AUTHOR=Zhang Man-ka , Rao Zhi-guo , Ma Tao , Tang Ming , Xu Tian-qi , He Xiao-xu , Li Zhou-ping , Liu Yin , Xu Qing-jie , Yang Ke-yu , Gong Yi-fan , Xue Jing , Wu Mei-qing , Xue Xiao-yan TITLE=Appropriate empirical antifungal therapy is associated with a reduced mortality rate in intensive care unit patients with invasive fungal infection: A real-world retrospective study based on the MIMIC-IV database JOURNAL=Frontiers in Medicine VOLUME=9 YEAR=2022 URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.952611 DOI=10.3389/fmed.2022.952611 ISSN=2296-858X ABSTRACT=Objective

The study aimed to determine the prevalence and pathogens of invasive fungal infection (IFI) among intensive care unit (ICU) patients. The next goal was to investigate the association between empirical antifungal treatment and mortality in ICU patients.

Methods

Using microbiological events, we identified all ICU patients with IFI and then retrieved electronic clinical data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. The data were statistically analyzed using t-tests, chi-square tests, log-rank tests, and Cox regression.

Results

The most commonly reported fungi were Candida (72.64%) and Aspergillus (19.08%). The most frequently prescribed antifungal medication was fluconazole (37.57%), followed by micafungin (26.47%). In the survival study of ICU patients and patients with sepsis, survivors were more likely to receive empirical antifungal treatment. In contrast, non-empirical antifungal therapy was significantly associated with poor survival in patients with positive blood cultures. We found that the current predictive score makes an accurate prediction of patients with fungal infections challenging.

Conclusions

Our study demonstrated that empirical antifungal treatment is associated with decreased mortality in ICU patients. To avoid treatment delays, novel diagnostic techniques should be implemented in the clinic. Until such tests are available, appropriate empirical antifungal therapy could be administered based on a model that predicts the optimal time to initiate antifungal therapy. Additional studies should be conducted to establish more accurate predictive models in the future.