Early-Warning Immune Predictors for Invasive Pulmonary Aspergillosis in Severe Patients With Severe Fever With Thrombocytopenia Syndrome

Abstract

Aspergillus-related disease was confirmed to be associated with immune disorders in patients, severe patients with severe fever with thrombocytopenia syndrome (SFTS) infected by novel phlebovirus were confirmed to have severe immune damage including cellular immunosuppression and cytokine storms. Secondary invasive pulmonary aspergillosis (IPA) in severe SFTS patients can increase fatality rate. This study investigated early-warning predictive factors of secondary IPA in severe SFTS patients. Receiver operating characteristic analysis was used to assess the value of immune parameters to predict IPA in SFTS patients. The cut-off values of CD4+ and CD8+ T-cell counts to predict IPA were 68 and 111 cells/mm3, with sensitivities of 82.6% and 72%, and specificities of 56.7% and 83.3%, respectively. Cut-off values of IL-6, TNF-α, IL-8, and IL-10 to predict IPA incidence in critically ill SFTS patients were 99 pg/mL, 63 pg/mL, 120 pg/mL, and 111 pg/mL, with sensitivities of 90.0%, 86.7%, 83.3% and 90.0% and specificities of 80.4%, 71.7%, 82.6% and 65.2%, respectively. Lower CD4+ and CD8+ T-cells counts, higher levels of IL-6, TNF-α, IL-8 and IL-10, higher incidence of pancreatic and renal damage, early antibacterial therapy of carbapenems, and intensive care unit admission were risk factors of IPA in SFTS patients. Multivariate logistic regression analysis indicated counts of CD4+ T-cells <68 cells/mm3 combined with CD8+ T-cells <111 cells/mm3 (odds ratio [OR] 0.218, 95% confidence interval [CI] 0.059–0.803, p=0.022), IL-6 >99 pg/ml combined with IL-10 >111 pg/ml (OR 17.614, 95% CI 2.319–133.769, p=0.006), and brain natriuretic peptide level >500 pg/ml (OR 13.681, 95% CI 1.994–93.871, p=0.008) were independent risk factors for IPA in SFTS patients. The mortality in the IPA group was significantly higher than in the non-IPA group (p=0.001). Early antifungal treatment of IPA patients was significantly associated with improved survival (log-rank, p=0.022). Early diagnosis of IPA and antifungal treatment can improve the prognosis of SFTS patients. Besides, we speculate SFTS may be as a host factor for IPA.

Associated microbiota and treatment of severe fever with thrombocytopenia syndrome complicated with infections

“…Use of antifungal drugs 25 ( Several studies have revealed that SFTSV infection is complicated by fungus-related co-infections (such as candidiasis and pulmonary aspergillosis). 7,9,12 This investigation revealed that A.…”

“…Various studies have reported an 8%–30% incidence of co‐infections among SFTS patients, however, it is unknown whether these infections are bacterial or fungal 4–6 . SFTSV infection has been documented to be worsened by fungal co‐infections like pulmonary aspergillosis and candidiasis 7–10 . Due to the severity of SFTS patients and the challenge of excluding an associated co‐infection based on clinical, radiological, or laboratory evidence, the majority of patients with SFTS were effectively treated with antibiotics following admission.…”

Overview of the immunological mechanism underlying severe fever with thrombocytopenia syndrome (Review)

“…A number of studies previously demonstrated that cd3 + , cd4 + , and cd8 + T cells are diminished in patients with SFTS (94)(95)(96)(115)(116)(117)(118)(119) and in experimental animal models (103). Sun et al (94) revealed a significant decline in CD3 + and cd4 + expression in the peripheral blood of patients with SFTS, where the average leukocyte count was 2.86±1.56x10 9 /l.…”

NLR, A Convenient Early-Warning Biomarker of Fatal Outcome in Patients With Severe Fever With Thrombocytopenia Syndrome

“…A major challenge is recognizing and treating critically ill patients and those who may die from SFTS. Even though there are already some studies describing the characteristics, predictors, or treatments of SFTS, most of them only discussed the association between fatal outcomes and various indicators, such as viral load, gender, comorbidities, age, and immune predictors that need special detection (He et al, 2020 ; Hu et al, 2021b ; Zhao et al, 2021 ). In addition, several studies tried to establish a special score model to forecast poor prognosis, which seemed difficult to count and limited in generalization (Wang et al, 2019 ).…”