key: cord-0310874-gk0roo4n authors: Khan, S.; Mishra, P.; Parveen, R.; Bajpai, R.; Khan, M. A.; Agarwal, N. B. title: Association of inflammatory markers with severity of disease and mortality in COVID-19 patients: a systematic review and meta-analysis date: 2021-09-21 journal: nan DOI: 10.1101/2021.09.16.21263678 sha: 7fb0b4ca27e2d131a9ac5560e1f029a2ca1c57f6 doc_id: 310874 cord_uid: gk0roo4n Purpose: Literature suggests association of inflammatory markers with the severity and mortality related to COVID-19, but there are varying conclusions available. We aimed to provide an overview of the association of inflammatory markers with the severity and mortality of COVID-19 patients. Methods: We searched Medline (via PubMed), Cochrane, Clinicaltrials.gov databases until Sept 1, 2020. Results: A total of 21 studies comprising 4023 patients with COVID-19 were included in our analysis. Levels of IL-6 (WMD=18.17 95%CI 3.38 to 32.96, p=0.016), IL-8 (WMD=12.09 95%CI 4.41 to 19.77, p=0.002), MCP-1 (WMD=146.66 95%CI 88.16 to 205.16, p<0.001), CRP (WMD=31.09 95%CI 10.08 to 52.10, p=0.004), PCT (WMD= -31.23 95%CI -37.70 to -24.76, p<0.001), IL-2R (WMD=861.93 95%CI 275.45 to 1448.41, p=0.004), ferritin (WMD= 1083.34 95%CI 431.99 to 1734.70, p=0.001) were found significantly higher in the severe group compared with the non-severe group of COVID-19 patients. Moreover, non-survivors had a higher levels of IL-2R (WMD= -666.06 95%CI -782.54 to -549.59, p<0.001), IL-8 (WMD= -26.63 95%CI -33.031 to -20.236, p<0.001), IL-10 (WMD= -7.60 95%CI -8.93 to -6.26, p<0.001), TNF- (WMD= -4.60 95%CI -5.71 to -3.48, p<0.001), IL- 1{beta} (WMD=22.66 95%CI 8.13 to 37.19, p=0.002), CRP (WMD= -96.40 95%CI -117.84 to -74.97, p<0.001), and ferritin (WMD= -937.60 95%CI -1084.15 to -791.065, p<0.001) when compared to the non-survivor group. Conclusion: This meta-analysis highlights the association of inflammatory markers with the severity and mortality of COVID-19 patients. Measurement of these inflammatory markers may assist clinicians to monitor and evaluate the severity and prognosis of COVID-19 thereby reducing the mortality rate. Keywords: inflammatory markers, cytokine storm, interleukin, disease severity, COVID-19 In December 2019, a largely enveloped virus was labeled as COVID-19, which was discovered in Wuhan, China, rapidly spread globally. It was found out to be a new infectious disease classified under SARS-CoV and MERS-CoV which primarily causes respiratory tract infection 1 . WHO declared the pandemic outbreak of novel coronavirus (2019-nCoV) as a global health emergency. As of September 1, 2020 over 216 countries have been affected by the COVID -19 disease with more than Twenty Four million (24,257,989 ) confirmed cases leading to over 8,27,246 deaths 2 . Although, most cases are mild to moderate, some patients develop severe symptoms characterized by respiratory dysfunction and/or multiple organ failure 3, 4 . Identification of progression of COVID-19 in the current state, depends mostly on the clinical manifestation. It has been recommended that one of the possible mechanisms of ultimate speedy disease progression is cytokine storm 5, 6 . Cytokine storm, also known as cytokine cascade, or hypercytokinemia, is caused by infection, drugs or autoimmune diseases of the body's excessive immunity response 7 . This inflammatory response is associated with elevated levels of inflammatory cytokines and leads to alveolar damage and acute respiratory distress syndrome (ARDS) 5 . Accumulating evidence suggest that an elevated level of inflammatory cytokines is associated with a high severity and case fatality of COVID-19 infection 4, 6, [8] [9] [10] . Pathological manifestations of COVID-19 greatly resemble what has been seen in SARS and MERS infection where massive interstitial inflammatory infiltrates diffuse in the lung 10 . The main effect of interleukins is to suppress inflammation, however, it has been shown that the over-production of specific inflammatory cytokines such as IL-2, IL-4, IL-6, IL-8, IL-10, tumor necrosis factor (TNF-α) are the gold standard of viral infection [11] [12] [13] . Interleukins can be of high interest for reaching out the target of immunosuppressive therapy approaches by cytokine blockers in COVID-19 like several approaches, including global targeting of the inflammation or neutralizing a single key inflammatory mediator, can be employed to cope with cytokine storm 14 . Interleukins promotes specific differentiation of CD4 + / CD8 + Tcells, thus performing an important function in the linking of innate to acquired immune response. Also, in combination with transforming growth factor (TGF)-β, interleukins are indispensable for Th17 differentiation from naıve CD4 + T cells 15 . Elevated levels of IL-6 can cause hyper-activation of JAK/STAT3 signaling, which is often associated with poor patient outcomes 16 . The elevated cytokine levels may also be responsible for the lethal complications of patients with COVID-19, SARS or MERS presented distinct cytokine profiles 17 . Along with interleukins the levels of C-reactive protein(CRP), induced by IL-6, is a significant biomarker of inflammation, infection and tissue damage 18 along with Procalcitonin (PCT) that is a glycoprotein and is the precursor of calcitonin, its levels are increased with bacterial and viral levels and can be indicative of the disease severity as these levels were found to be greater in severe group of patients . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted September 21, 2021. ; https://doi.org/10.1101/2021.09. 16 .21263678 doi: medRxiv preprint than in mild group 9 . Ferritin, a protein that contains iron and is the primary form of iron stored inside of cells. Levels of ferritin could be a significant marker for COVID-19 as it is found elevated in diseased patients 19 . To the best of our knowledge, due to the insufficient sample sizes, the complete inflammatory profile is missing to date. Therefore, we did a meta-analysis based on the current literature to compare the levels of inflammatory markers between severe vs non-severe and survivor vs non-survivors patients with COVID-19. Our findings will give insight about the role of inflammation in the pathophysiology of novel coronavirus and its clinical features. Detection of these inflammatory markers can work as a tool to group patients according to their disease severity and predict the prognosis and mortality, thereby contributing to treatment and reducing mortality rate. Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines extension for scoping reviews 20 and MOOSE guidelines were followed for designing and reporting this systematic review. The protocol of this systematic review was registered on PROSPERO (registration ID: CRD42020200757). A systematic literature search was performed using Medline (via PubMed), The Cochrane Central Register of Controlled Trials (CENTRAL) and Clinicaltrials.gov until September 1, 2020 using the keywords "SARS CoV-2", "Interleukins", "Cytokines", "COVID-19", "Cytokine storm", "Inflammatory markers", "laboratory findings". We also searched grey literature using Google Scholar and reference list of eligible articles with the aim of identifying additional potential eligible studies. Each article was separately reviewed by two authors independently to find out the right content. The searches were limited to articles published in English language. Inclusion and exclusion criteria . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint Observational studies or case series reporting the level of cytokines in defined groups as per severity of COVID-19 were included. We excluded duplicate publications, reviews, editorials, case reports, letters, meta-analysis, systematic review, protocols, studies in language other than English and studies not reporting the required data. First author (SK) searched data and screened articles for eligibility. Senior author (PM) double checked all the included articles and any dispute was resolved by the third author (RP). Two reviewers (SK and PM) assessed the quality of data in the included studies using the National Institute of Health (NIH) quality assessment tools 21 . We preferred the NIH tool because it is comprehensive and widely accepted for an exhaustive assessment of data quality. We rated the overall quality of included studies as good, fair and poor, and incorporated them in the results of this systematic review. The tools were designed to assist reviewers in focusing on concepts that are key for critical appraisal of the internal validity of a study. The tools were not designed to provide a list of factors comprising a numeric score. The tools were specific to individual types of included study designs and are described in more detail below. The tools included items for evaluating potential flaws in study methods or implementation, including sources of bias (e.g., patient selection, performance, attrition, and detection), confounding, study power, the strength of causality in the association between interventions and outcomes, and other factors. Quality reviewers could select "yes," "no," or "cannot determine/not reported/not applicable" in response to each item on the tool. For each item where "no" was selected, reviewers were instructed to consider the potential risk of bias that could be introduced by that flaw in the study design or implementation. Cannot determine and not reported were also noted as representing potential flaws. Each of the quality assessment tools had a detailed guidance document, which was also developed by the methodology team and NHLBI. Data was inputted into a standardized data extraction table (Excel) and independently checked by a second reviewer (PM) for accuracy. The following variables were extracted: name of the first author, year of publication, study design, age, gender, number of patients in severe and non-severe and survivor vs non-survivor groups, comorbidities, and the reported level of cytokines. The severity of disease was defined according to Diagnosis and Treatment Plan of COVID-. CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. The primary outcomes were (1) Severity of COVID-19 including: Intensive Care Unit (ICU) admission and (2) mortality due to confirmed COVID-19. Only intra-hospital mortality was considered. We performed an exploratory meta-analysis to understand the magnitude and direction of effect estimate. Continuous outcomes are presented using weighted mean difference (WMD) and 95% confidence intervals (CIs). Odds ratios (ORs) were calculated and presented with respective 95% CIs for binary outcomes. Meta-analysis of ORs using Mantel-Haenszel random-effects and inverse-variance method for WMDs using DerSimonian-Laird method was used 23 . Heterogeneity between studies was assessed using the χ 2 -based Cochran's Q statistic (p<0.1 considered as the presence of heterogeneity) and I-squared (I 2 ) statistics (>50% representing moderate heterogeneity) 23 . Publication bias was not assessed as a total number of studies for respective outcomes were less than ten 23 . The systematic search yielded a total of 838 publications. After removing duplicates, 313 articles were found to be potential publications for screening. After the application of predefined inclusion and exclusion criteria, a total of 21 studies were included for the final analysis (Figure-I). Among the 21 included studies, 16 were cohort studies, while 5 were case series. The main characteristics of the included studies are reported in Table-I . Overall, 4,023 participants were enrolled in the present study, out of which . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted September 21, 2021. ; https://doi.org/10.1101/2021.09.16.21263678 doi: medRxiv preprint 2,190 (57.55%) were male and 1,615 (42.44%) were females. The patients were classified into 4 groups on the basis of their disease severity: severe and non-severe or survivor and non-survivor group. Severe group had a total of 1,242 patients (32.64 %) whereas non -severe group had 2,563 patients (67.35 %). Survivor group had 425 patients (62.9%) and Non-Survivor group had 250 patients (37.03%). Inflammatory markers that were assessed in the present systematic review were IL-2, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-1β, TNF-α, MCP-1, C-reactive protein, procalcitonin, and ferritin. (Table-II) 4, 4, 8, 8, 17 ,24-32 . were not significantly associated with the mortality. Substantial heterogeneity was observed in IL-6 (I 2 ~ 98.9%) . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted September 21, 2021. ; https://doi.org/10.1101/2021.09. 16.21263678 doi: medRxiv preprint in the patient groups as survivors and non-survivors across 3 studies 17, 26, 33 (Table-II) . None of the comorbidities were statistically associated with the mortality in COVID- 19 COVID-19 a speedily increasing pandemic declared as an emergency by WHO increasing the burden on medical facilities 3 which is usually caused by cytokine storm which is the main factor driving severe clinical course of SARS-CoV-2 with a specific immune response that causes severe pathogenic mechanisms through inflammation in a way of 'attacking' the body which leads to severe pneumonia, pulmonary oedema, ARDS, or multiple organ failure, ICU admissions and even death 5, 7 . Studies have demonstrated the levels of cytokines can also be related to severity of COVID-19 infection 5, 7, 11 . Reports suggest that in patients with severe COVID-19, higher levels of IL-2, IL-10, TNF-α are present in ICU patients compared to non-ICU 12, 14 . Cytokines are quantitative measurements used clinically for many conditions reflecting pathological development of COVID-19 and evidence from literature depicts a major role of interleukins as an useful approach to clinicians for establishing a treatment and close monitoring and improving prognosis and outcomes and their significant variability between different groups of patients 5 . Cytokines drive T-cell growth, induces the differentiation of regulatory T-cells, and mediates activationinduced cell death 34,35 . IL-4 (IL-4R) signaling plays an essential role in immune responses through their signaling via type I and type II IL-4Rs on neutrophils to inhibition of several neutrophil effector functions fighting against infection at the site of infection 36 . IL-8 can add to neutrophil-mediated tissue damage, inflammatory diseases and host defense, neutrophils, granulocytes, causing migration toward the site of infection. 37 . IL-10, which is also to referred as human cytokine synthesis inhibitory factor (CSIF), acts as an anti-inflammatory cytokine 38 . IL-6 is an interleukin that acts as a pro-inflammatory cytokine 15, 39 . Elevated levels of IL-6 can cause hyper-activation of JAK/STAT3 signaling, which is often associated with poor patient outcomes 1640,41 , implying a possible shared . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted September 21, 2021. ; https://doi.org/10.1101/2021.09.16.21263678 doi: medRxiv preprint mechanism of cytokine-mediated lung damage caused by COVID-9 infection 42,43 along with co-morbidities like hypertension in severe group of patients more than non-severe ones is contributing to disease severity and case fatality 32 . Therefore, it is imperative to recognize the markers observing the progression of disease and treat patients early. The elevated cytokine levels may also be responsible for the lethal complications of patients with COVID-19 17 . Severity in COVID-19 may also be associated with IFN-γ production by CD4+ T-cells as its defect may lead to hypercytokinaemia 12 . Along with interleukins, the levels of C-reactive protein (CRP), induced by IL-6, is a significant biomarker of inflammation, infection and tissue damage 18 . The correlation between CRP levels, lung lesions, and disease severity can provide reference for clinical treatment 18, 40 . Procalcitonin (PCT) that is a glycoprotein and is the precursor of calcitonin, its levels are increased with bacterial and viral levels and can be indicative of the disease severity as these levels were found to be greater in severe group of patients than in mild group 9,32 indicating its association with disease severity and mortality 4, 6, 8, 19, 24, 27, 28, 30, 32, 33, [44] [45] [46] [47] . Ferritin, a protein that contains iron and is the primary form of iron stored inside of cells. Levels of ferritin could be a significant marker for COVID-19 as it is found elevated in diseased patients 19 Nevertheless, the role of inflammatory markers in observing the severity and mortality of COVID-19 is still controversial. In this study, through examining the 21 retrospective studies, we concluded that inflammatory markers were positively correlated with the severity and mortality of COVID-19. Furthermore, categorizing patients into severe and non-severe sub-groups is dependent on the definitions of severity of COVID-19. The approach was to measure severity of the disease between two groups as it was found from different literature studies .A retrospective study of 552 patients stated panel of circulating cytokinesIL-2R, IL-6, IL-8, IL-10, IL-1β and TNFα, PCT, CRP and ferritin could predict disease deterioration as the levels of cytokines were greatly increased in the severe group of patients than the non-severe ones which in turn was associated with the severity and mortality risk 46 . A meta-analysis demonstrated IL-6, IL-10 and serum ferritin were significantly elevated in patients with both severe and fatal COVID-19 indicating these interleukins as a strong discriminators for severe disease 49,50 . Increased CRP, IL-6 and TNF-α in COVID-19 patients and has shown a significant role of these markers in disease prognosis 31 . Furthermore, a retrospective study on 83 patients demonstrated how cytokines can be a targeted approach for the treatment methods for COVID-19 with IL blocking agents for severely ill patients seems effective as it is essential to accomplish a treatment for patient's condition in a timely manner 51 . Moreover, . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. There are several limitations that needs to be mentioned. The number of studies included in the meta-analysis is small. There was heterogeneity amongst individual studies because of which there was a deviation of some of our results from usual findings. Additionally, case-series were included in the present meta-analysis. Although we did an extensive search, we may have inadvertently missed relevant studies. Exclusion of studies in languages other than English may have resulted in missing of relevant studies. The present systematic review will provide understanding of the role of inflammatory markers in the pathophysiology of the disease COVID-19 which is associated with age and comorbidities donating to disease severity and mortality. The uncovering of these clinical parameters can contribute in the suitable diagnostic and treatment approach in a timely manner that can further help in the reduction of the mortality rate in the patients of . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. In the interest of transparency, we ask you to disclose all relationships/activities/interests listed below that are related to the content of your manuscript. "Related" means any relation with for-profit or not-for-profit third parties whose interests may be affected by the content of the manuscript. Disclosure represents a commitment to transparency and does not necessarily indicate a bias. If you are in doubt about whether to list a relationship/activity/interest, it is preferable that you do so. In the interest of transparency, we ask you to disclose all relationships/activities/interests listed below that are related to the content of your manuscript. "Related" means any relation with for-profit or not-for-profit third parties whose interests may be affected by the content of the manuscript. Disclosure represents a commitment to transparency and does not necessarily indicate a bias. If you are in doubt about whether to list a relationship/activity/interest, it is preferable that you do so. The author's relationships/activities/interests should be defined broadly. For example, if your manuscript pertains to the epidemiology of hypertension, you should declare all relationships with manufacturers of antihypertensive medication, even if that medication is not mentioned in the manuscript. In item #1 below, report all support for the work reported in this manuscript without time limit. For all other items, the time frame for disclosure is the past 36 months. Specifications/Comments (e.g., if payments were made to you or to your institution) Please place an "X" next to the following statement to indicate your agreement: ☒ I certify that I have answered every question and have not altered the wording of any of the questions on this form. . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint 1-2 Describe the rationale for the review in the context of what is already known. Explain why the review questions/objectives lend themselves to a scoping review approach. Objectives 4 Provide an explicit statement of the questions and objectives being addressed with reference to their key elements (e.g., population or participants, concepts, and context) or other relevant key elements used to conceptualize the review questions and/or objectives. Indicate whether a review protocol exists; state if and where it can be accessed (e.g., a Web address); and if available, provide registration information, including the registration number. -4 Eligibility criteria 6 Specify characteristics of the sources of evidence used as eligibility criteria (e.g., years considered, language, and publication status), and provide a rationale. Information sources* 7 Describe all information sources in the search (e.g., databases with dates of coverage and contact with authors to identify additional sources), as well as the date the most recent search was executed. Present the full electronic search strategy for at least 1 database, including any limits used, such that it could be repeated. Selection of sources of evidence † 9 State the process for selecting sources of evidence (i.e., screening and eligibility) included in the scoping review. 5 Data charting process ‡ 10 Describe the methods of charting data from the included sources of evidence (e.g., calibrated forms or forms that have been tested by the team before their use, and whether data charting was done independently or in duplicate) and any processes for obtaining and confirming data from investigators. Data items 11 List and define all variables for which data were sought and any assumptions and simplifications made. Critical appraisal of individual sources of evidence § If done, provide a rationale for conducting a critical appraisal of included sources of evidence; describe the methods used and how this information was used in any data synthesis (if appropriate). - Describe the methods of handling and summarizing the data that were charted. 7-8 . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint Give numbers of sources of evidence screened, assessed for eligibility, and included in the review, with reasons for exclusions at each stage, ideally using a flow diagram. Characteristics of sources of evidence 15 For each source of evidence, present characteristics for which data were charted and provide the citations. 7 Critical appraisal within sources of evidence 16 If done, present data on critical appraisal of included sources of evidence (see item 12). - For each included source of evidence, present the relevant data that were charted that relate to the review questions and objectives. 8 Summarize and/or present the charting results as they relate to the review questions and objectives. 9 Summarize the main results (including an overview of concepts, themes, and types of evidence available), link to the review questions and objectives, and consider the relevance to key groups. Limitations 20 Discuss the limitations of the scoping review process. 13 Provide a general interpretation of the results with respect to the review questions and objectives, as well as potential implications and/or next steps. Describe sources of funding for the included sources of evidence, as well as sources of funding for the scoping review. Describe the role of the funders of the scoping review. 14 JBI = Joanna Briggs Institute; PRISMA-ScR = Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews. * Where sources of evidence (see second footnote) are compiled from, such as bibliographic databases, social media platforms, and Web sites. † A more inclusive/heterogeneous term used to account for the different types of evidence or data sources (e.g., quantitative and/or qualitative research, expert opinion, and policy documents) that may be eligible in a scoping review as opposed to only studies. This is not to be confused with information sources (see first footnote). ‡ The frameworks by Arksey and O'Malley (6) and Levac and colleagues (7) and the JBI guidance (4, 5) refer to the process of data extraction in a scoping review as data charting. § The process of systematically examining research evidence to assess its validity, results, and relevance before using it to inform a decision. This term is used for items 12 and 19 instead of "risk of bias" (which is more applicable to systematic reviews of interventions) to include and acknowledge the various sources of evidence that may be used in a scoping review (e.g., quantitative and/or qualitative research, expert opinion, and policy document). . CC-BY-NC-ND 4.0 International license It is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) preprint The copyright holder for this this version posted September 21, 2021. ; https://doi.org/10.1101/2021.09.16.21263678 doi: medRxiv preprint Coronavirus disease (COVID-19) pandemic. World health organisation The role of biomarkers in diagnosis of COVID-19 -A systematic review Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system Epidemiological and Clinical Features of COVID-19 Patients with and without Pneumonia in Beijing Immune environment modulation in pneumonia patients caused by coronavirus: SARS-CoV, MERS-CoV and SARS-CoV-2 Clinical and pathological investigation of patients with severe COVID-19 Prognostic value of interleukin-6, C-reactive protein, and procalcitonin in patients with COVID-19 Pathological findings of COVID-19 associated with acute respiratory distress syndrome The possible of immunotherapy for COVID-19: A systematic review The Role of Cytokines including Interleukin-6 in COVID-19 induced Pneumonia and Macrophage Activation Syndrome-Like Disease Altered cytokine levels and immune responses in patients with SARS-CoV-2 infection and related conditions Cytokine-targeted therapy in severely ill COVID-19 patients: Options and cautions IL-6 in inflammation, immunity, and disease Targeting the IL-6/JAK/STAT3 signalling axis in cancer Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. The Lancet C-reactive protein levels in the early stage of COVID-19 Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Intern Med. broad regulator of T helper cell differentiation Lymphocyte subset (CD4+, CD8+) counts reflect the severity of infection and predict the clinical outcomes in patients with COVID-19 The Regulatory Effects of Interleukin-4 Receptor Signaling on Neutrophils in Type 2 Immune Responses Attracting Attention: Discovery of IL-8/CXCL8 and the Birth of the Chemokine Field Targeting IL-10 Family Cytokines for the Treatment of Human Diseases Interleukin-6: A Masterplayer in the Cytokine Network Clinical Characteristics of 51 Patients Discharged from Hospital with COVID-19 in Chongqing，China. Infectious Diseases (except HIV/AIDS) Multiple Enzyme Release, Inflammation Storm and Hypercoagulability Are Prominent Indicators For Disease Progression In COVID-19: A Multi-Centered, Correlation Study with CT Imaging Score Clinical Characteristics and Outcome of Medical Staff Infected with COVID-19 in Wuhan, China: A Retrospective Case Series Analysis. Infectious Diseases (except HIV/AIDS) Interleukin-6 as a potential biomarker of COVID-19 progression Risk factors influencing the prognosis of elderly patients infected with COVID-19: a clinical retrospective study in Wuhan Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19 Dysregulation of Immune Response in Patients With Coronavirus Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan