Prognostic value and dynamic change characteristics of cytokines in Severe fever with thrombocytopenia syndrome

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This study focuses on the predictive value and trend of cytokines in SFTS. Methods: Information of 128 SFTS patients retrospectively collected from January 2019 to January 2022 from a large general hospital in Anhui Province, China. Multivariate Cox model was used to identify predictors of death, ROC curve was used to calculate the value of predictors. Linear regression analysis was used to explore the correlation between cytokines and viral titers. Dynamic changes in cytokines to demonstrate therapeutic significance. Results: Of the 128 patients diagnosed with SFTS, 34 died during the course of the disease. Cytokines were significantly higher in the non-survival group than the survival group, while CD4 and CD8 counts were lower in the non-survival group. Multivariate Cox analysis showed that TNF-α was an independent predictor of death ( p = 0.038, HR = 12.78) with an AUC value of 0.901. TNF-α, IL-6, IL-10 and IL-8 were correlated with viral titer ( p < 0.001, 0.5 < r < 1). Different cytokines showed different trends in the course of treatment. High dose gamma-globulin shock therapy combined with ribavirin can effectively reduce the level of some cytokines (IL-6, IL-2R, IL-10). Conclusion: TNF-α is an independent predictor of SFTS death outcome and has excellent predictive value. There was a significant correlation between TNF-α, IL-6, IL-10, IL-8 and virus titer. Gamma-globulin shock therapy combined with ribavirin can control cytokine storm to some extent and provide new ideas for clinical treatment. Severe fever with thrombocytopenia syndrome (SFTS) Cytokines Viral titers. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Severe fever with thrombocytopenia syndrome (SFTS) is a seasonal infectious diseases caused by a pathogen called SFTS virus (1), which can cause a range of clinical signs including fever, thrombocytopenia, nausea, vomiting, and abnormal laboratory parameters. SFTS in humans is mainly transmitted by contact with ticks, but has also been reported to be transmitted by blood and aerosols (2, 3). Since it was first discovered in central China in 2009, it has gradually expanded to the whole country and even to other countries. The mortality in China has dropped from 30% at the beginning to about 10% recently (4, 5). There are no specific drugs for SFTS treatment, clinicians mainly provide symptomatic and supportive treatment based on patient signs. Although ribavirin has been approved for the treatment of SFTS virus infection, most results have not shown significant efficacy (6, 7). Cytokine storm is a general term for a several immune disorders (8). Interferon-γ, interleukin-1, interleukin-6, TNF and interleukin-18 are the key cytokines with elevated levels in the cytokine storm, whose increased circulating levels can eliminate pathogens and control infections. But sustained excessive increases can cause additional damage to organs. Certain microbial and viral infection may also lead to cytokine storms, including SFTS, which have been hotly debated by scholars in recent years (9–11). Studies have shown that cytokines exhibit unique trends in SFTS and show more extreme levels in fatal cases (12). However, relevant studies are still limited and studies at different levels in different regions are needed to further explore the relationship between the two. In this study, we aimed to analyze the predictive value of cytokine levels for death outcomes in SFTS and to establish a prognostic model to find valuable predictors. In addition, the role of cytokines in the occurrence and development of diseases was further explored by analyzing the correlation between cytokines and virus titers and their dynamic changes. The search for new treatment methods was also the focus of this study. Methods Patients and samples In this retrospective study, 128 patients were enrolled in this study at the First Affiliated Hospital of Anhui Medical University in Hefei, Anhui Province from January 1, 2019 to January 1, 2022. Patients who were included had the following conditions:(1) acute onset of high fever (≥ 37.5°C) for over 24h, (2) had reduced platelet count in peripheral blood in laboratory tests (PLT < 100×10 9 /L), (3) Positive SFTS virus RNA in blood confirmed by reverse transcription-polymerase chain reaction (RT-PCR) on admission, (4) Cytokine levels were performed on admission. Patients with hematologic disorders, autoimmune diseases, or had been treated with blood product stimulating factors were excluded. This study was approved by the Ethics Committee of the First Affiliated Hospital of Anhui Medical University. Data Collection Clinical data were obtained from the hospital electronic medical system. Clinical parameters include: age, sex, length of hospitalization, medical costs, Patient signs and treatment. laboratory indicators of white platelet count (PLT), Tumor Necrosis Factor α (TNF-α), Interleukin-6 (IL-6), Interleukin-8 (IL-8), Interleukin-10 (IL-10), Interleukin-2R (IL-2R), Interleukin-1B (IL-1B), CD4 and CD8 counts, serum SFTSV viral titers were collected as the first test data after admission. In addition, we collected the cytokine levels of 50 patients before and after treatment, of which 15 patients were tested every three days and monitored five times in a row. Death was defined as death during the course of the disease. Statistical analysis All data were statistically analyzed using SPSS 16.0 and PRISM (version 8). Quantitative data are expressed as mean ± standard deviation or median (interquartile range). Variables that conform to a normal distribution are tested using a t-test, while those that do not conform used a non-parametric test. Qualitative data were expressed as ratios and compared by chi-square or Fisher's exact test. P < 0.05 denote statistical significance. Risk factors were identified by univariable and multivariable Cox regression analyses for predicting mortality, and the results are expressed as adjusted Hazard ratio (HR) and 95% confidence intervals (95% CI). Predictive value of mortality-related predictors assessed by receiver operating characteristic (ROC) curves. Spearman's test was used to calculate the correlation coefficient between cytokines and viral titers. Results Characteristics of patients A total of 128 patients with SFTS diagnosed from the First Affiliated Hospital of Anhui Medical University in Hefei, Anhui Province were collected from January 2019 to January 2022. Of these, 52 patients were quantified for SFTS virus RNA on admission, and a total of 34 patients died during the course of the disease, with a mortality rate of 26.6%. The median age in the non-survival group was 65, higher than 61 in the survival group, and was statistically significant ( p = 0.006). There were 24 (67.7%) females in the death group much higher than males. All patients presented with fever on admission. Fatigue was the most common sign, followed by myalgia and diarrhea and abdominal pain. In addition, the incidence of central nervous system symptoms and multiple organ failure was much higher in the non-survival group, central nervous system symptoms mainly including headache and convulsions (Table 1 ). Table 1 Differences in clinical and laboratory characteristics between SFTS-survivors and non-survivors. Variable Total (n = 128) non-survivor (n = 34) survivor(n = 94) P value Demographic Age (median, IQR) 63 (27–63) 65 (45–88) 61 (27–80) 0.006 gender 50 (73.8) 10 (32.3) 40 (43.5) 0.271 Total hospital stay, days (median, IQR) 10 (3–39) 6 (3–39) 10 (4–34) < 0.001 Medical costs, Renminbi (RMB) 33585 (2306-197799) 35200 (6198-197799) 29466 (2306-107767) 0.380 Time from start of fever to hospital admission 5 (1–15) 4 (1–10) 5 (1–15) 0.731 Symptoms or signs Fatigue 77 (60.2) 17 (50.0) 60 (63.8) 0.158 Myalgia 49 (38.3) 13 (38.2) 36 (38.3) 0.995 Nausea 42 (32.8) 10 (29.4) 32 (34.0) 0.622 Vomiting 35 (27.3) 7 (20.6) 28 (29.8) 0.302 CNS manifestations 35 (27.3) 17 (50.0) 18 (19.1) 0.001 Ecchymosis 11 (8.7) 4 (11.8) 7 (7.5) 0.452 Diarrhoea and Abdominal pain 58 (45.3) 15 (44.1) 43 (45.7) 0.870 MOF 15 (11.8) 15 (45.5) 0 (0) < 0.001 Laboratory variables from blood, Mean ± SD PLT (10 9 /L) 65.10 ± 52.82 57.35 ± 55.17 67.90 ± 51.96 0.035 Viral titers (TCID50/ml) 35389 ± 159785 137530 ± 329270 5735 ± 15511 0.008 Treatment Ribavirin 13 (10.5) 0 (0) 13 (14.4) Gamma-globulin shock therapy 19 (15.3) 9 (26.5) 10 (11.1) Gamma-globulin shock therapy combined with ribavirin 92 (74.2) 25 (73.5) 67 (74.4) 0.013 Cytokines, Mean ± SD CD4 (cells/µL) 214.88 ± 178.63 120.65 ± 90.37 245.50 ± 189.61 0.001 CD8 (cells/µL) 225.33 ± 273.77 125.91 ± 130.40 257.63 ± 298.59 0.002 CD4/CD8 1.35 ± 0.92 1.27 ± 0.73 1.35 ± 0.98 0.985 TNF-α 48.31 ± 154.33 138.20 ± 278.50 15.46 ± 10.06 < 0.001 IL-6 44.55 ± 127.29 127.33 ± 227.70 14.61 ± 17.78 < 0.001 IL-10 90.37 ± 190.45 187.38 ± 219.57 55.28 ± 113.70 < 0.001 IL-8 84.16 ± 415.31 250.22 ± 798.17 24.61 ± 16.30 < 0.001 IL-2R 1340.35 ± 927.59 2341.30 ± 1672.34 1064.96 ± 561.61 < 0.001 IL-1B 17.50 ± 20.12 20.36 ± 29.48 9.95 ± 7.26 0.014 The platelet count in the non-survival group was significantly lower than that in the survival group ( p = 0.035), while the viral titer was higher than that in the survival group ( p = 0.008). In terms of treatment, the three treatments of ribavirin, gamma-globulin shock therapy, and gamma-globulin shock therapy combined with ribavirin therapy were significantly different between the two groups ( p = 0.013). Cytokine Characteristics Of Sfts Patients And Predictors Associated With Lethal Outcome Each patient was detected six cytokine levels as well as CD4 and CD8 counts on admission. Significant differences between the non-survival group and the survival group were showed from results (IL-1B: p = 0.013, other five cytokines: p < 0.001). The quantitative results of the non-survival group were much higher than those of the survival group, while the CD4 and CD8 counts of the death group were lower than those of the survival group (CD4: p = 0.001, CD8: p = 0.002). In addition, the values of other cytokines except IL-8 in the two groups were much higher than the normal reference interval, while the IL-8 in the survival group was almost within the normal range, and the non-survival group showed a higher trend. We included six cytokines, CD4 and CD8 counts, and age and sex into the Cox regression model (Table 2 ). The variable which p < 0.05 in univariate analysis, as well as corrective factors age and sex into multivariate analysis. The dichotomous threshold of the blood test is based on the cut-off point of the ROC curve. TNF-α was shown to be an independent predictor of death ( p = 0.038, HR = 12.78). To assess the predictive value of cytokine levels on the lethal outcome of SFTS, we performed a ROC analysis of TNF-α, and the result showed an AUC value of 0.901, which has an excellent predictive value (Fig. 1). Kaplan-Meier survival curves were used to confirm that patients with TNF-α above 20.15 pg/ml had a significant increase in mortality (Fig. 2). Table 2 Univariable and multivariable Cox regression analyses of features associated with fatal outcomes in patients with SFTS Variable Univariate analysis Multivariate analysis HR 95%CI for HR P value HR 95%CI for HR P value Sex, male vs female 0.69 0.32–1.47 0.337 Age, year, ≥ 65 vs < 65 1.03 0.99–1.07 0.072 CD4, /µL, < 207 vs ≥ 207 6.68 1.56–28.52 0.010 CD8, /µL, < 144 vs ≥ 144 4.24 1.58–11.34 0.004 TNF-α, pg/ml, ≥ 20.15 vs < 20.15 16.45 5.01–54.06 < 0.001 12.78 1.16-141.31 0.038 IL-6, pg/ml, ≥ 17.15 vs < 17.15 17.37 5.28–57.10 < 0.001 IL-10, pg/ml, ≥ 77.7 vs < 77.7 7.49 3.45–16.24 < 0.001 IL-8, pg/ml, ≥ 32.55 vs < 32.55 7.47 3.15–17.72 < 0.001 IL-2R, U/ml,, ≥ 1253 vs < 1253 8.96 3.08–26.09 < 0.001 IL-1B, pg/ml, ≥ 12.9 vs < 12.9 2.03 0.95–4.34 0.068 The Change Trend Of Cytokines And Its Correlation With Viral Titers 15 patients were dynamically monitored for cytokine levels every three days after admission, and their conditions eventually improved. As shown in Fig. 3, TNF-α, IL-2R and IL-1B peaked at 4–6 days after admission and then gradually decreased, while IL-6 and IL-8 peaked at 7–9 days and then decreased. It is noteworthy that IL-10 has been steadily decreasing after admission. We also found that IL -8 fluctuated within the normal range throughout the change except for a few values. In addition, TNF-α, IL-6 and IL-8 showed a small increase after 13 days. By comparing cytokine levels before and after treatment in 50 patients who had received gamma-globulin shock therapy in combination with ribavirin, IL-6 ( p = 0.049), IL-2R ( p = 0.006), IL-10 ( p = 0.005) decreased significantly after treatment, while the changes in TNF-α, IL-1B, 1L-8 were not statistically significant, and even IL-1B mostly had an upward trend (Fig. 4). The linear relationship between cytokines and viral titers was also analyzed. TNF-α, IL-6, IL-8 and IL-10 were positively correlated with viral titers ( p < 0.001, 0.5 < r < 1), while IL-2R and IL-1B were not (Fig. 5). Discussion At present, SFTS is a new infectious disease which attracts much attention. Up to now, there is no specific drug to treat it. Ribavirin, Favipiravir and other antiviral drug are commonly used in clinic (13). It is well known that the immune response is essential for the body to fight against viral infections, however, excessive immune responses can trigger cytokine storms that can cause further organ damage and lead to adverse outcomes (14). Therefore, controlling cytokine storms is also necessary to reduce mortality of viral infectious diseases, including SFTS. In this study, patient information was collected from 2019 to 2022 at one of the top two large general hospitals in Anhui Province. Anhui Province is a region with high incidence of SFTS (15), the mortality rate in our study is 26.6%, which is consistent with the data reported in recent years (16). We found that there were far more females than males among the patients who died, this result varied among studies (17, 18). This may be due to that in Anhui province, SFTS patients are mostly tea pickers from rural areas, and this occupation is mostly female. The older age of the deceased patients is indeed due to that older patients tend to have more underlying diseases and comorbidities, and a weaker immune system aggravates the poor prognosis. Thrombocytopenia is an important feature of SFTS. In our analysis, platelet levels showed lower values in the non-survival group, therefore were closely associated with death as well as disease severity. In addition, viral titers at hospital admission were much higher in the non-survival group, even up to hundreds of thousands of times, and most studies have confirmed that viral load is a serious threat to mortality outcomes(19, 20). Our study also found that the central nervous system symptoms of the deceased patients were significantly different from those of the survival group, with most patients presenting headaches, convulsions and even coma after admission, which further aggravated the development of the disease. Cytokines play an important role in immune regulation and immune response. Many studies have shown that the cytokine level in SFTS patients is significantly higher than that in healthy people, and it is even more obvious in dead patients, which is also confirmed by our study (21–23). High cytokine levels in dead patients are likely to cause systemic inflammatory symptoms and further organ failure, which may be a major cause of death. Most studies have reported the difference of cytokines in SFTS patients compared with healthy people or between severe and non-severe patients. Few studies have explored the predictive value of cytokines in death outcome (24). TNF-α is a cytokine with multiple functions, mainly including homeostatic functions of immune regulation, defense against pathogens, inhibition of tumorigenesis, and pathogenic functions such as induction of inflammatory mediators and induction of tissue degeneration (25). A recent study indicated that TNF-α was an independent predictor of death in patients with COVID-19 (26). In our study, TNF-α plays a very significant prognostic factor role in cytokines and has a high predictive value. IL-6 and IL-10 had also been shown to be good predictors of poor prognosis of SFTS (27). These findings suggest that cytokines are of great value in the prediction of SFTS prognosis. In our study, levels of all six cytokines were significantly higher in dead patients than in survivors, the levels of IL-8 were in the normal range in most of the patients in both groups, while the levels of other five cytokines were much higher than the normal range. This may be because IL-8 is a chemokine whose primary role is to attract leukocytes to infiltrate in inflammatory or tumor tissues [ 28 ], whereas SFTS is a systemic reactive disease, the absence of a specific immune target reduces the action of chemokines so that they do not change much. IL-8 levels have even been reported to be lower in SFTS patients than in the healthy population (29). Likewise, the reduced CD4 and CD8 counts in the dead patients were a sign of immune suppression after viral infection, which was also showed in previous studies (30). In the trend of cytokine changes, TNF-α, IL-2R and IL-1B reached the peak at 4–6 days after admission, while IL-6 and IL-8 increased slowly. Interestingly, IL-10 tended to decline after admission until it finally returned to the normal reference range, which is quite different from He et al (29). We speculated that this might be because the 15 patients with dynamic cytokine changes collected in this study were treated with cyclic gamma-globulin combined with ribavirin immediately after admission. In our study, we found that the change of IL-10 was the most significant before and after treatment, which can be inferred that IL-10 is the most sensitive to this kind of treatment. Unfortunately, patients in the non-survival group died within a relatively short period of time after readmission so the dynamic pattern of their cytokine levels was not monitored and the differences between the two groups could not be compared. In this study, we found that TNF-α, IL-6, IL-10, and IL-8 were significantly correlated with viral titers, which indicated that viral replication with high copy number could induce cytokine release in vivo, which was also confirmed by previous studies(12, 29). However, significant correlations between TNF-α and IL-8 and viral load have not been reported. At present, the treatment of SFTS is the focus of attention and needs to be urgent solved. Most current reports focus on ribavirin and other common antiviral drug, and the effect is not significant (31). In China, high-dose gamma-globulin shock therapy is a common treatment, although it is rarely reported (5). As an immunomodulator, gamma-globulin can enhance the function of phagocytes, help to eliminate pathogenic bacteria, at the same time significantly reduce the secretion of inflammatory cytokines, and inhibit the body's inflammatory response (32). In this study, high-dose gamma-globulin shock therapy combined with ribavirin treatment had a significant effect on the reduction of some cytokines (IL-10, IL-2R, IL-6), and since almost all patients were treated with the combination, no difference in efficacy was seen between the non-survival and survival groups. The dose and duration of gamma-globulin shock therapy needs to be explored in studies with larger samples. Nonetheless, the study has some limitations. First of all, the viral titer is only detected at admission, and there is no subsequent dynamic monitoring to better explore the correlation between it and cytokines. Secondly, due to the limitation of sample testing, this study included fewer cytokines, which failed to explore their development and predictive value in disease more comprehensively. In the future, the sample size and testing items will be expanded to continue to explore. Conclusion The levels of cytokines TNF-α, IL-6, IL-8, IL-10, IL-2R and IL-1B were significantly higher in patients with SFTS death than in surviving patients. TNF-α is an independent predictor of death and having a high predictive value. Different cytokines had different trends during the course of the disease and some cytokines (TNF-α, IL-6, IL-8, IL-10) were correlated with viral titers. The combination of gamma-globulin and ribavirin could control the cytokine storm to a limited extent, but only showed significant efficacy in some cytokines (IL-6, IL-10, IL-2R), and its therapeutic value needs to be further investigated. Declarations Ethical Statement This study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Anhui Medical University. The written informed consent was obtained from patients in accordance with the Declaration of Helsinki. Consent for publication Not applicable Data Availability Statement The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request. Funding This work was financially supported by Anhui Natural Science Foundation (grant number: 9021138201). Conflict of Interest The authors declare that they have no competing interests. Author Contributions DML: concept and writing of the manuscript. TM and LWZ: data processing and software. YZ and YHX: review and editing. All authors contributed to the article and approved the submitted version. Acknowledgments We would like to thank the First Affiliated Hospital of Anhui Medical University staffs for their support in sample and clinical data collections. References Yu XJ, Liang MF, Zhang SY, Liu Y, Li JD, Sun YL, et al. Fever with thrombocytopenia associated with a novel bunyavirus in China. N Engl J Med. 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Severe fever with thrombocytopenia syndrome virus: a highly lethal bunyavirus. CRIT REV MICROBIOL. [Journal Article; Review]. 2021 2021-02-01;47(1):112–25. Yang L, Wu EY, Tarrant TK. Immune Gamma Globulin Therapeutic Indications in Immune Deficiency and Autoimmunity. Curr Allergy Asthma Rep. [Journal Article; Review]. 2016 2016-07-01;16(8):55. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2251280","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":150762630,"identity":"ab337094-c8ce-4689-a9b0-c7701a7b3587","order_by":0,"name":"Dongmei Lv","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Dongmei","middleName":"","lastName":"Lv","suffix":""},{"id":150762631,"identity":"40f3d906-e340-4bd3-83b5-a069cb18a4b3","order_by":1,"name":"Tao Meng","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tao","middleName":"","lastName":"Meng","suffix":""},{"id":150762632,"identity":"c257a578-ac11-43fa-85ce-54fe38e21799","order_by":2,"name":"Luwen Zhang","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Luwen","middleName":"","lastName":"Zhang","suffix":""},{"id":150762633,"identity":"5b1681d7-4f60-4047-90c0-43af461557cc","order_by":3,"name":"Yan Zuo","email":"","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Zuo","suffix":""},{"id":150762634,"identity":"8c061746-7528-4a85-91a4-40921ba80d3e","order_by":4,"name":"Yuanhong Xu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYFACHhAhIcfPcPjAgQ8/iNdiYSzZeCzx4Mwe4rVUJG5oPmN8mIONCA0GN3IPPi74JZG4ge3Mh8NA/fL8Ygfwa5GckZdsPLNPwng7z9kNhwssGAxnzk7Ar4VfIsdMmrdHQnbnDKCWGTwMCQa3CWhhg2ph3HD/zYPDPGxEaAHbwvNDQnHDgTMMxGmR7HljbMzbIGEs2XDMABjIEoT9YnA8x/Axz586UFQ+/vDhh408vzQBLQwCQAWMbXCuBAHlIMB/AEj8IULhKBgFo2AUjFwAACiCSRpoeyBPAAAAAElFTkSuQmCC","orcid":"","institution":"the First Affiliated Hospital of Anhui Medical University","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Yuanhong","middleName":"","lastName":"Xu","suffix":""}],"badges":[],"createdAt":"2022-11-08 13:14:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2251280/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2251280/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":29031397,"identity":"767695b0-fe31-43b8-9d6c-ee3b76276ea1","added_by":"auto","created_at":"2022-11-14 15:17:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":50503,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic curve analysis of TNF-α to predict death outcome of patients with severe fever with thrombocytopenia syndrome.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/cfc63abaec730857f726fcce.png"},{"id":29031398,"identity":"035c9550-44bc-4831-9b97-7302c79d21df","added_by":"auto","created_at":"2022-11-14 15:17:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":243776,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan–Meier survival plots.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/a5471179d89fc58d9618ca1f.png"},{"id":29031400,"identity":"347f79b9-a3b2-4573-a55f-68d37e979109","added_by":"auto","created_at":"2022-11-14 15:17:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":163452,"visible":true,"origin":"","legend":"\u003cp\u003eDynamic changes in serum cytokines after admission in 15 surviving SFTS patients.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/595578193fbfa4ea6ee3a15e.png"},{"id":29032331,"identity":"48ac92e5-2eaf-4a61-b27a-131b20a47d10","added_by":"auto","created_at":"2022-11-14 15:25:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":5713,"visible":true,"origin":"","legend":"\u003cp\u003eChanges in serum cytokine levels in SFTS patients before and after treatment.\u003c/p\u003e","description":"","filename":"placeholderimage.png","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/478e319b8c6d3cf615856d33.png"},{"id":29031404,"identity":"9e6857bf-b654-41c6-9339-771a6eaf1983","added_by":"auto","created_at":"2022-11-14 15:17:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":184140,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between viral titers and cytokines.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/3d2ca87c5581fa33bb9c3048.png"},{"id":33903353,"identity":"9743f475-2058-4b3a-a1b4-59bb531ddbed","added_by":"auto","created_at":"2023-03-07 14:29:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":864625,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2251280/v1/ac5edbf3-9ad2-4f11-8627-abfe1f22eee3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic value and dynamic change characteristics of cytokines in Severe fever with thrombocytopenia syndrome","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSevere fever with thrombocytopenia syndrome (SFTS) is a seasonal infectious diseases caused by a pathogen called SFTS virus (1), which can cause a range of clinical signs including fever, thrombocytopenia, nausea, vomiting, and abnormal laboratory parameters. SFTS in humans is mainly transmitted by contact with ticks, but has also been reported to be transmitted by blood and aerosols (2, 3). Since it was first discovered in central China in 2009, it has gradually expanded to the whole country and even to other countries. The mortality in China has dropped from 30% at the beginning to about 10% recently (4, 5). There are no specific drugs for SFTS treatment, clinicians mainly provide symptomatic and supportive treatment based on patient signs. Although ribavirin has been approved for the treatment of SFTS virus infection, most results have not shown significant efficacy (6, 7).\u003c/p\u003e \u003cp\u003eCytokine storm is a general term for a several immune disorders (8). Interferon-γ, interleukin-1, interleukin-6, TNF and interleukin-18 are the key cytokines with elevated levels in the cytokine storm, whose increased circulating levels can eliminate pathogens and control infections. But sustained excessive increases can cause additional damage to organs. Certain microbial and viral infection may also lead to cytokine storms, including SFTS, which have been hotly debated by scholars in recent years (9\u0026ndash;11). Studies have shown that cytokines exhibit unique trends in SFTS and show more extreme levels in fatal cases (12). However, relevant studies are still limited and studies at different levels in different regions are needed to further explore the relationship between the two.\u003c/p\u003e \u003cp\u003eIn this study, we aimed to analyze the predictive value of cytokine levels for death outcomes in SFTS and to establish a prognostic model to find valuable predictors. In addition, the role of cytokines in the occurrence and development of diseases was further explored by analyzing the correlation between cytokines and virus titers and their dynamic changes. The search for new treatment methods was also the focus of this study.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePatients and samples\u003c/h2\u003e \u003cp\u003eIn this retrospective study, 128 patients were enrolled in this study at the First Affiliated Hospital of Anhui Medical University in Hefei, Anhui Province from January 1, 2019 to January 1, 2022. Patients who were included had the following conditions:(1) acute onset of high fever (\u0026ge;\u0026thinsp;37.5\u0026deg;C) for over 24h, (2) had reduced platelet count in peripheral blood in laboratory tests (PLT\u0026thinsp;\u0026lt;\u0026thinsp;100\u0026times;10\u003csup\u003e9\u003c/sup\u003e/L), (3) Positive SFTS virus RNA in blood confirmed by reverse transcription-polymerase chain reaction (RT-PCR) on admission, (4) Cytokine levels were performed on admission. Patients with hematologic disorders, autoimmune diseases, or had been treated with blood product stimulating factors were excluded. This study was approved by the Ethics Committee of the First Affiliated Hospital of Anhui Medical University.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eClinical data were obtained from the hospital electronic medical system. Clinical parameters include: age, sex, length of hospitalization, medical costs, Patient signs and treatment. laboratory indicators of white platelet count (PLT), Tumor Necrosis Factor α (TNF-α), Interleukin-6 (IL-6), Interleukin-8 (IL-8), Interleukin-10 (IL-10), Interleukin-2R (IL-2R), Interleukin-1B (IL-1B), CD4 and CD8 counts, serum SFTSV viral titers were collected as the first test data after admission. In addition, we collected the cytokine levels of 50 patients before and after treatment, of which 15 patients were tested every three days and monitored five times in a row. Death was defined as death during the course of the disease.\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eAll data were statistically analyzed using SPSS 16.0 and PRISM (version 8). Quantitative data are expressed as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation or median (interquartile range). Variables that conform to a normal distribution are tested using a t-test, while those that do not conform used a non-parametric test. Qualitative data were expressed as ratios and compared by chi-square or Fisher's exact test. \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 denote statistical significance. Risk factors were identified by univariable and multivariable Cox regression analyses for predicting mortality, and the results are expressed as adjusted Hazard ratio (HR) and 95% confidence intervals (95% CI). Predictive value of mortality-related predictors assessed by receiver operating characteristic (ROC) curves.\u003c/p\u003e \u003cp\u003eSpearman's test was used to calculate the correlation coefficient between cytokines and viral titers.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eCharacteristics of patients\u003c/h2\u003e \u003cp\u003eA total of 128 patients with SFTS diagnosed from the First Affiliated Hospital of Anhui Medical University in Hefei, Anhui Province were collected from January 2019 to January 2022. Of these, 52 patients were quantified for SFTS virus RNA on admission, and a total of 34 patients died during the course of the disease, with a mortality rate of 26.6%. The median age in the non-survival group was 65, higher than 61 in the survival group, and was statistically significant (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). There were 24 (67.7%) females in the death group much higher than males. All patients presented with fever on admission. Fatigue was the most common sign, followed by myalgia and diarrhea and abdominal pain. In addition, the incidence of central nervous system symptoms and multiple organ failure was much higher in the non-survival group, central nervous system symptoms mainly including headache and convulsions (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDifferences in clinical and laboratory characteristics between SFTS-survivors and non-survivors.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal (n\u0026thinsp;=\u0026thinsp;128)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003enon-survivor (n\u0026thinsp;=\u0026thinsp;34)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003esurvivor(n\u0026thinsp;=\u0026thinsp;94)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDemographic\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (27\u0026ndash;63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e65 (45\u0026ndash;88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (27\u0026ndash;80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.006\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egender\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e50 (73.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (32.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (43.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.271\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal hospital stay, days (median, IQR)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (3\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (3\u0026ndash;39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (4\u0026ndash;34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical costs, Renminbi (RMB)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33585 (2306-197799)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35200 (6198-197799)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29466 (2306-107767)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.380\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTime from start of fever to hospital admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (1\u0026ndash;10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (1\u0026ndash;15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSymptoms or signs\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFatigue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e77 (60.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60 (63.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyalgia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (38.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (38.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.995\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNausea\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (32.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (29.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.622\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28 (29.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.302\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCNS manifestations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (50.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18 (19.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEcchymosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.452\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiarrhoea and Abdominal pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (44.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (45.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.870\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMOF\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (11.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (45.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory variables from blood, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePLT (10\u003csup\u003e9\u003c/sup\u003e/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65.10\u0026thinsp;\u0026plusmn;\u0026thinsp;52.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57.35\u0026thinsp;\u0026plusmn;\u0026thinsp;55.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.90\u0026thinsp;\u0026plusmn;\u0026thinsp;51.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.035\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eViral titers (TCID50/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35389\u0026thinsp;\u0026plusmn;\u0026thinsp;159785\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e137530\u0026thinsp;\u0026plusmn;\u0026thinsp;329270\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5735\u0026thinsp;\u0026plusmn;\u0026thinsp;15511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.008\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTreatment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRibavirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGamma-globulin shock therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (11.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGamma-globulin shock therapy combined with ribavirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92 (74.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (73.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.013\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCytokines, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4 (cells/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e214.88\u0026thinsp;\u0026plusmn;\u0026thinsp;178.63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e120.65\u0026thinsp;\u0026plusmn;\u0026thinsp;90.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e245.50\u0026thinsp;\u0026plusmn;\u0026thinsp;189.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8 (cells/\u0026micro;L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e225.33\u0026thinsp;\u0026plusmn;\u0026thinsp;273.77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125.91\u0026thinsp;\u0026plusmn;\u0026thinsp;130.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e257.63\u0026thinsp;\u0026plusmn;\u0026thinsp;298.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4/CD8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.27\u0026thinsp;\u0026plusmn;\u0026thinsp;0.73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e48.31\u0026thinsp;\u0026plusmn;\u0026thinsp;154.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138.20\u0026thinsp;\u0026plusmn;\u0026thinsp;278.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.46\u0026thinsp;\u0026plusmn;\u0026thinsp;10.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.55\u0026thinsp;\u0026plusmn;\u0026thinsp;127.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127.33\u0026thinsp;\u0026plusmn;\u0026thinsp;227.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.61\u0026thinsp;\u0026plusmn;\u0026thinsp;17.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.37\u0026thinsp;\u0026plusmn;\u0026thinsp;190.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187.38\u0026thinsp;\u0026plusmn;\u0026thinsp;219.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.28\u0026thinsp;\u0026plusmn;\u0026thinsp;113.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e84.16\u0026thinsp;\u0026plusmn;\u0026thinsp;415.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e250.22\u0026thinsp;\u0026plusmn;\u0026thinsp;798.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.61\u0026thinsp;\u0026plusmn;\u0026thinsp;16.30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1340.35\u0026thinsp;\u0026plusmn;\u0026thinsp;927.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2341.30\u0026thinsp;\u0026plusmn;\u0026thinsp;1672.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1064.96\u0026thinsp;\u0026plusmn;\u0026thinsp;561.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-1B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.50\u0026thinsp;\u0026plusmn;\u0026thinsp;20.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.36\u0026thinsp;\u0026plusmn;\u0026thinsp;29.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.95\u0026thinsp;\u0026plusmn;\u0026thinsp;7.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.014\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe platelet count in the non-survival group was significantly lower than that in the survival group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035), while the viral titer was higher than that in the survival group (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.008). In terms of treatment, the three treatments of ribavirin, gamma-globulin shock therapy, and gamma-globulin shock therapy combined with ribavirin therapy were significantly different between the two groups (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCytokine Characteristics Of Sfts Patients And Predictors Associated With Lethal Outcome\u003c/h3\u003e\n\u003cp\u003eEach patient was detected six cytokine levels as well as CD4 and CD8 counts on admission. Significant differences between the non-survival group and the survival group were showed from results (IL-1B: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.013, other five cytokines: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The quantitative results of the non-survival group were much higher than those of the survival group, while the CD4 and CD8 counts of the death group were lower than those of the survival group (CD4: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001, CD8: \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002). In addition, the values of other cytokines except IL-8 in the two groups were much higher than the normal reference interval, while the IL-8 in the survival group was almost within the normal range, and the non-survival group showed a higher trend.\u003c/p\u003e \u003cp\u003eWe included six cytokines, CD4 and CD8 counts, and age and sex into the Cox regression model (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The variable which \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in univariate analysis, as well as corrective factors age and sex into multivariate analysis. The dichotomous threshold of the blood test is based on the cut-off point of the ROC curve. TNF-α was shown to be an independent predictor of death (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.038, HR\u0026thinsp;=\u0026thinsp;12.78). To assess the predictive value of cytokine levels on the lethal outcome of SFTS, we performed a ROC analysis of TNF-α, and the result showed an AUC value of 0.901, which has an excellent predictive value (Fig.\u0026nbsp;1). Kaplan-Meier survival curves were used to confirm that patients with TNF-α above 20.15 pg/ml had a significant increase in mortality (Fig.\u0026nbsp;2).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eUnivariable and multivariable Cox regression analyses of features associated with fatal outcomes in patients with SFTS\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95%CI for HR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eHR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95%CI for HR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex, male vs female\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.32\u0026ndash;1.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.337\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, year, \u0026ge;\u0026thinsp;65 vs\u0026thinsp;\u0026lt;\u0026thinsp;65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.99\u0026ndash;1.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD4, /\u0026micro;L, \u0026lt;\u0026thinsp;207 vs\u0026thinsp;\u0026ge;\u0026thinsp;207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.68\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.56\u0026ndash;28.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCD8, /\u0026micro;L, \u0026lt;\u0026thinsp;144 vs\u0026thinsp;\u0026ge;\u0026thinsp;144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58\u0026ndash;11.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTNF-α, pg/ml, \u0026ge;\u0026thinsp;20.15 vs\u0026thinsp;\u0026lt;\u0026thinsp;20.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.01\u0026ndash;54.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.16-141.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-6, pg/ml, \u0026ge;\u0026thinsp;17.15 vs\u0026thinsp;\u0026lt;\u0026thinsp;17.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.28\u0026ndash;57.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-10, pg/ml, \u0026ge;\u0026thinsp;77.7 vs\u0026thinsp;\u0026lt;\u0026thinsp;77.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.45\u0026ndash;16.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-8, pg/ml, \u0026ge;\u0026thinsp;32.55 vs\u0026thinsp;\u0026lt;\u0026thinsp;32.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.15\u0026ndash;17.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-2R, U/ml,, \u0026ge;\u0026thinsp;1253 vs\u0026thinsp;\u0026lt;\u0026thinsp;1253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8.96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.08\u0026ndash;26.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIL-1B, pg/ml, \u0026ge;\u0026thinsp;12.9 vs\u0026thinsp;\u0026lt;\u0026thinsp;12.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.95\u0026ndash;4.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eThe Change Trend Of Cytokines And Its Correlation With Viral Titers\u003c/h3\u003e\n\u003cp\u003e15 patients were dynamically monitored for cytokine levels every three days after admission, and their conditions eventually improved. As shown in Fig.\u0026nbsp;3, TNF-α, IL-2R and IL-1B peaked at 4\u0026ndash;6 days after admission and then gradually decreased, while IL-6 and IL-8 peaked at 7\u0026ndash;9 days and then decreased. It is noteworthy that IL-10 has been steadily decreasing after admission. We also found that IL -8 fluctuated within the normal range throughout the change except for a few values. In addition, TNF-α, IL-6 and IL-8 showed a small increase after 13 days. By comparing cytokine levels before and after treatment in 50 patients who had received gamma-globulin shock therapy in combination with ribavirin, IL-6 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049), IL-2R (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006), IL-10 (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005) decreased significantly after treatment, while the changes in TNF-α, IL-1B, 1L-8 were not statistically significant, and even IL-1B mostly had an upward trend (Fig.\u0026nbsp;4). The linear relationship between cytokines and viral titers was also analyzed. TNF-α, IL-6, IL-8 and IL-10 were positively correlated with viral titers (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001, 0.5\u0026thinsp;\u0026lt;\u0026thinsp;r\u0026thinsp;\u0026lt;\u0026thinsp;1), while IL-2R and IL-1B were not (Fig.\u0026nbsp;5).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eAt present, SFTS is a new infectious disease which attracts much attention. Up to now, there is no specific drug to treat it. Ribavirin, Favipiravir and other antiviral drug are commonly used in clinic (13). It is well known that the immune response is essential for the body to fight against viral infections, however, excessive immune responses can trigger cytokine storms that can cause further organ damage and lead to adverse outcomes (14). Therefore, controlling cytokine storms is also necessary to reduce mortality of viral infectious diseases, including SFTS.\u003c/p\u003e \u003cp\u003eIn this study, patient information was collected from 2019 to 2022 at one of the top two large general hospitals in Anhui Province. Anhui Province is a region with high incidence of SFTS (15), the mortality rate in our study is 26.6%, which is consistent with the data reported in recent years (16). We found that there were far more females than males among the patients who died, this result varied among studies (17, 18). This may be due to that in Anhui province, SFTS patients are mostly tea pickers from rural areas, and this occupation is mostly female. The older age of the deceased patients is indeed due to that older patients tend to have more underlying diseases and comorbidities, and a weaker immune system aggravates the poor prognosis. Thrombocytopenia is an important feature of SFTS. In our analysis, platelet levels showed lower values in the non-survival group, therefore were closely associated with death as well as disease severity. In addition, viral titers at hospital admission were much higher in the non-survival group, even up to hundreds of thousands of times, and most studies have confirmed that viral load is a serious threat to mortality outcomes(19, 20). Our study also found that the central nervous system symptoms of the deceased patients were significantly different from those of the survival group, with most patients presenting headaches, convulsions and even coma after admission, which further aggravated the development of the disease.\u003c/p\u003e \u003cp\u003eCytokines play an important role in immune regulation and immune response. Many studies have shown that the cytokine level in SFTS patients is significantly higher than that in healthy people, and it is even more obvious in dead patients, which is also confirmed by our study (21\u0026ndash;23). High cytokine levels in dead patients are likely to cause systemic inflammatory symptoms and further organ failure, which may be a major cause of death. Most studies have reported the difference of cytokines in SFTS patients compared with healthy people or between severe and non-severe patients. Few studies have explored the predictive value of cytokines in death outcome (24). TNF-α is a cytokine with multiple functions, mainly including homeostatic functions of immune regulation, defense against pathogens, inhibition of tumorigenesis, and pathogenic functions such as induction of inflammatory mediators and induction of tissue degeneration (25). A recent study indicated that TNF-α was an independent predictor of death in patients with COVID-19 (26). In our study, TNF-α plays a very significant prognostic factor role in cytokines and has a high predictive value. IL-6 and IL-10 had also been shown to be good predictors of poor prognosis of SFTS (27). These findings suggest that cytokines are of great value in the prediction of SFTS prognosis.\u003c/p\u003e \u003cp\u003eIn our study, levels of all six cytokines were significantly higher in dead patients than in survivors, the levels of IL-8 were in the normal range in most of the patients in both groups, while the levels of other five cytokines were much higher than the normal range. This may be because IL-8 is a chemokine whose primary role is to attract leukocytes to infiltrate in inflammatory or tumor tissues [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], whereas SFTS is a systemic reactive disease, the absence of a specific immune target reduces the action of chemokines so that they do not change much. IL-8 levels have even been reported to be lower in SFTS patients than in the healthy population (29). Likewise, the reduced CD4 and CD8 counts in the dead patients were a sign of immune suppression after viral infection, which was also showed in previous studies (30). In the trend of cytokine changes, TNF-α, IL-2R and IL-1B reached the peak at 4\u0026ndash;6 days after admission, while IL-6 and IL-8 increased slowly. Interestingly, IL-10 tended to decline after admission until it finally returned to the normal reference range, which is quite different from He et al (29). We speculated that this might be because the 15 patients with dynamic cytokine changes collected in this study were treated with cyclic gamma-globulin combined with ribavirin immediately after admission. In our study, we found that the change of IL-10 was the most significant before and after treatment, which can be inferred that IL-10 is the most sensitive to this kind of treatment. Unfortunately, patients in the non-survival group died within a relatively short period of time after readmission so the dynamic pattern of their cytokine levels was not monitored and the differences between the two groups could not be compared. In this study, we found that TNF-α, IL-6, IL-10, and IL-8 were significantly correlated with viral titers, which indicated that viral replication with high copy number could induce cytokine release in vivo, which was also confirmed by previous studies(12, 29). However, significant correlations between TNF-α and IL-8 and viral load have not been reported.\u003c/p\u003e \u003cp\u003eAt present, the treatment of SFTS is the focus of attention and needs to be urgent solved. Most current reports focus on ribavirin and other common antiviral drug, and the effect is not significant (31). In China, high-dose gamma-globulin shock therapy is a common treatment, although it is rarely reported (5). As an immunomodulator, gamma-globulin can enhance the function of phagocytes, help to eliminate pathogenic bacteria, at the same time significantly reduce the secretion of inflammatory cytokines, and inhibit the body's inflammatory response (32). In this study, high-dose gamma-globulin shock therapy combined with ribavirin treatment had a significant effect on the reduction of some cytokines (IL-10, IL-2R, IL-6), and since almost all patients were treated with the combination, no difference in efficacy was seen between the non-survival and survival groups. The dose and duration of gamma-globulin shock therapy needs to be explored in studies with larger samples.\u003c/p\u003e \u003cp\u003eNonetheless, the study has some limitations. First of all, the viral titer is only detected at admission, and there is no subsequent dynamic monitoring to better explore the correlation between it and cytokines. Secondly, due to the limitation of sample testing, this study included fewer cytokines, which failed to explore their development and predictive value in disease more comprehensively. In the future, the sample size and testing items will be expanded to continue to explore.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe levels of cytokines TNF-α, IL-6, IL-8, IL-10, IL-2R and IL-1B were significantly higher in patients with SFTS death than in surviving patients. TNF-α is an independent predictor of death and having a high predictive value. Different cytokines had different trends during the course of the disease and some cytokines (TNF-α, IL-6, IL-8, IL-10) were correlated with viral titers. The combination of gamma-globulin and ribavirin could control the cytokine storm to a limited extent, but only showed significant efficacy in some cytokines (IL-6, IL-10, IL-2R), and its therapeutic value needs to be further investigated.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was reviewed and approved by the Ethics Committee of the First Affiliated Hospital of Anhui Medical University. The written informed consent was obtained from patients in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was financially supported by Anhui Natural Science Foundation (grant number: 9021138201).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDML: concept and writing of the manuscript. TM and LWZ: data processing and software. YZ and YHX: review and editing. All authors contributed to the article and approved the submitted version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the First Affiliated Hospital of Anhui Medical University staffs for their support in sample and clinical data collections.\u003c/p\u003e\n\u003cdiv id=\"edn12\"\u003e\u003cbr\u003e\u003c/div\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eYu XJ, Liang MF, Zhang SY, Liu Y, Li JD, Sun YL, et al. Fever with thrombocytopenia associated with a novel bunyavirus in China. N Engl J Med. [Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't]. 2011 2011-04-21;364(16):1523\u0026ndash;32.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Deng B, Zhang J, Cui W, Yao W, Liu P. 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[Journal Article; Research Support, Non-U.S. Gov't]. 2012 2012-02-15;54(4):527\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Han Y, Xing Y, Li S, Kong L, Zhang Y, et al. Concurrent measurement of dynamic changes in viral load, serum enzymes, T cell subsets, and cytokines in patients with severe fever with thrombocytopenia syndrome. PLOS ONE. [Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't]. 2014 2014-01-20;9(3):e91679.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu MM, Lei XY, Yu H, Zhang JZ, Yu XJ. Correlation of cytokine level with the severity of severe fever with thrombocytopenia syndrome. VIROL J. [Journal Article; Research Support, Non-U.S. Gov't]. 2017 2017-01-13;14(1):6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNakamura S, Iwanaga N, Hara S, Shimada S, Kashima Y, Hayasaka D, et al. 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[Journal Article; Research Support, Non-U.S. Gov't]. 2021 2021-01-20;12:711847.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlfaro C, Sanmamed MF, Rodr\u0026iacute;guez-Ruiz ME, Teijeira \u0026Aacute;, O\u0026ntilde;ate C, Gonz\u0026aacute;lez \u0026Aacute;, et al. Interleukin-8 in cancer pathogenesis, treatment and follow-up.; 2017. p.\u0026nbsp;24\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHe Z, Wang B, Li Y, Hu K, Yi Z, Ma H, et al. Changes in peripheral blood cytokines in patients with severe fever with thrombocytopenia syndrome. J MED VIROL. [Journal Article; Research Support, Non-U.S. Gov't]. 2021 2021-08-01;93(8):4704\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu J, Wang L, Feng Z, Geng D, Sun Y, Yuan G. Dynamic changes of laboratory parameters and peripheral blood lymphocyte subsets in severe fever with thrombocytopenia syndrome patients. INT J INFECT DIS. [Journal Article]. 2017 2017-05-01;58:45\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi J, Li S, Yang L, Cao P, Lu J. Severe fever with thrombocytopenia syndrome virus: a highly lethal bunyavirus. CRIT REV MICROBIOL. [Journal Article; Review]. 2021 2021-02-01;47(1):112\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang L, Wu EY, Tarrant TK. Immune Gamma Globulin Therapeutic Indications in Immune Deficiency and Autoimmunity. Curr Allergy Asthma Rep. [Journal Article; Review]. 2016 2016-07-01;16(8):55.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Severe fever with thrombocytopenia syndrome (SFTS), Cytokines, Viral titers.","lastPublishedDoi":"10.21203/rs.3.rs-2251280/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2251280/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Severe fever with thrombocytopenia syndrome (SFTS) is a serious infectious disease that has received widespread attention. This study focuses on the predictive value and trend of cytokines in SFTS.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eInformation of 128 SFTS patients retrospectively collected from January 2019 to January 2022 from a large general hospital in Anhui Province, China. Multivariate Cox model was used to identify predictors of death, ROC curve was used to calculate the value of predictors. Linear regression analysis was used to explore the correlation between cytokines and viral titers. Dynamic changes in cytokines to demonstrate therapeutic significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eOf the 128 patients diagnosed with SFTS, 34 died during the course of the disease. Cytokines were significantly higher in the non-survival group than the survival group, while CD4 and CD8 counts were lower in the non-survival group. Multivariate Cox analysis showed that TNF-α was an independent predictor of death (\u003cem\u003ep\u003c/em\u003e = 0.038, HR = 12.78) with an AUC value of 0.901. TNF-α, IL-6, IL-10 and IL-8 were correlated with viral titer (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001, 0.5 \u0026lt; r \u0026lt; 1). Different cytokines showed different trends in the course of treatment. High dose gamma-globulin shock therapy combined with ribavirin can effectively reduce the level of some cytokines (IL-6, IL-2R, IL-10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eTNF-α is an independent predictor of SFTS death outcome and has excellent predictive value. There was a significant correlation between TNF-α, IL-6, IL-10, IL-8 and virus titer. Gamma-globulin shock therapy combined with ribavirin can control cytokine storm to some extent and provide new ideas for clinical treatment.\u003c/p\u003e","manuscriptTitle":"Prognostic value and dynamic change characteristics of cytokines in Severe fever with thrombocytopenia syndrome","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-11-14 15:17:09","doi":"10.21203/rs.3.rs-2251280/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6402bae5-3ede-421a-a883-9b75317bf5b5","owner":[],"postedDate":"November 14th, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2023-03-07T14:29:09+00:00","versionOfRecord":[],"versionCreatedAt":"2022-11-14 15:17:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-2251280","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2251280","identity":"rs-2251280","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}