| Background&Purpose:Sepsis is a life-threatening multi-organ dysfunction caused by the host’s dysfunctional response to infection and is one of the most common causes of death in intensive care unit(ICU)patients.In high-risk patients with suspected sepsis infection,effective identification and diagnosis of sepsis is crucial for timely treatment of patients and the application of antibiotics.Biomolecules that have been studied include C-reactive protein,procalcitonin,cytokines,and soluble leukocyte CD 14 subtypes,which are commonly used as biomarkers for diagnosing septic infection.Microbial blood culture is often used as the gold standard for determining systemic infection,but this method lacks sensitivity and has substantial time delays.Therefore,some new biomarkers for the diagnosis of sepsis have emerged in recent years.The trigger receptor expressed on myeloid cell-1(TREM-1)is a member of the inflammatory immunoglobulin superfamily and is commonly expressed in neutrophils,monocytes,and macrophages.Some systematic reviews and meta-analyses have demonstrated that sSM-1 in plasma,bronchoalveolar lavage fluid or pleural fluid has certain diagnostic value for systemic infection.However,the diagnostic value of sTREM-1 in sepsis remains to be further analyzed and determined.In this paper,Meta-analysis was used to collect previously published literatures on the diagnostic value of sTREM-1 in sepsis and systematically evaluate the diagnostic value of sTREM-1 detection in sepsis.Methods:The original literatures related to sTREM-1 and sepsis were collected from Chinese and English medical databases(the database was established until December 7,2020),including CNKI,Wanfang,VIP,CBM,PubMed,Embase,Cochrane Library,WEBOFScience and other databases.Data were extracted in strict accordance with inclusion criteria and exclusion criteria,and summarized and sorted according to number,author,year,sample size,experimental group,experimental control group,sensitivity,specificity,TP,FP,FN,TN,critical value,etc.Quadas-2 tool was used to evaluate the literature quality and select the literatures to be used in the Meta analysis.Meta-analysis was performed using Metaiscl.4,RevMan5.3,Stata14.0 and Graphpadprism 5.0 software,including threshold effect,heterogeneity test,sensitivity analysis,Deeks bias test and other analyses to evaluate the diagnostic value of sTREM-1 in sepsis.Results:A total of 712 documents were retrieved,including 454 in Chinese database and 258 in English database.After a series of preliminary screening and exclusion,27 literatures were included for meta-analysis,including 12 Chinese literatures and 15 English literatures.The spearman correlation coefficient between sensitivity logarithm and(1-specificity)logarithm is-0.376,P value is 0.053,greater than 0.05,and the difference is not significant,which indicates that there is no threshold effect in this study.Furthermore,it is found that Cochran-Q of DOR is 188.37(P<0.01),which indicates that there is a non-existence in this study of sTREM-1 diagnosis of sepsis Meta-analysis showed that the Sensitivity of sTREM-1 in diagnosing sepsis was 0.73,95%CI(0.71-0.75)for sen,0.79,95%CI(0.76-0.81)for Spe,4.35,95%CI(3.24-5.83)for PLR and DOR The area under SROC curve of combined effect was AUC=0.89.according to the sample size of sTREM-1 test for diagnosis of sepsis,the Sensitivity and specificity effects of large samples(more than 100 cases)were combined,and the results were sen combined=0.67(95%CI,0.64-0.69)and Spe combined=0.76(95%CI,0.72-0.79),small samples(less than 100 cases)were combined,and the results were sen combined=0.84(95%CI,0.81-0.86)and Spe combined=0.83(95%CI,0.80-0.86).Conclusion:1.According to the current studies,blood sTREM-1 has a moderate ability in the diagnosis of suspected sepsis,sTREM-1 alone as a biomarker is not enough to diagnose and predict sepsis.2.The threshold for diagnosing sepsis in this study is not uniform,so the inclusion of 27 original research literature results has limitations.3.The heterogeneity caused by the non-threshold effect in this study mainly comes from the size of the sample,and neither the publication period nor the case type can explain the source of the heterogeneity.Figure[fifteen]table[three]reference[eighty-five]... |
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