• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Virol J . Risk factors for intensive care unit coronavirus disease 2019 pneumonia-associated invasive fungal infections: a Bayesian evidence synthe

tetano

Editor, Senior Moderator
Virol J


. 2026 Apr 28.
doi: 10.1186/s12985-026-03183-5. Online ahead of print.
Risk factors for intensive care unit coronavirus disease 2019 pneumonia-associated invasive fungal infections: a Bayesian evidence synthesis integrating external and real-world data

Chengyu Wang[SUP] 1 [/SUP], Huangxin Gong[SUP] 1 [/SUP], Jiatian Wang[SUP] 1 [/SUP], Ting Yang[SUP] 1 [/SUP], Yuan Wu[SUP] 2 [/SUP], Yan Wang[SUP] 1 [/SUP], Yan Cai[SUP] 3 [/SUP]


Affiliations
Abstract

Background: The incidence of Coronavirus Disease 2019 (COVID-19) pneumonia-associated Invasive Fungal Infections (IFI) has risen markedly. However, current evidence regarding associated risk factors remains inconsistent across studies and limited by small sample sizes, underscoring the need for systematically integrated evidence.
Methods: This retrospective study integrated published external evidence with Real-World Data (RWD) within a Bayesian framework to derive more accurate and robust estimates of potential risk factors for IFI associated with COVID-19 pneumonia in Intensive Care Unit (ICU) patients.
Results: Based on the study-derived prior distributions for 25 potential risk factors, the Bayesian integrated analysis further suggested that male sex, advanced age, diabetes mellitus, chronic pulmonary disease, hepatic or renal dysfunction, malignancy, increased disease severity (Sequential Organ Failure Assessment (SOFA) scores, Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, and Charlson Comorbidity Index (CCI)), and prolonged mechanical ventilation were possible associated with IFI in ICU patients with COVID-19 pneumonia. In addition, prior glucocorticoid exposure, high-dose and prolonged glucocorticoid therapy, vasopressor use, renal replacement therapy, and mechanical ventilation were also potentially linked to higher IFI incidence. Subgroup analyses revealed that factors associated with Aspergillus infection in COVID-19 patients were largely consistent with the overall cohort.
Conclusion: This observational study systematically explored potential factors associated with IFI in ICU patients with COVID-19 pneumonia by integrating published external evidence with RWD within a Bayesian framework, thereby providing more reliable evidence to support early identification and prevention in high-risk individuals.

Keywords: Bayesian integration; COVID-19; Invasive Fungal Infections; Risk factors.

 
Back
Top