Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with the high case-fatality rate, and lack of vaccines. We aimed to systematically analysed the epidemiological characteristics, clinical signs, routine laboratory diagnosis, risk factors, and outcomes. Methods: Documents on SFTS were collected by searching the Chinese National Knowledge Infrastructure, Wan Fang Data, PubMed, Embase, and Web of Science databases from 2011 to 2018. Meta-analysis was performed by using Review Manager and Stata software. Results: Twenty-five articles involving 4143 cases were included. Diarrhea (odds ratio (OR) =1.60, 95% confidence interval (CI): 1.06 to 2.42, P = 0.02), and vomiting (OR = 1.56, 95% CI: 1.01 to 2.39, P = 0.04) on admission were associated with the fatal outcomes of SFTS. Compared to patients with mild symptoms, patients with severe symptoms had significantly elevated levels of lactic acid dehydrogenase (standard mean difference (SMD) =1.27, 95% CI: 0.59 to 1.94), alanine aminotransferase (SMD = 0.55, 95% CI: 0.24 to 0.85), aspirate aminotransferase (SMD = 1.01, 95% CI: 0.69 to 1.32), and creatine kinase (SMD = 1.04, 95% CI: 0.74 to 1.33) but had reduced platelet counts (SMD =-0.87, 95% CI: − 1.16 to − 0.58) and albumin levels (SMD =-1.00, 95% CI: − 1.32 to − 0.68). The risk factors for poor prognosis included age (mean difference (MD) =6.88, 95% CI: 5.41 to 8.35) and farming (OR = 2.01, 95% CI: 1.06 to 3.80). For the risk factors of contracting SFTS, the incidence of SFTS related to tick bites was 24% [95% CI: 0.18 to 0.31]. The pooled case-fatality rate of SFTS patients was 18% [95% CI: 0.16 to 0.21].

Severe fever with thrombocytopenia syndrome (SFTS) is recognized as an emerging infectious disease. This study aimed to investigate the pathogenic mechanism of SFTS. A total of 100 subjects were randomly included in the study. Cytokine levels were detected by enzyme‐linked immunosorbent assay and the viral load was detected by micro drop digital PCR. The results showed that levels of interleukin‐6 (IL‐6), IL‐8, IL‐10, IFN‐inducible protein‐10 (IP‐10), monocyte chemoattractant protein‐1 (MCP‐1), macrophage inflammatory protein‐1α (MIP‐1α), transforming growth factor‐β1 (TGF‐β1), and regulated upon activation normal T cell expressed and secreted factor (RANTES) differed significantly among the SFTS patient group, healthy people group, and asymptomatic infection group (p < .05). Compared to the healthy people group, the patient group had increased cytokine levels (IL‐6, IL‐10, IP‐10, MCP‐1, and IFN‐γ) but reduced levels of IL‐8, TGF‐β1, and RANTES (p < .0167). IL‐6, IL‐8, IL‐10, IP‐10, MCP‐1, MIP‐1α, TGF‐β1, and the RANTES levels had different trends after the onset of the disease. IL‐6, IL‐10, IP‐10, and MCP‐1 levels in severe patients were higher than those in mild patients (p < .05). There was a positive correlation between viral load and IL‐6 and IP‐10 but a negative correlation between viral load and RANTES. SFTSV could cause a cytokine change: the cytokine levels of patients had different degrees of fluctuation after the onset of the disease. The levels of IL‐6 and IL‐8 in the asymptomatic infection group were found between the SFTS patients group and the healthy people group. The levels of IL‐6, IL‐10, IP‐10, and MCP‐1 in the serum could reflect the severity of the disease, and the levels of IL‐6, IP‐10, and RANTES were correlated with the viral load.

Background Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease with a fatality of up to 30%. To identify the severity of SFTS precisely and quickly is important in clinical practice. Methods From June to July 2020, 71 patients admitted to the Infectious Department of Joint Logistics Support Force No. 990 Hospital were enrolled in this study. The most frequently observed symptoms and laboratory parameters on admission were collected by investigating patients’ electronic records. Decision trees were built to identify the severity of SFTS. Accuracy and Youden’s index were calculated to evaluate the identification capacity of the models. Results Clinical characteristics, including body temperature (p = 0.011), the size of the lymphadenectasis (p = 0.021), and cough (p = 0.017), and neurologic symptoms, including lassitude (p<0.001), limb tremor (p<0.001), hypersomnia (p = 0.009), coma (p = 0.018) and dysphoria (p = 0.008), were significantly different between the mild and severe groups. As for laboratory parameters, PLT (p = 0.006), AST (p<0.001), LDH (p<0.001), and CK (p = 0.003) were significantly different between the mild and severe groups of SFTS patients. A decision tree based on laboratory parameters and one based on demographic and clinical characteristics were built. Comparing with the decision tree based on demographic and clinical characteristics, the decision tree based on laboratory parameters had a stronger prediction capacity because of its higher accuracy and Youden’s index. Conclusion Decision trees can be applied to predict the severity of SFTS.