Prediction Model Of Death Risk In Patients With Fever And Thrombocytopenia Syndrome And Exploration Of SFTS Monocyte Inflammatory Pathway By Multi-omics

Part 1.Establishment and validation of death prediction model for patients with fever and thrombocytopenia syndromeBackground: Fever with thrombocytopenia syndrome(SFTS)is a new infectious disease caused by Dabie bandavirus(DBV)infection.SFTS can affect multiple organs,and in severe cases,nervous system symptoms occur.The reported mortality of SFTSV is between5% and 30%.SFTS mostly occurs in mountainous and rural areas,and the diseases reported by the elderly are more serious.Therefore,it is important to evaluate the prognosis at the early stage of the disease,In the past,although some SFTS prognosis models have been built by using clinical symptoms and laboratory indicators,these models have not been widely used due to the limited sample size and methods.At present,there is still a lack of reliable critical warning system in clinical practice.This study intends to use a retrospective analysis of our hospital to construct and verify the reliability of the model,so as to provide a basis for clinical early judgment of patients’ prognosis and adjustment of treatment plan accordingly.Objective: To establish a reliable model for evaluating the prognosis of SFTS patients,which can predict the prognosis of patients individually,and visualize the model for clinical use and can be popularized in grass-roots hospitals.Methods: A total of 1034 confirmed cases of SFTS admitted by the Infection Department of the Union Hospital Affiliated to Huazhong University of Science and Technology from January 2014 to December 2022 were retrospectively analyzed,and the cohort was randomly divided into training set and verification set according to the ratio of 7:3.Observe the clinical symptoms and signs of the patients,collect the laboratory examination results in the hospital,divide the patients into survival group and death group according to the outcome of SFTS disease,compare the differences of various indicators between the two groups,establish independent risk factors affecting the prognosis of the disease according to multiple methods such as single-factor logistic regression,LASSO regression,and multifactor logistic regression,and establish a patient prognosis prediction model based on these risk factors,And construct nomogram,and generate a web page calculator that can be used for promotion.Results:(1)There was no statistical difference between the training set and the validation set in terms of clinical symptoms,physical signs and laboratory examination results,suggesting that the data sources of the two groups were reliable and unbiased.(2)The results of single factor logistic analysis in the training set showed age,dyspnea,lung rale or wheezing,lethargy,coma,limb and muscle tremor,bleeding points,ecchymosis,viral load,platelets,total bilirubin,direct bilirubin,alanine aminotransferase,aspartate aminotransferase,alkaline phosphatase,lactate dehydrogenase,albumin,urea nitrogen,potassium,creatine kinase,D-dimer,PT,APTT,TT CRP,ferritin,creatinine,monocyte% γ-There were significant differences in 43 indicators,such as glutamyltransferase,calcium,neutrophil%,cerebrovascular disease,hypersensitive troponin I,lymphocyte%,PCT,hematemesis,lymph node enlargement,hypertension,headache,globulin,INR,fever,CKMB quality determination,between the death group and the survival group.(3)Multivariate regression analysis finally determined 10 indicators,including age,dyspnea,lethargy,coma,viral load,lactate dehydrogenase,urea nitrogen,ferritin,PCT,PT,and finally built a regression model based on these 10 indicators.(4)The AUC of the training group and the validation group were 0.945 and 0.908 respectively,indicating that the prediction performance of the model was good.Conclusion: This study has constructed and verified a predictive scoring system for predicting the prognosis of SFTS based on 10 simple and accessible clinical indicators,and has shown good differential diagnosis efficiency and clinical practicability.A web calculator has been established,which can be used and promoted in clinical practice.Part 2.Multiomics to explore the inflammatory pathway of mononuclear cells in fever with thrombocytopenia syndromeBackground: Studies have shown that in patients with fever and thrombocytopenia syndrome(SFTS),the peripheral blood mononuclear cells in the acute phase are decreased,the death group is lower,and the recovery period is higher.Mononuclear cells have an important relationship with the prognosis of SFTS.The severity of SFTS is related to "cytokine storm",which leads to multiple organ failure.However,the pathway of cytokine storm has not been clarified.At present,the existing single-cell transcriptomics have failed to conduct in-depth research on mononuclear cells.This study takes SFTS peripheral blood mononuclear cells(PBMC)single-cell transcriptomics and common transcriptomics in the database as the entry point to deeply explore the key pathways of SFTS peripheral blood PBMC mononuclear cells interacting with other cells,providing a research basis for the pathogenesis of SFTS.Objective: Monocytes play an important role in fever with thrombocytopenia syndrome.The purpose of this study is to explore the interaction pathway between monocytes and other cells through multi-group data to find a target for the follow-up treatment of fever with thrombocytopenia syndrome.Methods: This study first analyzed the different groups of patients with fever and thrombocytopenia syndrome in the GEO database,including the single-cell transcriptome data of peripheral blood PBMC in the acute phase,the death group,the recovery phase and the healthy control.Through the single-cell transcriptome data,we analyzed the cell communication between SFTS peripheral blood PBMC cells,and focused on the interaction pathway between monocytes and other cells.Then we analyzed the common transcriptome data of PBMC from SFTS peripheral blood,further verified the pathway found above in the common transcriptome,and carried out the QPCR verification of the key genes of the monocyte pathway found on SFTSV-infected monocyte lines.Results:(1)The differential genes of monocytes in SFTS peripheral blood PBMC acute phase group and healthy group were mainly concentrated in T cell activation,regulation of cytokine expression,leukocyte adhesion,restriction of viral activity,cytokine signal pathway,leukocyte activation,immune regulation signal pathway,and immune response involved by activated leukocytes.(2)The cell communication of PBMC in the acute phase of SFTS peripheral blood increased compared with that in the healthy control.Monocytes mainly interacted with other cells through IL and CXCL signaling pathways.The expressionof key genes of IL and CXCL in mononuclear macrophage cells infected by SFTSV increased.Conclusion: In the acute phase of SFTS,monocytes play a role in activating leukocytes and regulating cytokine expression.Monocytes interact with other cells mainly through IL and CXCL signaling pathways,which may be the key pathway to cause cytokine storm.