ArticleFrontiers in cellular and infection microbiology2024
A prediction model for secondary invasive fungal infection among severe SARS-CoV-2 positive patients in ICU.
Article in Frontiers in cellular and infection microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Incidence, mortality and risk factors of invasive pulmonary aspergillosis in critically ill patients during the COVID-19 era: a global systematic review and meta-analysis.Annals of clinical microbiology and antimicrobials · 2026Pooled it
- Risk factors for intensive care unit coronavirus disease 2019 pneumonia-associated invasive fungal infections: a Bayesian evidence synthesis integrating external and real-world data.Virology journal · 2026Article
- Metagenomics next-generation sequencing for diagnosis of invasive fungal diseases in patients with hematological diseases.IJID regions · 2025Article
- Epidemiological shifts and advances in research on early diagnosis of invasive fungal infection in critically ill patients.Frontiers in cellular and infection microbiology · 2025Review
- A Machine Learning Approach to Determine Risk Factors for Respiratory Bacterial/Fungal Coinfection in Critically Ill Patients with Influenza and SARS-CoV-2 Infection: A Spanish Perspective.Antibiotics (Basel, Switzerland) · 2024Article
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Abstract
Background: The global COVID-19 pandemic has resulted in over seven million deaths, and IFI can further complicate the clinical course of COVID-19. Coinfection of COVID-19 and IFI (secondary IFI) pose significant threats not only to healthcare systems but also to patient lives. After the control measures for COVID-19 were lifted in China, we observed a substantial number of ICU patients developing COVID-19-associated IFI. This creates an urgent need for predictive assessment of COVID-19 patients in the ICU environment for early detection of suspected fungal infection cases. Methods: This study is a single-center, retrospective research endeavor. We conducted a case-control study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive patients. The cases consisted of patients who developed any secondary IFI during their ICU stay at Jilin University China-Japan Union Hospital in Changchun, Jilin Province, China, from December 1st, 2022, to August 31st, 2023. The control group consisted of SARS-CoV-2 positive patients without secondary IFI. Descriptive and comparative analyses were performed, and a logistic regression prediction model for secondary IFI in COVID-19 patients was established. Additionally, we observed an increased incidence of COVID-19-associated pulmonary aspergillosis (CAPA) during this pandemic. Therefore, we conducted a univariate subgroup analysis on top of IFI, using non-CAPA patients as the control subgroup. Results: From multivariate analysis, the prediction model identified 6 factors that are significantly associated with IFI, including the use of broad-spectrum antibiotics for more than 2 weeks (aOR=4.14, 95% CI 2.03-8.67), fever (aOR=2.3, 95%CI 1.16-4.55), elevated log Conclusion: We recommend paying special attention for the occurrence of secondary IFI in COVID-19 patients with low BMI (BMI < 28 kg/m
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