Background
Severe fever with thrombocytopenia syndrome (SFTS) is an infectious disease caused by neo-Bunia virus infection. It was initially suspected of human granulocytic anaplasmosis. It was not until 2009 that the pathogenic virus was isolated from the blood of a patient in rural areas of Henan Province and was named severe fever with thrombocytopenia syndrome virus (SFTSV) [
1]. Until now, cases have been reported in more than 20 provinces in China, as well as in Japan, South Korea and the United States [
2]. SFTS is transmitted mainly through tick bites, with an incubation period of about 7–14 days. It has also been reported that SFTS can be transmitted from person to person through contacts with a patient's blood or secretions [
3‐
5].The clinical manifestations of SFTS are not specific, including fever, gastrointestinal symptoms, nervous system symptoms, and decrease of white blood cell (WBC) and platelet (PLT) count. Severe patients can progress to multiple organ dysfunction syndrome (MODS) or even death. The case fatality rate of SFTS is 6.4–20.9% [
6,
7]. However, at present, there is no special treatment for SFTSV, such as specific antiviral drugs or vaccines, so it is particularly important to identify the severity of the disease and predict the prognosis of the disease as soon as possible.
Previous studies have shown that viral load, PLT, alanine aminotransferase (ALT), aspartate transaminase (AST), creatine kinase (CK), lactate dehydrogenase (LDH), prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer (D-D), blood urea nitrogen (BUN) and creatinine (Cr) are related to the prognosis of the disease [
8,
9]. It has been confirmed that the level of cystatin C (CysC) is related to the prognosis of many diseases, for example, the increase of CysC level can predict the adverse outcome of patients with COVID-19 and heart failure [
10,
11], it also means that stroke recurrence in patients with acute ischemic stroke and the increased risk of rehospitalization in patients with heart failure [
11,
12]. It is also a useful indicator for predicting renal prognosis, mortality and acute renal injury in patients with decompensated liver cirrhosis [
13,
14], and so on. But there is no research report on the relationship between CysC level and SFTS. Therefore, by collecting the clinical data of patients with SFTS, we explore the value of CysC level in evaluating the severity and prognosis of patients with SFTS, in order to provide some guidance for judging the condition and prognosis of patients with SFTS in clinical work.
Methods
Patients
From May 2017 to July 2020, 254 patients with SFTS were collected in the Department of Infectious Diseases, Union Hospital of Tongji Medical College. The enrolled patients were based on the following inclusion criteria: (1) age ≥ 18 years and ≤ 80 years, (2) detection of positive SFTSV ribonucleic acid by reverse-transcriptase polymerase chain reaction (RT-PCR). Patients who met any of the following criteria were excluded: (1) history of chronic kidney disease, (2) history of malignant tumor, (3) autoimmune diseases. According to the clinical manifestations, the patients were divided into two groups: general group and severe group, and the severe group cases were divided into survival group and death group according to the prognosis. The following information were collected and analyzed: demography, laboratory indicators (first blood examination during hospitalization), prognosis. We aimed to explore the value of CysC level in the evaluation of disease severity and prognosis in patients with severe fever with SFTS.
The research was approved by the Ethics Committee of Tongji medical college of Huazhong university of science and technology.
Statistical analysis
SPSS22.0 and GraphPad Prism 8.0 were used for statistical analysis. Continuous data following normal distribution were expressed the mean ± SD and compared using the t-test; the spacing median and quartile [M (P25 ~ P75)] was used to indicate the non-normal distribution and compared using the Mann–Whitney U test. Categorical data were expressed by rate, and compared using the χ2 test. The variables that were significant (P < 0.05) were incorporated into the binary Logistic regression model to obtain independent risk factors and draw the Receiver Operating Characteristic (ROC) curve to evaluate the value of CysC in evaluating the severity of the disease and prognosis. The best cut-off value was calculated according to the ROC curve, and the Kaplan survival Meier survival curve was drawn. Log-rank test was used to calculate the risk ratio (HR) and 95% confidence interval (95% CI). A two-tailed P value less than 0.05 was considered statistically significant.
Discussion
In our study, the clinical data of 254 patients with SFTS were analyzed retrospectively to explore the risk factors affecting the severity and prognosis of the disease. Many previous studies have shown that age is a risk factor for SFTS death [
15‐
17]. Similarly, the age of general group and fatal group in our study was significantly older than that of severe group and non-fatal group, which suggested that the elderly were more likely to develop into severe disease or even death, which may be related to decreased immunity, susceptibility to SFTSV and decreased organ function in the elderly.
SFTSV infection can directly or indirectly damage the function of multiple systems, like most viruses. We found that the viral load, ALT, AST were significantly correlated with the severity of SFTS and the prognosis of critically ill patients, which was consistent with the results of previous studies [
18,
19].
To our knowledge, this is the first time to study the relationship between CysC and SFTS. CysC is an endogenous cysteine protease inhibition [
20], which is easily detected in biological body fluids and has nothing to do with age, sex, diet, and muscle mass [
21]. CysC can regulate the immune response by inhibiting cathepsin activity, reducing MHC-II-mediated antigen presentation [
22] and regulating the function of natural killer cells [
23]. It can also induce macrophages to release nitric oxide, regulate the degradation of intracellular antigens, and cytokines in T cells and fibroblasts. Further regulate cell differentiation, proliferation and biological activity [
24‐
26]. It was found that the level of CysC was positively correlated with microinflammatory indexes such as interleukin (IL)-1β, IL-6, tumor necrosis factor (TNF)-α and C reactive protein (CRP) It was also suggested that the elevated level of CysC activated mononuclear macrophage system, endothelial cells or neutrophils to some extent, resulting in excessive release of inflammatory cytokines (such as IL-6, TNF, etc.), thus promoting the occurrence of inflammatory reaction [
27]. Therefore, high levels of CysC may reflect high levels of inflammation and immune response in the body.
We found that the level of CysC was significantly correlated with the severity and prognosis of SFTS. The risk of death in high CysC group (≥ 1.23 mg/L) was significantly higher than that in low CysC group (< 1.23 mg/L) (HR = 5.487), and other renal function indexes were not independent risk factors for disease severity and risk of death. At the same time, previous studies have found the association between septicemia and high serum CysC levels, and the association trend between Acute Physiology and Chronic Health Evaluation II(APACHE II) and cystatin C [
28], which may represent direct and indirect inflammation, as some authors have suggested, CysC may reflect the pathogenic state other than GFR [
29]. Therefore, CysC, as an index that is easy to detect and relatively unaffected, can provide a certain value in judging the severity and prognosis of patients with SFTS, which undoubtedly provides a more convenient basis for clinical work to judge the severity of the disease and prognosis. However, the role and regulatory mechanism of CysC in SFTS need to be further studied and verified.
However, this study also has some limitations. First, this study is a single-center retrospective study. Some patients were not included in the study due to the lack of data, which means there is a certain selection bias. Secondly, there is no dynamic monitoring of laboratory indicators to better judge the relationship between index changes and diseases. Finally, the collection of cases is limited, and the representativeness of the results needs to be further expanded to verify the sample.
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