key: cord-1018153-nqkby912 authors: Liu, Kun; Yang, Tong; Peng, Xue‐Fang; Lv, Shou‐Ming; Ye, Xiao‐lei; Zhao, Tian‐Shuo; Li, Jia‐Chen; Shao, Zhong‐Jun; Lu, Qing‐Bin; Li, Jing‐Yun; Liu, Wei title: A systematic meta‐analysis of immune signatures in patients with COVID‐19 date: 2020-11-20 journal: Rev Med Virol DOI: 10.1002/rmv.2195 sha: c1cfb273a9f19fed31535fdb43789cf32c2f786c doc_id: 1018153 cord_uid: nqkby912 Currently severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) transmission has been on the rise worldwide. Predicting outcome in COVID‐19 remains challenging, and the search for more robust predictors continues. We made a systematic meta‐analysis on the current literature from 1 January 2020 to 15 August 2020 that independently evaluated 32 circulatory immunological signatures that were compared between patients with different disease severity was made. Their roles as predictors of disease severity were determined as well. A total of 149 distinct studies that evaluated ten cytokines, four antibodies, four T cells, B cells, NK cells, neutrophils, monocytes, eosinophils and basophils were included. Compared with the non‐severe patients of COVID‐19, serum levels of Interleukins (IL)‐2, IL‐2R, IL‐4, IL‐6, IL‐8, IL‐10 and tumor necrosis factor α were significantly up‐regulated in severe patients, with the largest inter‐group differences observed for IL‐6 and IL‐10. In contrast, IL‐5, IL‐1β and Interferon (IFN)‐γ did not show significant inter‐group difference. Four mediators of T cells count, including CD3(+) T, CD4(+) T, CD8(+) T, CD4(+)CD25(+)CD127(‐) Treg, together with CD19(+) B cells count and CD16(+)CD56(+) NK cells were all consistently and significantly depressed in severe group than in non‐severe group. SARS‐CoV‐2 specific IgA and IgG antibodies were significantly higher in severe group than in non‐severe group, while IgM antibody in the severe patients was slightly lower than those in the non‐severe patients, and IgE antibody showed no significant inter‐group differences. The combination of cytokines, especially IL‐6 and IL‐10, and T cell related immune signatures can be used as robust biomarkers to predict disease severity following SARS‐CoV‐2 infection. Currently, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been on the rise in the worldwide range, with more than 32,000,000 cases and more than 990,000 deaths documented to 28 September 2020. Intensive efforts have been put forward to study the clinical process and outcome of the disease. 1 Predicting outcome in coronavirus disease 19 remains challenging, and the search for more robust methods continues. A broad range of signs and symptoms have been investigated in COVID-19 to predict the disease outcome, while showing divergent results. [2] [3] [4] [5] [6] Inclusion more specific biomarkers is urgently needed to develop a robust algorithm. Previous studies have suggested that lymphocytopenia and inflammatory cytokine storm are typical abnormalities in infections caused by highly pathogenic coronavirus, such as SARS and MERS. 7, 8 Similarly, numerous studies on COVID-19 patients have reported a decrease in peripheral blood lymphocyte count and an increase in serum inflammatory cytokines, [9] [10] [11] [12] which is suggested that the inflammatory factors may be the main reason for adverse progression and poor treatment response in COVID-19, but mostly proposed from small sample studies. 13 If these biomarkers are validated in a large patient cohort, their incorporation into algorithms might prove sufficiently sensitive and specific to be clinically useful, particularly when they can be related to the disease outcome. In the current study, we attempted to address these issues by conducting a systematic meta-analysis using the pooled data for the immune indicators that were evaluated at early disease and among patients with various disease severity. The inclusion of various studies allowed more statistical power for a holistic view of SARS-CoV-2-induced immune mediators among patients with different disease severity, and across various geographic locations. This will also help to identify the immune signatures that better distinguish the development of COVID-19 outcome. This systematic review was not registered. The format of the review used the preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) (Table S1) (Table S2 ). We performed a comprehensive systematic review and metaanalysis to identify the associations of immune cells, cytokines and the severity of COVID-19. Identification of relevant existing literature was performed by an online search in PubMed, Web of Science and EMBASE, for studies published from 1 January 2020 to 15 August 2020. The MESH headings (keywords) searched were 'nCoV' or 'coronavirus' or 'SARS-CoV-2' or 'COVID' and 'cytokine' or 'immunological or 'immunity' or 'Cellular immunity' or 'T cell' or 'B cell' or 'NK cell' or 'antibody'. In addition, the same search strategy was applied to the database of bioRxiv and medRxiv for the unpublished studies (Table S3) . Two reviewers (TY and XFP) independently screened the list of titles and abstracts, and the full text of chosen manuscripts related the immune mediators. Disagreements on which manuscripts to include during both title and abstract screen, and the subsequent full-text analysis, were discussed until a conclusion was reached with two other reviewers (SML and KL). All studies evaluating individual measurement of immunological indicators in predicting severe infection (as measured by disease severity criteria, or ICU admission or fatal/survived) were included. All studies of any design, from any time since the outbreak started were eligible. To avoid selection bias, no subjective quality criteria were applied to the studies for inclusion. The immunological signatures that were measured at the acute phase of infection were used, and if there was more than one evaluation for the same patient, only the first test results were used. Only those immune signatures investigated in at least three papers were used in the subsequent analysis. Exclusion criteria included the following: (1) Case reports of individual patients, literature reviews, nonhuman studies, editorials, comments, expert opinions or articles with number of patients ≤10; (2) Studies of exclusively paediatric or pregnant patients, due to the varying presentation of the disease in these groups and (3) Studies without adequate baseline information, such as age, sex or geographic region. All the search results were evaluated according to the PRISMA statement. 14 From each study, various details including the baseline information of study population (age, sex, interval from disease onset to hospitalization, intervals from disease onset to the sample collection, study areas), the number of patients in each study group, the measured immunological indicators and their test methods and the definitions used to measure outcome, were extracted into Microsoft Excel. These details are presented in Table 1 . The Newcastle-Ottawa Quality Assessment Scale (NOQAS) was used to assess the quality of the studies included in the meta-analysis and performed by two reviewers (TY and XFP) with a third reviewer (SML) consulted in case of discrepancy. The included studies varied in their differentiation of patients' disease status, with classifications of 'mild, moderate, severe and critical', 'ordinary and severe/critical', 'common and severe', 'acute respiratory distress syndrome (ARDS) and non-ARDS' and 'nonsevere and severe'. To allow comparability between studies for metaanalysis, these were grouped into a single disease severity, with the outcome measure used was severe (including both severe and critical cases, ICU admission, death, ARDS, etc.) versus non-severe disease (including non-severe, mild disease, ordinary disease, non-ICU admission and non-ARDS, etc.). Quantitative syntheses and meta-analyses were analysed using the meta package in the R statistical language (Version 3.6.3). First, we collected the mean and standard deviation (SD) from each value of immune mediators in severe and non-severe groups of COVID-19 patients. Where necessary, the mean and SD were converted from the median and interquartile range (IQR) using a previously standard approach. 155 For some articles, data regarding the immunological signature were extracted from the figures by measuring the pixel positions of the electronic figures and then computing the actual values. For box plots, medians and ranges were used to compute means and SDs, and for scatter plots, the individual values were used to compute means and SDs. Second, forest plots were conducted to illustrate the differences in the two groups. For fear of that the recruited studies used different experiment methods, for which means and differences cannot be pooled directly to estimate the effect, we calculated a dimensionless effect measure from each study for the pooling use. The standardized mean difference (SMD) was computed from means and SDs, and used as the effect size. 156 Finally, we undertook the meta-analyses for each immune mediator. The heterogeneity of the studies was tested by the Cochran Chi-square test and I 2 index, and the pooled SMD were calculated by using the random-effects model. All results were pooled and presented in the forest plots. Leave-one-out sensitivity analysis was applied to detect the robustness of the results. Funnel plot method and Egger's regression were used to test the publication bias. If the funnel plot was asymmetric or p < 0.05, the trim-and-fill method was adopted to further test publication bias. The statistical testing with p < 0.05 was considered to be significant (two-sided). full-text was retrieved and evaluated for eligibility, and then 2861 studies were excluded from the meta-analysis: 1305 studies contained data from only case series, 1,312 studies were literature reviews, 52 studies provided no comparison data between disease severity, and 192 studies didn't provide enough data. As five studies were further excluded because the described immune mediators were investigated in <3 studies (Table S4) , at last 214 studies were included in the qualitative synthesis. Those remained in the study were collated for the meta-analysis consisted of 149 distinct studies that were performed in China (133) , the United States (6), South Korea (2), Singapore (2), the United Kingdom (1), France (1), Germany (1), Italy (1), Spain (1), and both China and USA (1) ( Table 1) . All the included studies had reported patients with severe patients and nonsevere patients. These articles included data from 33,691 patients, 25 .96% (n ¼ 8746) with severe COVID-19 disease and 74.04% (n ¼ 24,945) with non-severe disease. Of these studies, 55 studies had evaluated the data on 10 cytokines, including interleukins 2 (IL-2), IL-2R, IL-4, IL-5, IL-6, IL-8, IL-10, interferon γ (IFN-γ), tumour necrosis factor α (TNF-α) and IL-1β, 1, 9, 10, 157 8 studies investigated the antibodies (IgA, IgG, IgM and IgE) 10,16,20,25,66-69 and 40 studies assessed the T cells [CD3 þ T cells count, CD4 þ T cells count, CD8 þ T cells count, CD4 þ CD25 þ CD127 À Treg cells count, CD3 þ T cells ratio, CD4 þ T cells ratio, CD8 þ T cells ratio and CD4 þ /CD8 þ (Th/ Ts)], [9] [10] [11] [15] [16] [17] [18] [19] [20] 24, 27, 33, 34, 41, 45, 47, 48, [51] [52] [53] 56, 57, 59, 61, 63, [65] [66] [67] [69] [70] [71] [72] [73] [74] [75] [76] [77] [78] [79] 157 and 22 studies estimated the B cells and NK cells (CD16 þ CD56 þ NK cells count, CD19 þ B cells count,CD16 þ CD56 þ NK cells ratio and CD19 þ B cells ratio), 10,11,15-20,24,33,34,41,45,47,48,63,67,69,71- A total of 55 studies were evaluated 10 mediators of cytokines between the severe (n ¼ 3038) and non-severe groups of COVID-19 patients (n ¼ 5895), including IL-2, IL-2R, IL-4, IL-5, IL-6, IL-8, IL-10, IFN-γ, TNF-α and IL-1β with three or more studies included ( Figure S1 ). 1, 9, 10, 157 Compared with the non-severe patients of COVID-19, we found that serum levels of seven cytokines were significantly up-regulated in severe patients, (SMD, À 0.18; 95% CI, À 0.32 to À 0.03, p ¼ 0.02; Figure S2c ). No significant differences were noted in the serum levels of IgE between two groups (SMD, 0.16; 95% CI, À 0.16 to 0.43, p ¼ 0.43; Figure S2d ). T cells ratio, CD4 þ T cells ratio, CD8 þ T cells ratio and CD4 þ /CD8 þ (Th/Ts) in Figure S3 . Compared with the non-severe group, severe group had significantly lower CD3 þ T cells count (SMD, À 1.14; 95% CI, À 1.41 to À 0.88; p < 0.01; Figure S3a ) as well as CD4 þ T cells count (SMD, À 116; 95% CI, À 1.44 to À 0.89; p < 0.01; Figure S3b ), CD8 þ T cells count (SMD, À 1.03; 95% CI, À 1.27 to À 0.79; p < 0.01; Figure S3c ), CD4 þ CD25 þ CD127 -Treg cells count (SMD, À 0.45; 95% CI, À 0.76 to À 0.13; p < 0.01; Figure S3d ), CD3 þ T cells ratio (SMD, À 1.10; 95% CI, À 1.77 to À 0.42; p < 0.01; Figure S3e ), and CD4 þ T cells ratio (SMD, À 0.61; 95% CI, À 1.02 to À 0.19; p < 0.01; Figure S3f ). In contrast, no significant difference was attained for CD8 þ T cells ratio (SMD, À 0.61; 95% CI, À 1.35 to 0.12; p ¼ 0.10; Figure S3g ), or CD4 þ /CD8 þ (Th/Ts) (SMD, 0.16; 95% CI, À 0.10 to 0.42; p ¼ 0.23; Figure S3h ). A total of 22 studies on the evaluation of B cells and NK cells between severe and non-severe COVID-19 patients were included. 10, 11, [15] [16] [17] [18] [19] [20] 24, 33, 34, 41, 45, 47, 48, 63, 67, 69, [71] [72] [73] 157 As shown in Figure S4 , the CD19 þ B cells count and CD16 þ CD56 þ NK cells count in the severe group were significantly lower than those in the nonsevere group with SMDs of À 0.74 (95% CI, À 1.05 to À 0.42; p < 0.01; Figure S4a ), and À 0.61 (95% CI, À 0.84 to À 0.38; p < 0.01; Figure S4b ), respectively. In contrast, the CD19 þ B cells ratio and CD16 þ CD56 þ NK cells ratio were significantly higher in the severe patients than in the non-severe patients with SMDs of 0.35 (95% CI, 0.15-0.55; p < 0.01; Figure S4c ), and 1.19 (95% CI, 0.30-2.07; p < 0.01; Figure S4d ), respectively. Figure S5 , the neutrophils cells count and neutrophils cells ratio in the severe group were significantly higher than those in the non-severe group with SMDs of 0.72 (95% CI, 0.61-0.82; p < 0.01; Figure S5a ), and 0.62 (95% CI, 0.35-0.88; p < 0.01; Figure S5b ), respectively. The monocytes cells ratio and eosinophils cells count were significantly lower in the severe patients than in the non-severe patients of COVID-19 with SMDs of À 0.36 (95% CI, À 0.51 to À 0.21; p < 0.01; Figure S5c ), and À 0.45 (95% CI, À 0.59 to À 0.31; p < 0.01; Figure S5d ), while the monocytes cells count and basophils cells count were comparable between the two groups with SMDs of À 0.06 (95% CI, À 0.15 to 0.04; Figure S5e ), and À 0.14 (95% CI, À 0.43 to 0.15; p ¼ 0.34; Figure S5f ), respectively. The sub-analysis considering only peer-reviewed studies for each immune mediator was performed, and the results were presented in Table 2 , but without obvious difference with those of all the included literatures analysed. The results showed that none of the exclusions altered the results of the previous analysis for cytokines (except for IL-4 and IL-10), four specific antibodies, T cells, B cells, NK cells (except for CD16þCD56þ NK cells ratio), neutrophils, monocytes, eosinophils and basophils, indicating the good reliability and stability of the results of this metaanalysis ( Figure S6 ). For IL-4, one study by Hong et al. 35 had a strong influence on the result of the meta-analysis. For IL-10, Wan et al. 37 study had a strong influence on the result of the meta-analysis. For CD16þCD56þ NK cells ratio, one study by Liu et al. 15 had a strong influence on the result of the meta-analysis. However, the results of meta-analysis were not badly altered to be the opposite. The p value from Egger's regression and funnel plots suggested that the publication bias presented in seven mediators including IL-2R, IL-6, IL-10, CD4þ T cells count, CD3þ T cells ratio, CD8þ T cells ratio and CD16þCD56þ NK cells ratio (Table S5 and Figure S7 ). Therefore, we adopted the trim-and-fill method to further test publication bias. As shown in Table S6 , the results showed that there was LIU ET AL. no significant change in the pooled value change before (p < 0.05) and after (p < 0.05) trim-and-fill, indicating that the original pooled SMD was relatively robust. Inflammation is the body's first coordinated line of defense against tissue damage caused by either injury or infection, involving both the innate and adaptive immune responses. 57 However, exuberant immune responses following infection have been frequently associated with excessive levels of pro-inflammatory cytokines and widespread tissue damage including ARDS. [158] [159] [160] In most previous studies, patients with SARS-CoV-2 infection are associated with a cytokine storm, which is characterized by increased production of IL-2, IL-7 and IL-10, granulocyte-colony stimulating factor, interferon-α-inducible protein 10, monocyte chemoattractant protein 1, macrophage inflammatory protein 1 alpha and TNF-α. 16, 18, 157 However, there had been conflicting opinion as to whether the cytokine storm was responsible for the severe outcome. One argument was that the pathological process of severe COVID-19 disease was mainly due to the direct lung injury that induced the subsequent ARDS, and respiratory depression. In addition to the virus-induced direct lung injury, it is also considered that COVID-19 invasion triggers the immune responses that lead to the activation of immune cells to release many pro-and antiinflammatory cytokines including TNF-α, IL-1β, IL-6 and so on. Overwhelming secretion of cytokines causes severe lung damage, which manifest as extensive damage of pulmonary vascular endothelial and alveolar epithelial cells as well as increased pulmonary vascular permeability, leading to the pulmonary oedema and hyaline membrane formation. 15, 25, 36, 66 Multiple studies have been conducted to characterize the profiles of immune mediator during different phases of the COVID-19 disease in different geographic locations. 43, [161] [162] [163] However, results varied, which might be due to the difference in clinical sample preparations, assay platforms and recursion criteria of the patients among studies. Here by performing meta-analysis on studies that explored the association between cytokine storm and disease severity, we have determined that several cytokines, including IL-2, IL-2R, IL-4, IL-6, IL-8, IL-10 and IFN-γ, were induced to significantly higher levels in severe cases than in non-severe cases, but not for IL-1β or TNF-α. It is notable that IL-6 and IL-10 were two of the cytokines that were most consistently enhanced in severe patients, and with large 9, 25, 26 and also associated with high viremia in COVID-19 patients. The plasma IL-6 level was increased dramatically in SARS-CoV-2-infected patients with cardiac injury, which was associated with fatal outcome induced by fulminant myocarditis. 164 Significantly elevated systemic level of IL-6 have been reported in several COVID-19 patient cohorts and shown to correlate with disease severity. 165 IL-6 level diverges profoundly between nonsurvivors and survivors in the third week after symptom onset and is a predictor of COVID-19 severity and in-hospital mortality, 15, 58 which suggest that IL-6 production might play a more important role than viral burden in the pathogenesis COVID-19, since high viral loads were observed at the early clinical process. 65, [166] [167] [168] In a consistent manner, a study performed on medical staff with COVID-19 disease in Wuhan disclosed normal IL-6 levels on admission were favourable for discharge after infection. 169 Until now, there had been only two studies that showed a reversed direction for the IL-6-severe disease association according to our meta-analysis. 18, 42 All these evidences had supported a critical role of IL-6 in determining the outcome. Transcriptional profiling found that SARS-CoV-2 infection in addition to activating type-I interferon and IL-6-dependent inflammatory responses, also results in robust engagement of the complement and coagulation pathway activation. 170 As a simple, fast and readily available screen, we propose it reasonable to take an immediate evaluation of IL-6 and IL-10 levels upon hospital admission of COVID-19 patients, due to its potential benefits to assess worsening clinical features and disease progression in COVID-19. For example, a notably elevated IL-6 value over a certain level by using a predetermined detection kit and following a standard protocol should alert clinicians to adopt aggressive therapeutic approaches without delay. Accompanying the inflammatory process is the lymphopenia depressed CD4 þ , CD8 þ T cells, NK and B cells in COVID-19 patients. Studies found that acute SARS-CoV-2 infection resulted in broad immune cell reduction including T, NK, monocyte, and dendritic cells (DCs). 171 In the meta-analysed studies, lymphopenia was ubiquitous in severe COVID-19 infection and was associated with adverse outcome. CD3 þ , CD4 þ and CD8 þ T cells counts were always below normal range, and CD19 þ B cells and CD16 þ 56 þ NK cells counts were consistently depressed in the severe versus non-severe cases. Recently studies have shown that the extent of lymphopenia seemingly correlates with COVID-19-associated disease severity and mortality. 2, 4, 24, 68, 70, 71, [172] [173] [174] [175] Patients with mild symptoms, however, typically present with normal or slightly higher T cell counts. 176, 177 The presence of lymphopenia and depressed T cell counts seems to correlate with serum IL-6, IL-10 and TNF-α, which might also act as a signature of severe COVID-19. 34 and critical for reducing mortality. For example, Tocilizumab, a monoclonal antibody targeting the IL-6 receptor, is currently being investigated for the treatment of patients with COVID-19-CSS. 159 The approved randomized controlled trial that evaluates the efficacy and safety of tocilizumab in the treatment of COVID-19 might bring about potential benefit soon. The lymphopenia plays an important role in the pathogenesis of the disease, thus the drugs targeting lymphocyte proliferation or apoptosis (IL-7 and PD1/PD-L1 inhibitors) could help to restore lymphocyte counts in severe patients suffering COVID-19. The recruited studies evaluated by NOQAS in the meta-analysis revealed good quality, which provided the strong evidence for the association between immune signatures and SARS-CoV-2 infection. However, our study was subject to limitations that were inherent to meta-analysis. All types of severe diseases, such as ARDS development, ICU entrance, the critical ill patients, were pooled into one for comparison. This broad range of severe disease, although been defined according to standard criteria, might cause bias away from the actual estimation of the association. However, with all association with these complications undoubtedly toward the same direction, we would consider these results adaptable for the disease severity prediction. Age and comorbidities are important risk determinants of severity and mortality of COVID-19 patients, which effects however was not measured, as there were only few literatures presenting the subgrouping data on the immune signatures and disease severity, based on age or comorbidities. We also failed to consider the effect of therapy on the disease outcome, because most of the therapy information was missing from the included studies, for which further investigation are warranted. Our systematic review and meta-analysis are the first to reveal that multiple immune mediators were significantly associated with clinical outcome in COVID-19 patients in a comprehensive way. A dysregulated immunological response with hypercytokinemia and lymphopenia assembled among severe COVID-19 disease was disclosed. The screening for the currently significant biomarkers, especially cytokine of IL-6, IL-10 and the T cells counts, have important implication in assisting prompt recognition of severe patients and guiding early treatment. Clinical features of patients infected with 2019 novel coronavirus in Wuhan Neutrophil-to-lymphocyte ratio predicts critical illness patients with 2019 coronavirus disease in the early stage Early prediction of disease progression in 2019 novel coronavirus pneumonia patients outside Wuhan with CT and clinical characteristics. medRxiv Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study A new predictor of disease severity in patients with COVID-19 in Wuhan, China. medRxiv Predictors of refractory coronavirus disease (COVID-19) pneumonia COVID-19, SARS and MERS: are they closely related? Immune responses and pathogenesis of SARS-CoV-2 during an outbreak in Iran: comparison with SARS and MERS Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China Dysregulation of immune response in patients with COVID-19 in Wuhan, China Functional exhaustion of antiviral lymphocytes in COVID-19 patients Impaired type I interferon activity and exacerbated inflammatory responses in severe Covid-19 patients Key to successful treatment of COVID-19: accurate identification of severe risks and early intervention of disease progression. medRxiv Preferred reporting items for systematic reviews and metaanalyses: the PRISMA statement The potential role of IL-6 in monitoring coronavirus disease 2019. medRxiv Metabolic disturbances and inflammatory dysfunction predict severity of coronavirus disease 2019 (COVID-19): a retrospective study Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou COVID-19 early warning score: a multiparameter screening tool to identify highly suspected patients. medRxiv Clinical characteristics and immune injury mechanisms in 71 patients with COVID-19. mSphere The clinical course and its correlated immune status in COVID-19 pneumonia Elevations of serum cancer biomarkers correlate with severity of COVID-19 Clinical value of immune-inflammatory parameters to assess the severity of coronavirus disease 2019 Analysis of clinical features of 29 patients with 2019 novel coronavirus pneumonia Clinical and immunological features of severe and moderate coronavirus disease 2019 Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study Predictors of fatality including radiographic findings in adults with COVID-19 Correlation between relative nasopharyngeal virus RNA load and lymphocyte count disease severity in patients with COVID-19 Obesity predisposes to the risk of higher mortality in young COVID patients Renal Involvement and early prognosis in patients with COVID-19 pneumonia Using IL-2R/lymphocyte for predicting the clinical progression of patients with COVID-19 Clinical characteristics of COVID-19 in patients with preexisting ILD: a retrospective study in a single center in Wuhan Clinical course and outcomes of 344 Intensive care patients with COVID-19 The laboratory tests and host immunity of COVID-19 patients with different severity of illness Characteristics of lymphocyte subsets and cytokines in peripheral blood of 123 hospitalized patients with 2019 novel coronavirus pneumonia (NCP). medRxiv Clinical features and outcomes of 98 patients hospitalized with SARS-CoV-2 infection in Daegu, South Korea: a brief descriptive study COVID-19 in a designated infectious diseases hospital outside Hubei province Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19 Clinical characteristics of refractory COVID-19 pneumonia in Wuhan, China Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China The clinical features of the 143 patients with COVID-19 in North-East of Chongqing Clinical characteristics of SARS-CoV-2 pneumonia compared to controls in Chinese Han population Elevated exhaustion levels and reduced functional diversity of T cells in peripheral blood may predict severe progression in COVID-19 patients Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study Risk factors for mortality in 244 Older adults with COVID-19 in Wuhan, China: a retrospective study Letter to the Editor: low-density lipoprotein is a potential predictor of poor prognosis in patients with coronavirus disease 2019 A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection Characteristics and prognostic factors of disease severity in patients with COVID-19: the Beijing experience Clinical and pathological investigation of patients with severe COVID-19 Intensive care risk estimation in COVID-19 pneumonia based on clinical and imaging parameters: experiences from the Munich cohort Clinical characteristics and predictors of mortality in African-Americans with COVID-19 from an inner-city community teaching hospital in New York Clinical characteristics and risk factors for mortality among inpatients with COVID-19 in Wuhan, China Analysis of the clinical characteristics and early warning model construction of severe/critical coronavirus disease 2019 patients Impact of cardiovascular disease on clinical characteristics and outcomes of coronavirus disease 2019 (COVID-19) Clinical characteristics and predictors of survival in adults with coronavirus disease 2019 receiving tocilizumab Epidemiological and clinical features of 125 hospitalized patients with COVID-19 in Risk-adapted treatment strategy for COVID-19 patients Coronavirus disease 2019 in elderly patients: characteristics and prognostic factors based on 4-week follow-up Detectable serum severe acute respiratory syndrome coronavirus 2 viral load (RNAemia) is closely correlated with drastically elevated interleukin 6 level in critically ill Patients with coronavirus disease 2019 Clinical outcomes of COVID-19 in Wuhan, China: a large cohort study Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans Risk factors for severe COVID-19: evidence from 167 hospitalized patients in Anhui Clinical characteristics of imported and second-generation COVID-19 cases outside Wuhan, China: a multicenter retrospective study Suppressed T cell-mediated immunity in patients with COVID-19: a clinical retrospective study in Wuhan COVID in solid organ transplant recipients: initial report from the US epicenter Exuberant elevation of IP-10, MCP-3 and IL-1ra during SARS-CoV-2 infection is associated with disease severity and fatal outcome. medRxiv Clinical features of patients infected with the 2019 novel coronavirus (COVID-19 Lactate dehydrogenase, an independent risk factor of severe COVID-19 patients: a retrospective and observational study Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients Effect of blood analysis and immune function on the prognosis of patients with COVID-19 Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19) Mortality of COVID-19 is associated with cellular immune function compared to immune function in Chinese Han population Study of the lymphocyte change between COVID-19 and non-COVID-19 pneumonia cases suggesting other factors besides uncontrolled inflammation contributed to multi-organ injury. medRxiv Clinical characteristics and risk factors for mortality of COVID-19 patients with diabetes in Wuhan, China: a two-center, retrospective study Decreased T cell populations contribute to the increased severity of COVID-19 Risk factors associated with disease progression in a cohort of patients infected with the 2019 novel coronavirus Plasma IP-10 and MCP-3 levels are highly associated with disease severity and predict the progression of COVID-19 A retrospective study on the epidemiological characteristics and establishment of an early warning system of severe COVID-19 patients Epidemiological characteristics and clinical features of 32 critical and 67 noncritical cases of COVID-19 in Chengdu Characteristics of patients with coronavirus disease (COVID-19) confirmed using an IgM-IgG antibody test Significance of neutrophilto-lymphocyte ratio, platelet-to-lymphocyte ratio for predicting clinical outcomes in COVID-19. medRxiv Clinical findings of patients with coronavirus disease 2019 in Jiangsu province, China: a retrospective, multi-center study Clinical characteristics and chest CT imaging features of critically ill COVID-19 patients Association of clinical and radiographic findings with the outcomes of 93 patients with COVID-19 in Wuhan Abnormalities of peripheral blood system in patients with COVID-19 in Wenzhou, China Clinical course and risk factors for mortality of COVID-19 patients with pre-existing cirrhosis: a multicentre cohort study The value of clinical parameters in predicting the severity of COVID-19 Temporal changes in immune blood cell parameters in COVID-19 infection and recovery from severe infection Early decrease in blood platelet count is associated with poor prognosis in COVID-19 patients-indications for predictive, preventive, and personalized medical approach Clinical course and outcome of 107 patients infected with the novel coronavirus, SARS-CoV-2, discharged from two hospitals in Wuhan Association between clinical manifestations and prognosis in patients with COVID-19 Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus infected pneumonia in Wuhan, China Hypoalbuminemia predicts the outcome of COVID-19 independent of age and co-morbidity The clinical implication of dynamic neutrophil to lymphocyte ratio and D-dimer in COVID-19: a retrospective study in Suzhou China A descriptive study of the impact of diseases control and prevention on the epidemics dynamics and clinical features of SARS-CoV-2 outbreak in Shanghai, lessons learned for metropolis epidemics prevention Clinical characteristics of 51 patients discharged from hospital with COVID-19 in Chongqing, China. medRxiv Neurologic manifestations of hospitalized patients with coronavirus disease 2019 in Wuhan, China Epidemiologic and clinical characteristics of 91 hospitalized patients with COVID-19 in Zhejiang, China: a retrospective, multi-centre case series Clinical characteristics of patients with severe pneumonia caused by the SARS-CoV-2 in Wuhan Development and validation of a clinical risk score to predict the Occurrence of critical illness in hospitalized patients with COVID-19 Low albumin levels are associated with poorer outcomes in a case series of COVID-19 patients in Spain: a retrospective cohort study. Microorganisms Clinical characteristics of and medical Interventions for COVID-19 in Hemodialysis patients in Wuhan Individualized prediction nomograms for disease progression in mild COVID-19 30-day mortality in patients hospitalized with COVID-19 during the first wave of the Italian epidemic: a prospective cohort study Analysis of factors associated with disease outcomes in hospitalized patients with 2019 novel coronavirus disease The clinical and chest CT features associated with severe and critical COVID-19 pneumonia Characteristics of disease progress in patients with coronavirus disease 2019 in Wuhan Hematologic parameters in patients with COVID infection Prognostic value of C-reactive protein in patients with COVID-19 Clinical features and outcomes of 105 hospitalized patients with COVID-19 in Development of a clinical decision support system for severity risk prediction and triage of COVID-19 patients at hospital admission: an International multicenter study Lactate dehydrogenase and susceptibility to deterioration of mild COVID-19 patients: a multicenter nested case-control study Epidemiological and clinical characteristics of coronavirus disease 2019 in Daegu, South Korea Epidemiological and clinical characteristics of 1663 hospitalized patients infected with COVID-19 in Wuhan, China: a single-center experience Epidemiological and clinical features of 291 cases with coronavirus disease 2019 in areas adjacent to Hubei, China: a double-center observational study. medRxiv Clinical characteristics of coronavirus disease 2019 patients in Beijing Clinical features and shortterm outcomes of 221 patients with COVID-19 in Wuhan Clinical characteristics of patients infected with the novel 2019 coronavirus (SARS-Cov-2) in Guangzhou Clinical characteristics and CT imaging features of patients with different clinical types of coronavirus disease 2019 Clinical characteristics and outcomes of 74 patients with severe or critical COVID-19 Clinical characteristics of different subtypes and risk factors for the severity of illness in patients with COVID-19 in Zhejiang, China Clinical and hematological characteristics of 88 patients with COVID-19 Development and validation of a survival calculator for hospitalized patients with COVID-19. medRxiv Characteristics of hospitalized adults with COVID-19 in an Integrated health care system in California Down-regulated gene expression spectrum and immune responses changed during the disease progression in patients with COVID-19 A tool for early prediction of severe coronavirus disease 2019 (COVID-19): a multicenter study using the risk nomogram in Wuhan and Guangdong, China Clinical characteristics and outcomes of patients undergoing surgeries during the incubation period of COVID-19 infection Clinical features and treatment of COVID patients in northeast Chongqing COVID-19 with different severity: a multicenter study of clinical features New onset COVID-19-related diabetes: an indicator of mortality Deep learning for predicting COVID-19 malignant progression Clinical characteristics of coronavirus disease 2019 in Hainan, China. medRxiv Elevated serum IgM levels indicate poor outcome in patients with coronavirus disease 2019 pneumonia: a retrospective case-control study Prognosticfactors for COVID-19 pneumonia progression to severe symptoms based on earlier clinical features: a retrospective analysis Evaluation of SARS-CoV-2 RNA shedding in clinical specimens and clinical characteristics of 10 patients with COVID-19 in Macau Clinical characteristics of non-ICU hospitalized patients with coronavirus disease 2019 and liver injury: a retrospective study Hospitalization and critical care of 109 decedents with COVID-19 pneumonia in Wuhan The use of adjuvant therapy in preventing progression to severe pneumonia in patients with coronavirus disease 2019: a multicenter data analysis. medRxiv Predictors of mortality for patients with COVID-19 pneumonia caused by SARS-CoV-2: a prospective cohort study CT features of SARS-CoV-2 pneumonia according to clinical presentation: a retrospective analysis of 120 consecutive patients from Wuhan city Clinical features and management of severe COVID-19: a retrospective study in Wuxi Preliminary study to identify severe from moderate cases of COVID-19 using combined hematology parameters Delayed-phase thrombocytopenia in patients with coronavirus disease 2019 (COVID-19) The role of peripheral blood eosinophil counts in COVID patients The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients COVID-19: a retrospective cohort study with focus on the over-80s and hospital-onset disease Retrospective study of risk factors for severe SARS-Cov-2 infections in hospitalized adult patients. Polskie Archiwum Medycyny Wewntrznej Myocardial characteristics as the prognosis for COVID-19 patients Clinical features of patients with coronavirus disease 2019 from a designated hospital in Beijing Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019 Analysis of the clinical characteristics, drug treatments and prognoses of 136 patients with coronavirus disease 2019 High incidence of asymptomatic SARS-CoV-2 infection Clinical characteristics of 145 patients with corona virus disease 2019 (COVID-19 Eosinopenia phenotype in patients with coronavirus disease 2019: a multi-center retrospective study from Anhui, China. medRxiv Clinical characteristics of 276 hospitalized patients with coronavirus disease Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range Serum lipids and risk of atherosclerosis in xanthelasma palpebrarum: a systematic review and meta-analysis Immunopathological characteristics of coronavirus disease 2019 cases in Guangzhou Targeting the 'cytokine storm' for therapeutic benefit Acute respiratory distress syndrome Acute respiratory distress syndrome Immunodepletion with hypoxemia: a potential high risk subtype of coronavirus disease Immune phenotyping based on the neutrophil-to-lymphocyte ratio and IgG level predicts disease severity and outcome for patients With COVID-19 A comparative study on the clinical features of coronavirus 2019 (COVID-19) pneumonia with other pneumonias SARS-CoV-2: a potential novel etiology of fulminant myocarditis COVID-19: consider cytokine storm syndromes and immunosuppression SARS-CoV-2 viral load in Upper respiratory specimens of infected patients Viral load of SARS-CoV-2 in clinical samples Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study Epidemiological, clinical characteristics and outcome of medical staff infected with COVID-19 in Wuhan, China: a retrospective case series analysis. medRxiv Immune complement and coagulation dysfunction in adverse outcomes of SARS-CoV-2 infection Acute SARS-CoV-2 infection Impairs dendritic cell and T cell responses Characteristics of peripheral lymphocyte Subset alteration in COVID-19 pneumonia The definition and risks of cytokine release syndrome-Like in 11 COVID-19-infected pneumonia critically ill patients: disease characteristics and retrospective analysis. medRxiv Pathogenic T-cells and inflammatory monocytes incite inflammatory storms in severe COVID-19 patients Immunology of COVID-19: current state of the science Breadth of concomitant immune responses prior to patient recovery: a case report of nonsevere COVID-19 Persistent SARS-CoV-2 presence is companied with defects in adaptive immune system in nonsevere COVID-19 patients. medRxiv We thank all medical staff and health practitioners who have China (81803289, 81825019). The funding agencies had no role in the study design, data collection and analysis, or preparation of the manuscript. The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.