the French multicenter database of the Invasive Fungal Infections Surveillance Network (RESSIF). The patients were investigated according to the AspICU algorithm, and the BM-AspICU algorithm in analyzing the clinical, imaging, and biomarker data available in the records, without taking into account the pathology findings. RESULTS: Eight patients had to be excluded because no imaging data were recorded in the database. Among the 27 proven IPAs with complete data, 16 would have been considered as putative IPA with the AspICU algorithm and 24 would have been considered as probable IPA using the new algorithm BM-AspICU. Seven out of the 8 patients with probable BM-AspICU IPA (and not classified with the AspICU algorithm) had no host factors and no Aspergillus-positive broncho-alveolar lavage fluid (BALF) culture. Three patients were non-classifiable with any of the two algorithms, because they did not have any microbial criteria during the course of the infection, and diagnosis of proven aspergillosis was done using autopsy samples. CONCLUSION: Inclusion of biomarkers could be effective to identify probable IPA in the ICU population. A prospective study is needed to validate the routine application of the BM-AspICU algorithm in the ICU population.
Authors: Julia Ebner; Miriam Van den Nest; Lukas Bouvier-Azula; Astrid Füszl; Cornelia Gabler; Birgit Willinger; Magda Diab-Elschahawi; Elisabeth Presterl Journal: J Fungi (Basel) Date: 2022-03-08