Literature DB >> 35040086

Identification of Parameters Representative of Immune Dysfunction in Patients with Severe and Fatal COVID-19 Infection: a Systematic Review and Meta-analysis.

Rundong Qin1, Li He1, Zhaowei Yang1, Nan Jia1, Ruchong Chen1, Jiaxing Xie1, Wanyi Fu1, Hao Chen1, Xinliu Lin1, Renbin Huang1, Tian Luo1, Yukai Liu1, Siyang Yao1, Mei Jiang2, Jing Li3.   

Abstract

Abnormal immunological indicators associated with disease severity and mortality in patients with COVID-19 have been reported in several observational studies. However, there are marked heterogeneities in patient characteristics and research methodologies in these studies. We aimed to provide an updated synthesis of the association between immune-related indicators and COVID-19 prognosis. We conducted an electronic search of PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane library, and CNKI for studies reporting immunological and/or immune-related parameters, including hematological, inflammatory, coagulation, and biochemical variables, tested on hospital admission of COVID-19 patients with different severities and outcomes. A total of 145 studies were included in the current meta-analysis, with 26 immunological, 11 hematological, 5 inflammatory, 4 coagulation, and 10 biochemical variables reported. Of them, levels of cytokines, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, IgG, and CD4+ T/CD8+ T cell ratio, WBC, neutrophil, platelet, ESR, CRP, ferritin, SAA, D-dimer, FIB, and LDH were significantly increased in severely ill patients or non-survivors. Moreover, non-severely ill patients or survivors presented significantly higher counts of lymphocytes, monocytes, lymphocyte/monocyte ratio, eosinophils, CD3+ T,CD4+T and CD8+T cells, B cells, and NK cells. The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19 containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells, and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with poor prognosis. Therefore, parameters of immune response dysfunction combined with inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict severe patients and those non-survivors.
© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  COVID-19; Hematological parameters; Immunological indices; Inflammatory responses; Meta-analysis

Year:  2022        PMID: 35040086      PMCID: PMC8763427          DOI: 10.1007/s12016-021-08908-8

Source DB:  PubMed          Journal:  Clin Rev Allergy Immunol        ISSN: 1080-0549            Impact factor:   10.817


Introduction

As of 27 September 2021, the outbreak of coronavirus disease 2019 (COVID-19) has affected more than 200 countries, with 231,703,120 confirmed cases and 4,746,620 deaths globally [1]. The disease is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which results in a large number of severe/critical ill patients who require rigorous management in intensive-care units (ICUs) [2-4]. Until now, there has been no consensus on an effective method to eradicate SARS-CoV-2. Prompt recognition and supportive care for potentially severe/critical ill patients are the mainstay treatments to save lives. Our previous study [5] showed that the counts of lymphocytes, T cell subsets, and eosinophils decreased markedly in severely and fatally ill patients. Non-survivors maintained high levels of, or showed an upward trend in, neutrophil (Neu) counts, interleukin-6 (IL-6), procalcitonin (PCT), serum amyloid A protein (SAA), and C-reactive protein (CRP) levels, while levels of these markers held stable or showed a downward trend in survivors. In addition, studies from other research groups have also investigated the correlation between abnormal immune parameters, including white blood cells (WBC), lymphocytes (Lym), and eosinophil (Eos) counts, infection-related variables, serum inflammatory-cytokine levels, and severity or mortality of the disease [5-7]. Indeed, identifying early and sensitive indicators representative of innate and adaptive immune responses to COVID-19 may help predict the disease progression and potential fatal outcomes. The evidence of immune abnormalities associated with disease severity and mortality in COVID-19 patients has been widely reported in many published observation clinical studies. However, these studies presented a significant heterogeneity in demographic characteristics, genetic features, and therapeutic approaches before hospital admission. Although previous systematic meta-analyses provided evidence of immune signatures in patients with COVID-19 in the early phase of the disease outbreak [8-11], a number of studies have emerged that offer updated data on the immune abnormality associated with poor clinical outcomes [12-16]. Therefore, we aimed to obtain updated, comprehensive evidence of the immune index alongside hematological, biochemical, inflammatory, and coagulation parameters in either a severity or mortality cohort to present the interplay between impaired immune responses and multi-system abnormality contributing to disease progression.

Materials and Methods

Search Strategy and Selection Criteria

This systematic review was conducted according to the Preferred Reporting in Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We previously registered this meta-analysis in PROSPERO, and the study registration number is CRD42020196272. We searched seven databases, PubMed, Scopus, Ovid, Willey, Web of Science, Cochrane Library and the China National Knowledge Infrastructure (CNKI), using the advanced search mode in the field “Title/Abstract,” the search terms [“COVID-19” OR “SARS-COV-2”] AND [“biomarkers” OR “predictors” OR “parameters”] AND [“severity” OR “mortality”], from January 1, 2020 to August 20, 2021, without any language restrictions. After removing duplicates by Endnote, two reviewers independently assessed the title, abstract, and full text of each article to identify eligibility. Any disagreements were solved by a discussion with a third reviewer to reach a consensus. We included observational studies that consisted of two groups: (a) patients with different severities of COVID-19 and/or (b) patients who died from COVID-19 compared to those who survived. Articles with computable data about immune-related variables, including immunological and/or hematological, coagulation, inflammatory, and biochemical variables, were included in the current meta-analysis. The following results were excluded: reviews and meta-analysis, case reports, editorials, preprints, correspondences and letters, data papers, notes, comments, news, short surveys, erratums and retractions, guidelines, and mathematical models. Moreover, we used the Newcastle–Ottawa Scale (NOS) to evaluate the quality of each included publication.

Data Collection

Based on the classifications of the COVID-19 Diagnosis and Treatment Guideline in China (Interim version 8) [17], the severity of disease was classified as four types: mild, moderate, severe and critical. As the originally reported clinical groups were highly diverse among the included publications, we attempted to combine them into two groups, severe COVID-19 and non-severe COVID-19, for further meta-analysis. The strategy for this combination was as follows: (1) groups consisting of severe or critical cases, cases treated in ICUs, aggravations, refractory disease, and ARDS cases; and (2) groups consisting of non-severe, mild, moderate, common, ordinary, or general cases, cases not treated in ICUs, no aggravations, and cases without ARDS were placed into the non-severe COVID-19 group. Raw published/publicly available data were extracted, verified in duplication, and combined into a single database. In order to present the detailed characteristics of included studies, we extracted basic information of each study, which included the first author, year of publication, country and region, language, original reported groups, combined groups, average age, gender, and sample size of the “case and control groups.” We defined “severe and non-survivors” as “case groups” and “non-severe and survivors” as “control groups.” We also described the collected parameters in each study, including immunological and hematological parameters that are closely associated with immune function, and a few indexes reflecting infection, coagulation, and biochemical status. The final item was the quality score of studies, evaluated by the Newcastle–Ottawa Scale, with a higher score meaning higher quality.

Statistical Analysis

All analyses were performed using R software version 3.6.2 (package: meta/metafor; R Project for Statistical Computing, https://www.r-project.org). We divided studies into two separate cohorts for analysis: a severity cohort and a mortality cohort. For the meta-analysis, we transformed the format of laboratory variables presented as “median [interquartile range (IQR)]” into that of “mean [standard deviation (SD)]” [18, 19]. The value of “mean (SD)” of each included variable in the combined groups was calculated with the raw data from the originally reported groups using the formula proposed by Zhang et al. [20]. Standardized mean differences (SMDs) and 95% confidence intervals (95%CIs) were calculated as the primary metrics for each laboratory variable. Laboratory data was pooled whenever two or more publications reported a given variable. We quantified the variations in observed laboratory variables across studies attributable to heterogeneity using the I statistic, a metric ranging from 0% (indicating that all the heterogeneity was spurious) to 100% (indicating that all the heterogeneity was “real” and required further examination or explanation). To probe the sources of heterogeneity, we conducted a meta-regression analysis with three potential factors: the approach of combining disease severity, age, and region. The included variables that presented high heterogeneity (I > 50%) and were reported by an adequate number of studies (n ≥ 10) were applied to the analysis. In addition, the robustness of the results was applied by performing leave-one-out sensitivity analysis. The funnel plot method was used to test the publication bias.

Results

Figure 1 shows the flow diagram of selecting studies according to the PRISMA guidelines. We identified a total of 8552 records by searching seven databases. After removing duplicates, we screened the title and abstract of 5461 articles and excluded ineligible study designs (n = 2061) and unrelated to the topic (n = 1782). Then, we assessed 1618 full-text articles and excluded 1473 publications, mainly owing to no targeted groups (n = 654) and lacking of available and computable laboratory data (n = 819). Ultimately, we included 145 eligible publications in the systematic review and meta-analysis [5, 21–164]. Among the included studies, 91 ones were from China; and 54 studies were from America, Pakistan, Japan, Italy, France, Turkey, Korea, UK, Saudi Arabia, Egypt, India, Serbia, Greece, Libya, Spain, Iran, Mexico, Poland, Germany, and the Netherlands. All studies reported that laboratory variables were measured on admission or early during the hospitalization. There were 137 studies published in English and 8 studies published in Chinese. The characteristics of the included studies are presented in Table 1. Detailed results of the quality assessment of the included studies are presented in Fig. E1.
Fig. 1

PRISMA flowchart of the study selection process

Table 1

Characteristics of included studies

StudyRegionLanguageOriginal reported groupsCombined groups†Sample size‡Case groupsControl groupsCollected parametersQuality score
Age (y)Male [n (%)]Age (y)Male [n (%)]ImmunologicalHematologicalInflammatoryCoagulationBiochemical
Chen 2020Chongqing, ChinaChineseCritical/Severe/ModerateSevere/ Non severe143 (36/107)5120 (55.6)4352 (48.6)IL-6WBC, Lym, PLTPCT, CRPD-dimerLDH, CK8
Li 2020Wuhan, ChinaChineseCritical/Severe/ModerateSevere/Non severe62 (44/18)5525 (56.8)507 (38.9)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IgA, IgM, IgE, IgG, C3, C4WBC, Neu, Lym, PLTPCT,CRPAPTT, PTLDH8
Ling 2020Shanghai, ChinaChineseSevere/ Non severeSevere/ Non severe292 (21/271)6619 (90.5)49135 (49.8)CD3+(ab), CD4+(ab), CD8+(ab)WBC, Neu, LymESR,PCT, CRPD-dimer, FIBLDH, CK, cTnI, AST, ALT, CRN9
Lu 2020Wuhan, ChinaChineseSevere/ Non severeSevere/Non severe101 (34/67)6117 (50)4117 (25.4)CD3+(ab), CD4+(ab), CD8+(ab), B(ab), NK(ab), IgA, IgM, IgG, C3, C4WBC, Neu, Lym, PLTCRPNALDH, ALT, AST, CRN, BUN7
Xiang 2020Jiangxi, ChinaChineseSevere/ ModerateSevere/Non severe49(9/40)538 (88.9)4125 (62.5)CD3+(ab), CD4+(ab), CD8+(ab), B(ab), NK(ab)WBC, Neu, Lym, Eos, Mono, PLT, HBPCT, ESR, CRP, SAAAPTT, PT, D-dimer, FIBLDH, TBIL, ALB, AST, ALT, CRN, CK8
Xu 2020Hefei,ChinaChineseSevere/ ModerateSevere/ Non severe155 (30/125)5120 (66.7)4067 (53.6)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, IL-6NACRP, SAAAPTTNA8
Yang 2020Beijing, ChinaChineseDeath/ SurvivalNon survivors/ Survivors94 (13/81)778 (61.5)6637 (45.7)IL-6, IL-8, IL-10, TNF-αWBC, Neu, LymFerritinNACRN, cTnI9
Altschul 2020New York, AmericaEnglishDied/ DischargedNon survivors/ Survivors2354 (621/ 1733)73327 (52.7)63771 (44.5)IL-6WBC, Lym, PLTPCT, CRP, FerritinD-dimerAST, ALT, CRN, BUN, cTnI9
Asghar 2021Karachi, PakistanEnglishA. ICU/ Ward B. Deceased/Recovered + Home isolationA. Severe/Non severe B. Non survivors/ SurvivorsA. 191 (61/130) B. 191 (44/147)53NANANANALMR, NLR, PLR, HB, PLTPCT, CRP, FerritinNALDH7
Awano 2020Tokyo, JapanEnglishSevere/Non severeSevere/Non severe54(21/33)6615 (71.4)4123 (69.7)NAWBC, Lym, EosPCT, FerritinD-dimerLDH8
Cai 2020Shenzhen,ChinaEnglishSevere/Non severeSevere/ Non severe298 (58/240)6139 (67.2)43106 (44.2)IL-6WBC, Neu, Lym, EosPCT, ESR, CRPD-dimerAST, ALT, CK, BUN, CRN, LDH, TBIL, MYO9
Cao 2020Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/ Non severe244 (153/91)6489 (58.2)6044 (48.4)CD4+(ab), CD8+(ab)WBC, Neu, Lym, HB, PLTPCT, CRPNAcTnI, AST, ALT, CRN, CK, LDH, MYO, TBIL8
Chen 2020Wuhan, ChinaEnglishSevere/ ModerateSevere/ Non severe21 (11/10)6110 (90.9)507 (70.0)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), B(ab)WBC, Neu, Lym, HB, PLTPCT, CRP, FerritinAPTT, PT, D-dimerALT, AST, BUN, CRN, CK, LDH, TBIL8
Chen 2020Jiangsu,ChinaEnglishSevere or critical/ Mild/ OrdinarySevere/ Non severe598 (31/567)61302 (53.3)4520 (64.5)CD3+(ab), CD4+(ab), CD8+(ab), IL-6WBC, Neu, Lym, Eos, Mono, PLT, HBPCT, CRP, ESRAPTT, PT, FIBAST, ALT, BUN, CRN, LDH, TBIL8
Chen 2020Wuhan, ChinaChineseCritical/Severe/ModerateSevere/Non severe29 (14/15)NANANANAIL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-αLymCRPNALDH7
Chen 2020Wuhan, ChinaEnglishA. Non survivors/ Survivors B. Critical/Severe/Moderate/MildA. Non survivors/ Survivors B. Severe/Non severeA. 575 (103/445); B. 575 (203/345)A.67 B.61A.69 (67.0)B.131 (64.5)A.54 B.67A.244 (54.8)B.182 (52.8)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, IL-6WBC, Neu, Lym, Eos, Mono, Bas, NLR, PLR, PLT, HBPCT, CRP, Ferritin, SAAAPTT, PT, D-dimerNA8
Chen 2020Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors55 (19/36)7716 (84.2)7218 (50.0)IL-6WBC, Neu, Lym, PLTPCT, ESR, CRPD‐dimerALT, AST, ALB, CRN, LDH, CK8
Chen 2020Wuhan, ChinaEnglishDead/SurviveNon survivors/Survivors274(113/161)6983 (73.0)51171 (62.0)IL-2R, IL-6, IL-8, IL-10, TNF-α, IgA, IgG, C3, C4WBC, Neu, Lym, Mono, HB, PLTPCT, ESR, CRP,FerritinAPTT, PT, D-dimerALT, AST, ALB, BUN, CRN, CK, LDH, cTnI, TBIL9
Chen 2020Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/ Non severe48 (27/21)7424 (88.9)5313 (61.9)IL-6WBC, Neu, LymPCTNACRN, BUN8
Chi 2020Nanjing, ChinaEnglishSevere/Moderate/MildSevere/ Non severe66(8/58)545 (63.0)4232 (55.2)IL-1Ra, IL-1β, IL-8, IL-10, IL-18, TNF-α, IFN-rNANANANA8
Ciceri 2020Milan, ItalyEnglishDead/DischargedNon survivors/Survivors386 (95/291)7570 (73.7)63207 (71.1)IL-6WBC, Neu, Lym, HB, PLT, NLRPCT,CRP, FerritinD-dimerLDH, CK, cTnI, AST, CRN, TBIL9
Dong 2020Wuhan, ChinaEnglishSevere/Non severeSevere/Non severe147 (53/94)5829 (54.7)4334 (36.2)IL-6, IL-10, TNF-αWBC, Neu, LymCRP, ESR,SAAD-dimer, FIBALT, AST, BUN, CRN8
Du 2020Wuhan, ChinaEnglishDeceased/SurvivorsNon survivors/Survivors179 (21/158)7010 (47.6)5687 (55.1)CD4+(ab), CD8+(ab)WBC, Neu, LymPCT, CRPAPTT, PT, D-dimerMYO, ALB, TBIL, ALT, AST, CRN, cTnI8
Feng 2020Wuhan, ChinaEnglishPoor outcome/Good outcomeNon survivors/Survivors114 (20/94)6913 (65.0)6358 (61.7)CD4+(%), CD8+(%), IL-2, IL-4, IL-6, IL-10, IFN-γWBC, Neu, Lym, Mono, HBCRP,FerritinAPTT, PT, D-dimer, FIBALT, AST, BUN, CRN, CK, LDH, cTnI, TBIL9
Feng 2020ChinaEnglishCritical/Severe/ModerateSevere/Non severe476(124/352)5981 (65.3)50190 (54.0)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), TNF-α, IgA, IgM, IgGWBC, Neu, Lym, HB, PLTCRP,PCT, ESRD-dimer, FIBTBIL, ALB, MYO, CRN, LDH, CK, BUN8
Guo 2020Shanghai,ChinaEnglishSevere/Non severeSevere/Non severe200 (19/181) 348(68/280)5746 (67.6)50157 (56.1)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, IL-6, IgA, IgM, IgGNANANANA7
Han 2020Anhui, ChinaEnglishSevere/MildSevere/Non severe154 (32/122)5223 (71.8)4063 (51.6)CD3+(ab), CD4 + T(ab), CD8 + T(ab), B(ab), NK(ab), IL-6WBC, Neu, Lym, PLT, HBPCT, ESR, CRP, SAAD-dimer, FIB, PTALT, AST, ALB, TBIL, BUN, CRN, CK, LDH7
He 2020Wuhan, ChinaEnglishSevere/Non severeSevere/Non severe204 (69/135)6237 (53.6)4242 (31.1)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-2, IL-4, IL-10, TNF, IFN-γ, IgA, IgM, IgE, IgG, C3, C4WBC, Neu, Lym, PLTPCT, CRPPT, D-dimerALT, AST, CRN, LDH, CK, cTnI7
Huang 2020Wuhan, ChinaEnglishDead/AliveNon survivors/Survivors50 (10/40)385 (50.0)3718 (45.0)IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-α,Neu, Lym, Eos, MonoCRPAPTT, PT, D-dimer, FIBALT, AST, cTnI, CK, CRN, BUN9
Huang 2020Wuhan, ChinaEnglishNon survivors/ SurvivorsNon survivors/Survivors151 (15/136)7613 (86.7)5968 (50.0)IL-2R, IL-6, IL-8, TNF-αWBC, LymPCT, CRPNAAST, ALT, BUN, CRN, MYO7
Hue 2020Créteil, FranceEnglishDead/AliveNon survivors/Survivors38 (13/25)68NA57NAIL-6, IL-10NANANANA9
Jiang 2020Wuhan, ChinaEnglishNon-survivor/SurvivorNon survivors/Survivors215 (72/143)7036 (50.0)6669 (48.3)CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab)WBC, Neu, Lym, Mono, HB, PLTPCT, CRPAPTT, PT, D-dimer, FIBALT, AST, ALB, TBIL, LDH, cTnI, CRN, BUN8
Kazancioglu 2020Ankara, TurkeyEnglishSevere/Non severeSevere/Non severe120 (35/85)6020 (57.1)4452 (61.2)IL-6WBC, Neu, Lym, Eos, Mono, Bas, HB, PLTCRP, FerritinAPTT, PT, D-dimerALT, AST, LDH, CK7
Lei 2020Guangzhou, ChinaEnglishSevere & Critical/ Mild & ModerateSevere/Non severe297 (52/245)6032 (61.5)44111 (45.3)NALym, EosCRP,PCTNATBIL, LDH, ALB7
Li 2020Shanghai,ChinaEnglishSevere/Non severeSevere/Non severe322 (26/296)6820 (76.9)49147 (49.8)CD3+(ab), CD4+(ab), CD8+(ab)WBC, Lym, PLTPCT, CRPD-dimerLDH, AST, ALT, TBIL, BUN, CRN, CK7
Li 2020Beijing, ChinaEnglishSevere/Non severeSevere/Non severe69 (26/43)5914 (53.8)4026 (60.5)CD3+(ab), CD4+T(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-1β, IL-6, IL-8, TNF-αWBC, Neu, Lym, Eos, Mono, BasPCT, ESR,CRP, FerritinFIB, D-dimerALB, AST, ALT, LDH9
Liao 2020Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/Non severe380(231/149)67137 (59.3)5569 (46)IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γWBC, Neu, Lym, Eos, Mono, Bas, HB, PLTCRP,FerritinAPTT, PT, D-dimer, FIBLDH9
Liu 2020Wuhan, ChinaEnglishSevere/MildSevere/Non severe140 (33/107)7725 (75.8)6166 (61.7)IL-6NAPCT, CRPNANA9
Liu 2020Wuhan, ChinaEnglishSevere/MildSevere/Non severe40 (13/27)607 (53.8)438 (29.6)IgA, IgM, IgE, IgG, C3, C4WBC, Neu, Lym, Mono, HB, PLT

CRP,Ferritin,

SAA

APTT, PT, D-Dimer, FIBTBIL, ALT, AST, LDH, CK, BUN, CRN7
Lu 2020Shanghai,ChinaEnglishSevere and critical/Mild and moderateSevere/Non severe53(9/44)688 (88.9)5326 (59.1)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, IgA, IgM, IgG, C3, C4WBC, Neu, Lym, Eos, MonoCRP,ESRAPTT, PT, D-dimer, FIBALB, CRN, TBIL, LDH8
Luo 2021Wuhan, ChinaEnglishNon survivors/ SurvivorsNon survivors/Survivors1018(201/817)70133 (66.2)56388 (47.5)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, IL-2R, IL-6, IL-8, IL-10, TNF-αNANANANA8
Lv 2020Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/Non severe354(239/115)60117 (49.0)5458 (50.4)IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γ, IgA, IgM, IgG, C3, C4WBC, Neu, LymPCT, CRPD-dimerBUN, TBIL8
Mo 2020Wuhan, ChinaEnglishRefractory/GeneralSevere/Non severe155(85/70)6131 (44.3)4655 (64.7)IL-6WBC, Neu, Lym, PLTPCT, ESR, CRPD-dimerALT, AST, ALB, CRN, CK, LDH9
Park 2020Daegu, South KoreaEnglishFatal cases/SurvivorNon survivors/Survivors289 (70/219)7742 (60.0)7091 (41.6)NAWBC, Lym, HB, PLTCRP,PCT, ESR, FerritinPTCK, AST, ALT, TBIL, BUN, CRN, LDH, ALB7
Pei 2020Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/Non severe333(189/144)60115 (60.8)5167 (46.5)IL-2R, IL-6, IL-10, TNF-αNeu, Lym, Eos, MonoESR, CRPPT, D-dimerALT, AST, cTnI,BUN9
Qin 2020Wuhan, ChinaEnglishSevere/ModerateSevere/Non severe452(286/ 166)60155 (54.2)5280 (48.2)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab), IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-α, IgA, IgM, IgG, C3, C4WBC, Neu, Lym, Eos, Mono, BasPCT, ESR, CRP, FerritinNANA8
Sinha 2020Newport and London, UKEnglishNon survivors/SurvivorsNon survivors/Survivors39 (17/22)6014 (82.0)5211 (50.0)IL-6WBC, Lym, PLTCRP,PCT, FerritinD-Dimer, FIBALB, cTnI, LDH, CRN8
Sun 2020Jilin, ChinaEnglishA. Severe/Non severe B. Died/ DischargedA. Severe/Non severe B. Non survivors/SurvivorsA. 57(45/12) B. 36 (11/25)6524 (53.3)585 (41.7)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab)WBC, Neu, Mono, Eos, BasNANANA8
Sun 2020Beijing, ChinaEnglishCritical/Severe/Moderate/ MildSevere/Non severe63 (19/44)59NA42NACD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, NK(ab), IL-6WBC, Neu, Lym, Eos, Mono, HB, PLTCRP, ESR, FerritinPT, D-dimer, FIBALB, TBIL, CRN, ALT, AST, LDH, CK, BUN8
Urra 2020SpainEnglishICU/Non ICUSevere/Non severe172 (27/145)6620 (74.1)5884 (57.9)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%)Neu, Lym, NLR, PLRCRP,D-dimerNA8
Wan 2020Chong qing, ChinaEnglishSevere/ModerateSevere/Non severe123 (21/102)61NA43NACD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-4, IL-6, IL-10, TNF-α, IFN-γWBC, Neu, LymNANANA8
Wang 2020Wuhan, ChinaEnglishICU/ Non-ICUSevere/Non severe28(14/14)7110 (71.4)6611 (78.6)IL-2R, IL-6, IL-8, IL-10, TNF-αWBC, Neu, Lym, HB, PLTPCT, ESR, CRP, FerritinPT, APTT, D-dimerCK, LDH, ALT, AST, ALB, TBIL, cTnI, BUN9
Wang 2020ChinaEnglishSevere/CommonSevere/Non severe61(24/37)5615 (62.5)5116 (43.2)NAWBC, Neu, Lym, Mono, PLT, LMR, NLR, PLRPCT,CRPPT, D-dimerAST, LDH, ALB, CRN, CK9
Wang 2020Wuhan, ChinaEnglishDeceased/AliveNon survivors/Survivors119 (16/103)7212 (8.2)5949 (52.8)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+WBC, Neu, Lym, Mono, LMR, NLRPCT,CRPPT, APTT, D-dimer, FIBCK, LDH, ALT, AST, CRN, MYO8
Wang 2020Beijing, ChinaEnglishA. Severe/Moderate B. Non survivors/SurvivorsA. Severe/Non severe B. Non survivors/SurvivorsA. 199(129/70) B. 199(24/175)A.65 B.72A.70 (54.3)B.16 (66.7)A.58 B.62A.29 (41.4)B.86 (49.1)IL-1β, IL-2R, IL-8, IL-10, TNF-αWBC, Neu, Lym, HB, PLTPCT, CRP, FerritinPT, APTT, D-dimer, FIBAST, ALT, ALB, LDH, TBIL, BUN, CRN8
Wang 2020Wuhan, ChinaEnglishDeath/SurvivalNonsurvivors/Survivors339 (65/274)7639 (60.0)69127 (46.4)CD8+(ab), IL-6WBC, Neu, Lym, Mono, HB, PLTPCT, CRPPT, APTT, D-dimerAST, ALT, CRN, CK, cTnI, LDH, BUN9
Wang 2020Wuhan, ChinaEnglishSevere/Non severeSevere/Non severe43(8/35)6.816 (75.0)6.9321 (60.0)CD3+(ab), CD4+(ab), B(ab), NK(ab), IL-2, IL-4, IL-6, IL-10WBC, LymCRPD-dimerLDH, CK, ALT, AST, TBIL8
Wang 2020Wuhan, ChinaEnglishSevere/MildSevere/Non severe69 (14/55)707 (50.0)4025 (45.0)CD4+(%), CD8+(%), IL-2, IL-4, IL-6, IL-10, TNF-αWBC, Neu, Lym, Mono, Eos, HB, PLTPCT, ESR, CRPNAAST, ALT, LDH, CRN8
Wang 2020Wuhan, ChinaEnglishNonsurviving/SurvivingNon survivors/Survivors293(116/ 177)7365 (56.0)5073 (41.2)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab), NK(%), IgA, IgG, C3, C4WBC, Neu, LymPCT, CRPPT, APTT, D-dimerALT, AST, ALB, CRN, BUN, CK, LDH, MYO, cTnI, TBIL7
Wu 2020Wuhan, ChinaEnglishA .ARDS/Without ARDS B. Died/AliveA. Severe/ Non severe B. Non survivors/ SurvivorsA. 201 (84/117) B. 84 (44/40)A.59 B.68A.60 (71.4)B.29 (65.9)A.47 B.49A.68 (58.1)B.31 (77.5)CD3+(ab), CD4+(ab), CD8+(ab), IL-6WBC, Neu, Lym, Mono, PLTESR, CRP, FerritinPT, APTT, D-dimerTBIL, AST, ALT, ALB, CRN, LDH, BUN8
Xie 2020Wuhan,ChinaEnglishSevere/Non severeSevere/Non severe56 (34/22)596 (27.3)5318 (52.9)CD3+(%), CD4+(%), CD8+(%), CD4+/CD8+WBC, Neu, Lym, PLT, HBPCT, CRPPT, APTT, D-dimer, FIBALT, AST, CRN, cTnI, CK, LDH7
Xiong 2020Wuhan,ChinaEnglishSevere/Non severeSevere/Non severe116 (55/61)6438 (69.1)5242 (68.9)CD3+(ab), CD4+(ab), CD8+(ab), IL-6WBC, Neu, Lym, Mono, HB, PLTCRPPT, APTT, D-dimerCRN, BUN, AST, ALT, TBIL, LDH, cTnI, MYO8
Xu 2020Wuhan, ChinaEnglishA. Died/Discharged B. Critical/Severe/MildA. Non survivors/Survivors B. Severe/NonsevereA. 145 (28/117) B. 187 (107/80)A.73 B.64A.17 (60.7)B.73 (68.2)A.55 B.56A.59 (50.4)B.30 (37.5)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-1β, IL-6, IL-10, TNF-αWBC, Neu, Lym, MonoPCT, CRP, SAAPT, D-dimerBUN, CRN, ALT, AST, CK8
Yan 2020Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors48(39/9)7076 (70.4)4938 (44.7)IL-2R, IL-6, IL-8, TNF-αWBC, Neu, Lym, HB, PLTPCT, ESR, CRP, FerritinPT, APTT, FIB, D-dimerALT, AST, ALB, TBIL, CK, LDH, CRN,cTnI, BUN8
Yang 2020Wuhan, ChinaEnglishCritical/Severe/MildSevere/Non severe52 (19/33)NANANANACD4+(ab), CD8+(ab), IL-6WBC, Neu, LymPCT, CRPD‐dimerLDH, AST, ALT, CRN, cTnI8
Yang 2020Shenzhen, ChinaEnglishCritical/Severe/ModerateSevere/Non severe50(36/14)5922 (61.1)507 (50.0)CD4+(ab), CD8+(ab)WBC, Neu, Lym, PLTPCT, CRPNAAST, ALT, CRN, BUN, CK, LDH, TBIL8
Yuan 2020Shenzhen, ChinaEnglishCritical/Severe/ModerateSevere/Non severe214 (92/122)5859 (64.1)4158 (47.5)CD4+(ab), IL-6WBC, Neu, PLTCRPD-DimerALB7
Zhang 2020ChinaEnglishCritical/Severe/Moderate/ MildSevere/Non severe414 (162/251)4434 (57.6)4211 (37.9)NAWBC, Neu, Lym, Mono, LMR, NLR, PLRNANANA7
Jun. Zhang 2020Wuhan, ChinaEnglishDeterioration/DischargeNon survivors/Survivors111 (18/93)6414 (77.8)3832 (34.4)IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γWBC, Neu, Lym, Mono, PLTCRPNACRN, BUN, ALT, AST9
Zhang 2020Wuhan, ChinaEnglishSevere/Non severeSevere/Non severe74 (27/47)7018 (66.7)6118 (38.3)CD3+(ab), CD4+(ab), CD8+(ab), B(ab), NK(ab), IL-6, IgM, IgE, IgGWBC, Neu, Lym, Eos, HB, PLTPCT, ESR, CRP, SAAD-dimerCRN, ALB, AST, ALT, CK, LDH,   cTnI7
Zhao 2020Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors539 (125/414)7171 (56.8)52184 (44.4)CD3+(ab), CD4+(ab), CD8+(ab), B(ab), IL-6, IgA, IgGWBC, Neu, Lym, HB, PLTPCT, CRPNANA9
Zhao 2020aBeijing, ChinaEnglishSevere/MildSevere/Non severe71 (18/53)647 (38.9)4553 (43.4)IL-1β, IL-1Ra, IL-2, IL-4, IL-6, IL-10, IL-18, TNF-αNANANANA9
Zheng 2020Chengdu,ChinaEnglishCritical/ModerateSevere/Non severe99 (32/67)64NA43NACD4+(ab), CD8+(ab)WBC, Neu, LymCRPPT, D-dimerALT, AST, MYO, cTnI7
Zhou 2020Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors191 (54/137)6938 (70.0)5281 (59.0)IL-6,WBC, Lym, HB, PLTPCT, FerritinPT, D-dimerLDH, ALB, ALT, CK,    cTnI8
Zhou 2020Nanchang, ChinaEnglishAggravation group/Non aggravation groupSevere/Non severe17(5/12)420 (0.0)426 (50.0)CD4+(ab), CD8+(ab)WBC, LymNAD-dimerLDH, ALB8
Zhu 2020Ningbo, ChinaEnglishSevere/Non severeSevere/Non severe127 (16/111)589 (56.3)5073 (65.8)IL-2, IL-4, IL-6, IL-10, TNF-α, IFN-γWBC, Neu, Lym, NLR, PLRCRP,ESRD-dimer, FIBNA8
Abers 2020New York, AmericaEnglishCritical/Severe/ModerateSevere/Non severe175 (145/30)NANANANAIL-1β, IL-1Ra, IL-2, IL-4, IL-8, IL-18, TNF-αNANANANA7
G.Açıksarı 2021TurkeyEnglishNon survivors/SurvivorsNon survivors/Survivors223 (36/187)7415 (12.7)57103 (87.3)NAWBC, Neu, Lym, Mono, HB, PLT, LMR, NLR, PLRCRPNANA8
Alhumaid 2021Alahsa, Saudi ArabiaEnglishICU/Non-ICUSevere/Non severe1014(205/809)53116 (56.5)45466 (57.6)NAWBC, Neu, Lym, HB, PLTCRP,ESR, FerritinNACK, AST, ALT, LDH, CRN, CK8
Aly 2021EgyptEnglishCritical/Severe/Non severeSevere/Non severe496(311/185)57181 (58.2)3892 (49.5)NAHB, PLT, LMR, NLR, PLRCRP,FerritinD-dimerNA8
Bellan 2021ItalyEnglishDead/DischargedNon survivors/Survivors664(211/ 453)80144 (68.0)63260 (57.0)NAWBC, Neu, Lym, Eos, NLR, PLTNANANA7
Bergantini 2021ItalyEnglishSevere/Mild to moderateSevere/Non severe24(10/14)658 (80.0)6211 (78.6)CD4+(%), CD8+(%), IL-6WBC, Neu, Lym, Mono, Eos, Bas, PLTCRPNAALT, AST, LDH9
Betti 2021Alessandria, ItalyEnglishSeverec & critical/Mild & moderateSevere/Non severe171 (82/89)5754 (65.9)5150 (56.2)NAWBC, Neu, Lym, Eos, HB, PLTCRP,FerritinAPTT, PT, D-dimer, FIBALT, AST, LDH, TBIL, CRN, cTnI, BUN8
Bg 2021Davangere, IndiaEnglishNon survivors/SurvivorsNon survivors/Survivors100 (25/75)5913 (52.0)4344 (58.7)NALMR, NLR, PLRNANANA8
Cai 2020Wuhan, ChinaEnglishA. Severe/Non-severe B. Death/RecoveryA. Severe/Non-severe B. Non survivors/SurvivorsA. 85(48/37) B. 41(22/19) C. 22(7/15)A.64 B.67C.70A.34 (70.8)B.12 (54.5)C.3 (42.9)A.55 B.50 C.66A.21 (56.8)B.9 (47.4)C.9 (60.0)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, TNF-α, IFN-γWBC, Neu, Lym, HB, PLTCRPAPTT, PT, D-dimerALB, BUN, CRN, CK, AST, ALT9
Capdevila-Reniu 2021Barcelona, ItalyEnglishDead/RecoveredNon survivors/Survivors159 (53/106)8629 (55.0)8347 (44.0)NALymCRP, FerritinD-dimerLDH9
Cekerevac 2021SerbiaEnglishSevere/Moderate/MildSevere/Non severe127 (70/57)6149 (56.3)5238 (66.7)NAWBC, Lym, HB, PLTCRPFIBLDH, CK8
Chen 2020Taiwan, ChinaEnglishSevere/Non severeSevere/Non severe55 (24/31)52.1NANANAIL-1β, IL-1Ra, IL-6, IL-18, TNF-α, IFN-γNANANANA7
Conca 2021Saudi ArabiaEnglishSevere/Moderate/MildSevere/Non severe34 (5/29)745 (100.0)447 (24.1)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab)WBCCRP, FerritinD-dimerNA7
d’Alessandro 2020Siena, ItalyEnglishSevere/Non severeSevere/Non severe54(14/40)6512 (85.7)6521 (52.5)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab)NANANANA8
Deng 2021Guangzhou, ChinaEnglishSevere & critical/MildSevere/Non severe166 (17/149)599 (52.9)4865 (43.6)CD3+(%), CD4+(%), CD8+(%), CD4+/CD8+HB, PLTNAPT, APTT, D-dimer, FIBLDH, CK, CRN8
Eleni 2021GreeceEnglishA. Death/No death  B. ICU/No ICUA. Non survivors/Survivors B. Severe/ Non severeA. 5 (9/76) B. 85 (17/68)A. 71 B. 60A. 5 (55.6) B. 14 (82.4)A. 60 B. 60A. 44 (57.9) B. 35 (51.5)NALym, PLTCRP, FerritinD-dimer, FIBALT, AST, LDH, cTnI8
Elhadi 2021LibyaEnglishNon survivors/SurvivorsNon survivors/Survivors465(281/184)69153 (54.4)6487 (47.3)NAWBC, Neu, Lym, PLTCRP,PCT, FerritinPT, D-dimer, FIBcTnI8
García de Guadiana-Romualdo 2021SpainEnglishA. Non survivors/Survivors B. Severe/Non- severeA. Non survivors/Survivors B. Severe/Non- severeA. 99 (14/85) B. 99 (25/74)A. 76 B. 70A. 10 (71.4) B. 16 (64.0)A. 64 B. 65A. 51 (60.0) B. 45 (60.8)IL-6WBC, Neu, Lym, NLR, PLT, HBCRP,PCT, FerritinD-dimerCRN, ALB, ALT, LDH9
Huang 2021Wuhan, ChinaEnglishCritical/Severe/ModerateSevere/ Non severe218 (102/116)6857 (49.1)5649 (42)CD3+(ab), CD4+(ab), CD8+(ab), B(ab), NK(ab), IL-6Neu, Lym, Mono, Eos, NLRNANANA8
Karahan 2021TurkeyEnglishA. Severe-Critica/Moderate B. Deceased/SurvivingA. Severe/Non severe B. Non survivors/SurvivorsA. 149 (102/47) B. 149 (69/80)A. 67 B. 68A. 58 (56.9) B. 41 (59.4)A. 56 B. 60A. 23 (48.9) B. 40 (50.0)NAWBC, Neu, Lym, HB, PLTCRPNAALB8
Karampoor 2021IranEnglishICU/Non ICUSevere/ Non severe120 (63/57)6129 (46.0)5235 (61.0)IL-6, IL-10, IL-18NANANANA8
Li 2021Wuhan, ChinaEnglishA. Nonsurvivors/Survivors B. ICU/Non ICUA. Non survivors/Survivors B. Severe/ Non severeA. 211 (95/116) B. (211/312)6956 (58.9)5663 (54.3)IL-6WBC, HBCRP, PCTNABUN, CRN, cTnI, AST, ALT, TBIL, ALB8
Li 2021Changchun,ChinaEnglishSevere or Critical/NonsevereSevere/Non severe285 (90/164)7057 (63.3)6473 (44.5)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab), IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-αWBC, Neu, Lym, Mono, PLT, NLRCRP,PCT, ESRAPTT, PT, D-dimer, FIBLDH, cTnI, AST, ALT, TBIL, ALB, CRN8
Liu 2021Wuhan, ChinaEnglishSevere CommonSevere/Non severe122 (79/43)6346 (58.2)5326 (60.5)IL-6WBC, Neu, LymCRP,PCT, SAA,ESR, FerritinAPTT, PT, D-dimer, FIBAST, ALT, CRN, LDH, CK, MYO, cTnI, BUN, TBIL8
Liu 2020Nanchang,ChinaEnglishSevere/ MildSevere/ Non severe76 (30/46)NANANANACD4+(ab), CD8+(ab), IL-1β, IL-2R, IL-6, IL-8, IL-10LymNAAPTT, PT, D-dimer, FIBCK, LDH7
López- Escobar 2021Madrid, Barcelona and Galicia, SpainEnglishNon survivors/SurvivorsNon survivors/Survivors2088 (321/1767)82213(66.4)661032(58.4)NAWBC, Neu, Lym, Mono, NLR, PLTCRPAPTT, PT, D-dimerAST, ALT, LDH, CRN7
Lu 2021Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors77 (40/37)6029 (73.0)5721 (57.0)NAWBC, Neu, LymCRP,PCT, ESR, FerritinAPTT, PT, D-dimerAST, ALT, CRN, LDH, CK, MYO, cTnI, BUN, TBIL9
Marín-Corral 2021SpainEnglishCritical/Severe/ModerateSevere/Non severe49 (36/13)5117 (47.2)597 (53.8)NAWBC, LymPCTD-dimer, FIBLDH9
Montrucchio 2021Turin, Northern-ItalyEnglishNon survivors/SurvivorsNon survivors/Survivors57(31/26)6628 (90.3)6022 (84.6)NAWBC, LymCRP,PCTD-dimerLDH8
Nakamura 2021Tokyo, JapanEnglishNon survivors/SurvivorsNon survivors/Survivors32(11/21)7410 (91.0)6712 (57.0)NAWBC, Neu, Lym, HB, PLTCRP, FerritinD-dimerCRN, ALB, TBIL, LDH9
Namendys-Silva 2021MexicoEnglishDead/ AliveNon survivors/Survivors164 (85/79)5759 (69.4)4955 (69.6)NAWBC, Neu, Lym, PLTCRP, FerritinD-dimerCRN, TBIL8
Özdemir 2021TurkeyEnglishDeceased/ SurvivingNon survivors/Survivors350 (55/295)7329 (52.7)50165 (55.9)NAWBC, Lym, HBCRPD-dimercTnI, CRN, AST, ALT, ALB7
Peiro 2021SpainEnglishNon survivors/SurvivorsNon survivors/Survivors196 (37/159)7623 (62.2)6394 (59.1)NAWBC, Lym, HB, PLTCRPD-dimerLDH, cTnI8
Provencio 2021SpainEnglishDied/ SurvivedNon survivors/Survivors447 (146/301)68NA67NANANeu, Lym, Mono, NLRCRPD-dimerLDH, ALB8
Qin 2021Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors262 (23/239)6910 (43.5)61113 (47.3)CD3+(ab), CD4+(ab), CD8+(ab), C3, C4WBC, Neu, Lym, MonoCRPNAAST, ALT, CRN, LDH, TBIL8
Quartuccio 2021Udine, ItalyEnglishPatients with P/F < 300/Patients with P/F ≥ 300Severe/ Non severe67(22/45)5817 (77.3)5932 (71.1)IL-6, IL-18WBC, Neu, LymCRPD-dimerLDH, CK9
Sai 2021Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors47 (15/32)717 (46.7)7023 (71.9)IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-αWBC, Neu, Lym, HB, PLTCRP,PCTD-dimerLDH, AST, CRN, cTnI, TBIL9
Salto‑Alejandre 2021Seville, SpainEnglishSevere/ Moderate/ MildSevere/ Non severe321 (85/236)7450 (58.8)60119 (50.4)NAWBC, Neu, LymCRPD-dimerCRN, AST, LDH8
Scotto 2021ItalyEnglishUnfavourable Outcome/Favourable OutcomeNon survivors/Survivors34 (15/19)NANANANAIL-6WBC, Neu, LymCRPD-dimerNA7
Song 2021Hubei, ChinaEnglishCritical/Severe/Mild&moderateSevere/ Non severe295 (107/188)6767 (62.6)5188 (46.8)IL-6WBC, Lym, PLTNAD-dimerALT, AST, BUN, CRN, TBIL7
Sozio 2021ItalyEnglishDeath or IOT/Not death and not IOTNon survivors/Survivors111 (28/83)6422 (78.6)6244 (53.0)CD4+/CD8+, IL-1β, IL-6, IL-8, TNF-αWBC, Neu, LymCRP,PCTD-dimerLDH, CK, CRN8
Stachura 2021Kraków, PolandEnglishSevere/ Non severeSevere/ Non severe100(47/53)62.330 (63.8)56.533 (62.3)IL-6WBC, Neu, LymCRP,PCT, FerritinAPTT, D-dimerAST, MYO, cTnI, LDH9
Tang 2021Wuhan, ChinaEnglishCritical/Severe/CommonSevere/ Non severe100 (44/56)4925 (56.8)3931 (55.4)IL-6LymPCTNANA8
Tao 2021Wuhan, ChinaEnglishSevere/ Non severeSevere/ Non severe222 (20/202)6812 (60.0)54130 (64.4)NAWBC, Neu, Lym, Mono, Eos, Bas, HB, PLTCRP,PCT, ESRAPTT, PT, D-dimerMYO, LDH, ALT, AST, TBIL, BUN8
Tepasse 2021GermanyEnglishCritical/Severe/Non severeSevere/ Non severe40(31/9)5929 (93.5)557 (77.8)IL-6WBCCRP,PCT, FerritinD-dimerCRN, ALT, ALB8
Viana-Llamas 2021SpainEnglishDeceased /AliveNon survivors/Survivors609 (128/481)8085 (66.4)66282 (58.6)NAWBC, Lym, HB, PLTCRP, FerritinD-dimer, FIBcTnI, LDH, AST, ALB, CRN8
Wang 2021Wuhan, ChinaEnglishCritical/Severe/Non severeSevere/ Non severeA.211 (100/111) B.112(46/66)6363 (68.0)4638 (34.2)CD3+(ab), CD3+(%), CD4+(ab), CD4+(%), CD8+(ab), CD8+(%), CD4+/CD8+, B(ab), NK(ab), IL-2, IL-4, IL-6, IL-10, IFN-γWBC, LymNANAAST, ALT8
Wang 2021Wuhan, ChinaEnglishNon survivors/SurvivorsNon survivors/Survivors156 (56/100)7432 (57.1)5444 (44.0)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), IL-6WBC, Neu, Lym, HB, PLTCRP,PCTD-dimerCRN, BUN, LDH, AST, ALT, CK,    cTnI, TBIL8
Waris 2021PakistanEnglishCritical/Severe/Moderate/MildSevere/ Non severe101 (25/76)62.1/ 5617 (68.0)49.1 /43.2453 (69.7)NAWBC, Lym, HB, PLT, LMR, PLR, NLRNANANA7
Xiong 2021ChinaEnglishDead cases/Recovery casesNon survivors/Survivors190 (85/105)7253 (62.4)5946 (43.8)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+, B(ab), NK(ab)WBC, Neu, Lym, HB, PLTCRP,PCTD-dimerLDH, CRN, CK, AST, ALT, BUN, TBIL7
Xue 2021ChinaEnglishSevere/ ModerateSevere/ Non severe289 (63/226)6231 (49.2)5499 (43.8)NAWBC, Neu, LymCRPNANA8
Yang 2021Wuhan, ChinaEnglishNon survivors/ SurvivorsNon survivors/Survivors203 (58/145)6738 (65.5)5677 (53.1)IL-6WBC, Neu, LymCRPAPTT, PT, D-dimerCK, MYO, cTnI, LDH, ALT, AST, TBIL, ALB, CRN, BUN8
Zayat 2021Heinsberg,GermanEnglishNon survivors/ SurvivorsNon survivors/Survivors17(8/9)574 (50.0)572 (22.0)IL-6WBC, PLT, HBCRP,PCTD-dimer, FIBLDH, CRN, BUN, CK, ALT9
Zhang 2021Wuhan, ChinaEnglishDied/ CuredNon survivors/Survivors208 (26/182)6918 (69.0)62111 (61.0)CD3+(ab), CD3+(%), CD4+(ab), CD8+(ab), B(ab), NK(ab), IL-2R, IL-6, IL-8, IL-10, TNF-α, C3, C4WBC, Neu, Lym, Mono, Eos, Bas, HB, PLTCRP,ESR, FerritinPT, D-dimerAST, ALT, LDH, cTnI, BUN, CRN, TBIL9
Zhao 2021bWuhan, ChinaEnglishSevere/MildSevere/ Non severe285 (74/211)6738 (51.0)6396 (45.0)IL-6Neu, Lym, Mono, Eos, NLR, PLR, LMRCRPPT, D-dimerALT, AST, BUN, CRN8
Ahmad 2021Northern IndiaEnglishMortality/ SurvivalNon survivors/Survivors1448(159/1289)58128 (12.2)47921 (87.8)NAHB, WBC, PLTFerritin, CRPD-dimerALT, AST, ALB, BUN, CRN, LDH7
Akdogan 2021TurkeyEnglishSevere/Non severeSevere/Non severe175(57/118)52NA39NANAWBC, LymCRPD-dimerLDH, AST, ALT, BUN7
Berenguer 2020SpainEnglishDead/ AliveNon survivors /Survivors4037 (1133/ 2904)791119 (68.5)642868 (58.1)IL-6HB, WBC, Neu, Lym, NLR, PLTCRP,PCT, FerritinD-dimerALT, AST, BUN, CRN, ALB, LDH7
Albalawi 2021Saudi ArabiaEnglishNon-survivors/SurvivorsNon survivors /Survivors119 (26/93)6114 (53.9)5366 (71.0)NAWBC, Neu, Lym, HB, PLTCRPD-dimer, PT, APTTAST, ALT, BUN, CRN, LDH, ALB7
Arikan 2021TurkeyEnglishDead/DischargedNon survivors /Survivor225/35371149 (66.2)67203 (57.5)NAHB, WBC, Neu, Lym, PLTFerritin, PCTFIB, D-dimerBUN, CRN, AST, ALT, LDH, ALB7
Chinnadurai 2020Bury, UKEnglishDeceased/AliveNon survivors /Survivors215(86/129)8051 (59.3)6882 (63.5)NAHB, Neu, Lym, NLR, PLTCRPD-dimerALB, ALT8
d’Arminio Monforte 2020ItalyEnglishDeath/ SurvivalNon survivors /Survivors541(174/367)76117 (67.2)61230 (63.0)NAHB, WBC, Lym, PLTCRP,PCT, FerritinD-dimerLDH, CK, ALT, AST, CRN8
Gozalbo-Rovira 2020SpainEnglishICU/pneumology wardSevere/ Non severe51 (24/27)6218 (75.0)5814 (52.0)IL-6LymCRP, FerritinD-dimerLDH8
Gupta 2020IndiaEnglishICU/Non ICUSevere/ Non severe200 (32/168)5120 (62.4)3896 (57.1)NAWBC, Lym, HB, PLTNANABUN, CRN, AST, ALT8
Kaal 2021The NetherlandsEnglishSevere/Non severeSevere/ Non severe142 (41/101)6928 (68.3)5865 (64.4)NAWBC, Lym, PLTCRP,PCT, FerritinNACRN, LDH8
Duan 2020Chongqing, ChinaEnglishSevere/Non severeSevere/ Non severe348 (20/328)58170 (52.0)4414 (70.0)CD3+(ab), CD4+(ab), CD8+(ab), CD4+/CD8+WBC, Lym, NLR, PLT, HBCRP,PCTAPTT, PT, FIB, D-dimerALB, ALT, AST, CRN, BUN, TBIL8
Li 2020Wuhan, ChinaEnglishNon-survivors/SurvivorNon survivors/ Survivors102 (15/87)6811 (73.0)5548 (55.0)IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-αWBC, Neu, Lym, HB, PLTCRP,PCTD-dimer, PTcTnI, ALB, LDH, ALT, AST, TBIL, CRN, BUN8
Li 2021Jinan, ChinaEnglishNon-survivors/SurvivorNon survivors/ Survivors99(9/63)726 (66.7)5729 (43.9)IL-6WBC, Lym, PLTCRP,PCTD-dimerBUN, CRN, CK, LDH8
Aksel 2021TurkeyEnglishNon-survivors/SurvivorNon survivors/ Survivors168 (32/136)7017 (53.1)6273 (53.7)NAWBC, Neu, LymCRPNANA8

Data of age are presened as Mean. NA: not available. Combined groups†: Case group (Non-survivors/Severe)/Control group (Survivors/Non-severe). Sample size‡: Total sample (Case group sample/Control group sample). Quality score*: The Newcastle–Ottawa Scale was used for assessing the quality score of each article, with more stars meaning a higher score

PRISMA flowchart of the study selection process Characteristics of included studies CRP,Ferritin, SAA Data of age are presened as Mean. NA: not available. Combined groups†: Case group (Non-survivors/Severe)/Control group (Survivors/Non-severe). Sample size‡: Total sample (Case group sample/Control group sample). Quality score*: The Newcastle–Ottawa Scale was used for assessing the quality score of each article, with more stars meaning a higher score

Immunological Results

A total of 26 immunological variables were included for comparisons between patients with severe and those with non-severe COVID-19, including IL-1β, IL-1Ra, IL-2, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, tumor necrosis factor-alpha (TNF-α), interferon-γ (IFN-γ), CD3-positive T-lymphocyte absolute count (CD3+ T[ab]), CD3+ T percentage (CD3+T[%]), CD4+T(ab), CD4+T(%), CD8+T(ab), CD8+T(%), CD4+T(ab)/CD8+T(ab) ratio, B-lymphocyte absolute count (B cell[ab]), Natural-killer cell absolute count (NK[ab]), immunoglobulin A (IgA), IgM, IgG, IgE, C3(Complement 3), and C4. Of these, IL-1β, IL-2, IL-2R, IL-4, IL-6, IL-8, IL-10, TNF-α, IFN-γ, CD3+ T(ab), CD3+ T(%), CD4+ T(ab), CD4+T(%), CD8+ T(ab), CD8+T(%), CD4+T(ab)/CD8+T(ab) ratio, B cell(ab), NK cell(ab), IgA, IgM, IgG, C3, and C4 were available for comparisons between non-survivors and survivors infected with SARS-CoV-2. The summarized results are presented in Fig. 2. The detailed forest plots are presented in Fig. E2.
Fig. 2

Summary result of the comparison of immunological parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B)

Severe Versus Non-severe COVID-19 Summary result of the comparison of immunological parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B) IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, IFN-γ, IgA, and IgG were significantly increased in patients with severe versus those with non-severe COVID-19 (IL-1β = 0.13 [95%CI, 0.03 to 0.24], P = 0.0121, I2 = 39.1%; IL-1Ra = 0.71 [95%CI, 0.45 to 0.98], P < 0.001, I2 = 28.6%; IL-2R = 1.05 [95%CI, 0.65 to 1.44], P < 0.0001, I2 = 89%; IL-4 = 0.53 [95%CI, 0.11 to 0.95], P = 0.014, I2 = 92.3%; IL-6 = 1.07 [95%CI, 0.88 to 1.25], P < 0.001, I2 = 91.2%; IL-8 = 0.69 [95%CI, 0.45 to 0.94], P < 0.0001, I2 = 69.5%; IL-10 = 0.91 [95%CI, 0.61 to 1.20], P < 0.001, I2 = 92.9%; IL-18 = 0.71 [95%CI, 0.37 to 1.05], P < 0.001, I2 = 63%; TNF-α = 0.28 [95%CI, 0.05 to 0.51], P = 0.0186, I2 = 87.3%; IFN-γ = 0.44 [0.07; 0.81], P = 0.0196, I2 = 89.2%; IgA = 0.18 [95%CI, 0.07 to 0.29], P < 0.001, I2 = 24.2%; IgG = 0.11 [95%CI, 0.01 to 0.22], P = 0.0335, I2 = 46.6%); whereas CD3+ T(ab), CD3+ T(%), CD4+ T(ab), CD4+ T(%), CD8+ T(ab), CD8+ T(%), Total B cell(ab), NK cell(ab), and IgM were significantly decreased in patients with severe versus those with non-severe COVID-19 (CD3+ T(ab) =  −1.06 [95%CI, −1.24 to −0.89], P < 0.001, I2 = 77.6%; CD3+ T(%) =  −0.58[95%CI, −0.87 to −0.29], P < 0.001, I2 = 78.2%; CD4+ T(ab) =  −1.09 [95%CI, −1.29 to −0.89], P < 0.001, I2 = 86.9%; CD4+ T(%) =  −0.21[95%CI, −0.32 to −0.09], P < 0.001, I2 = 37.9%; CD8+T(ab) =  −1.00 [95%CI, −1.20 to −0.80], P < 0.001, I2 = 86.3%; B cell(ab) =  −0.70 [95%CI, −1.02 to −0.38], P < 0.001, I2 = 87.4%; NK cell(ab) =  −0.56 [95%CI, −0.79 to −0.33], P < 0.001, I2 = 78.1% and IgM =  −0.21 [95%CI, −0.32 to −0.11], P < 0.001, I2 = 26.1%). There were no differences in IL-2, CD8+ T(%), CD4+T/CD8 + T ratio, C3, C4, and IgE between the two groups. Non-survivors Versus Survivors of COVID-19 IL-1β, IL-2R, IL-6, IL-8, IL-10, TNF-α and CD4+T/CD8+T ratio, IgA, and IgG were significantly increased in non-survivors versus survivors of COVID-19 (IL-1β = 0.72 [95%CI, 0.48 to 0.96], P < 0.001, I2 = 40.6%; IL-2R = 1.44 [95%CI, 1.04 to 1.83], P < 0.001, I2 = 84.3%; IL-6 = 1.13 [95%CI, 0.99 to 1.27], P < 0.001, I2 = 83.6%; IL-8 = 1.02 [95%CI, 0.70 to 1.35], P < 0.001, I2 = 81.6%; IL-10 = 1.19 [95%CI, 1.08 to 1.30], P < 0.001, I2 = 49.1%; TNF-α = 0.68 [95%CI, 0.38 to 0.97], P < 0.001, I2 = 83.8%; CD4+T/CD8+T ratio = 0.71[95%CI, 0.30 to 1.11], P = 0.0007, I2 = 94%; IgA = 0.36 [95%CI, 0.23 to 0.49], P < 0.001, I2 = 0%; IgG = 0.39[95%CI, 0.26 to 0.52], P < 0.001, I2 = 27%). CD3+ T(ab), CD4+ T(ab), CD8+ T(ab), CD8+ T(%), B cell(ab), NK cell(ab) and C3 were significantly decreased in non-survivors versus survivors (CD3+ T(ab) =  −1.51 [95%CI, −1.89 to −1.13], P < 0.001, I2 = 94%; CD4+ T(ab) =  −1.12[95%CI, −1.45 to −0.80], P < 0.001, I2 = 94%; CD8+T(ab) =  −1.18[95%CI, –1.57 to −0.78], P < 0.001, I2 = 96%; CD8+ T(%) =  −0.62 [95%CI, −0.79 to −0.45], P < 0.001, I2 = 23%; B cell(ab) =  −0.35 [95%CI, −0.67 to −0.02], P = 0.0367, I2 = 87.7%; NK cell(ab) =  −0.61 [95%CI, −0.83 to −0.40], P < 0.001, I2 = 54%; C3 =  −0.63[95%CI, -1.02 to −0.24], P = 0.0014, I2 = 83%). There were no differences in IL-2, IL-4, IFN-γ, CD3+ T(%), CD4+ T(%), C4, and IgM between the two groups.

Hematological Results

Eleven hematological variables, including WBC, neutrophil (Neu), lymphocyte (Lym), eosinophil (Eos), monocyte (Mono), basophil (Bas) absolute counts and platelet (PLT), hemoglobin (HB), neutrophil/lymphocyte ratio(NLR), lymphocyte/monocyte ratio (LMR), and platelet/lymphocyte ratio (PLR), were included in the meta-analysis for comparisons between patients with severe and non-severe COVID-19. All hematological parameters were available for comparisons between non-survivors and survivors of COVID-19. The summarized results are presented in Fig. 3. The detailed forest plots are presented in Fig. E3.
Fig. 3

Summary result of the comparison of hematological parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B)

Severe Versus Non-severe COVID-19 Summary result of the comparison of hematological parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B) WBC, Neu, NLR, and PLR counts were significantly increased in patients with severe versus those with non-severe COVID-19 (WBC = 0.48 [95%CI, 0.37 to 0.59], P < 0.001, I2 = 83.7%; Neu = 0.73 [95%CI, 0.63 to 0.84], P < 0.001, I2 = 80.2%; NLR = 0.95 [95%CI, 0.70 to 1.20], P < 0.001, I2 = 87%; PLR = 0.47 [95%CI, 0.27 to 0.68], P < 0.001, I2 = 77.3%), whereas Lym, Mono, LMR, Eos, PLT and HB were significantly decreased in patients with severe versus those with non-severe COVID-19 (Lym =  −0.74 [95%CI, −0.87 to −0.61], P < 0.001, I2 = 89.9%; Mono =  −0.10 [95%CI, −0.21 to −0.00], P = 0.0465, I2 = 50.2%; Eos =  −0.39 [95%CI, −0.55 to −0.22], P < 0.001, I2 = 79.1%; LMR =  −0.94 [95%CI, −1.05 to −0.83], P < 0.001, I2 = 46.8%; PLT =  −0.27 [95%CI, −0.41 to −0.133], P < 0.001, I2 = 86.1%; HB =  −0.21 [95%CI, −0.36 to −0.06], P = 0.006, I2 = 83.7%) There was no difference in the Bas count between the two groups. Non-survivors Versus Survivors of COVID-19 Similarly, WBC, Neu, NLR, and PLR were significantly increased in non-survivors versus survivors of COVID-19 (WBC = 0.74 [95%CI, 0.62 to 0.86], P < 0.001, I2 = 90.4%; Neu = 0.96 [95%CI, 0.82 to 1.10], P < 0.001, I2 = 89.9%; NLR = 0.45 [95%CI, 0.08 to 0.82], P = 0.0169, I2 = 97.4%; PLR = 0.44 [95%CI, 0.02 to 0.86], P = 0.038, I2 = 84.1%), whereas Lym, Eos, LMR, PLT and HB were significantly decreased in non-survivors versus survivors (Lym =  −0.70 [95%CI, −0.83 to −0.56], P < 0.001, I2 = 92.5%; Eos =  −0.65 [95%CI, −0.78 to −0.53], P < 0.001, I2 = 50.2%; LMR =  −2.15 [95%CI, −3.77 to −0.54], P = 0.009, I2 = 98%; PLT =  −0.35 [95%CI, −0.43 to −0.26], P < 0.001, I2 = 75%; HB =  − 0.41 [95%CI, −0.61 to −0.21], P < 0.001, I2 = 95.3%). There were no differences in the Mono and Bas count between the two groups.

Other Abnormal Clinical Parameters Deriving from Immune Dysfunction

Beyond immunological and hematological cells, cytokines, antibodies and complements, there are some other laboratory parameters that are related to immune dysfunction and reflect the progression of COVID-19 which have been reported in previous studies [165-168]. In the current study, we simultaneously included coagulation parameters (including prothrombin time(PT), activated partial thromboplastin time(APTT), D-dimer and fibrinogen (FIB)), inflammatory parameters (containing C-reactive protein(CRP), procalcitonin(PCT), erythrocyte sedimentation rate(ESR), serum amyloid A(SAA)) and ferritin, biochemical parameters (including cardiac function related ones such as creatine kinase(CK), cardiac troponin I(cTnI), myoglobin (MYO), lactate dehydrogenase (LDH), liver function related ones such as aspartate aminotransferase(AST), alanine aminotransferase (ALT), total bilirubin(TBIL) and kidney function related ones such as creatinine(CRN), albumin(ALB), blood urea nitrogen(BUN). The summarized results are presented in Fig. 4.
Fig. 4

Summary result of the comparison of coagulation, inflammatory and biochemical parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B)

Summary result of the comparison of coagulation, inflammatory and biochemical parameters between patients with severe COVID-19 and non-severe COVID-19 (A), and between non-survivors and survivors with COVID-19 (B)

Coagulation Results

Four coagulation variables, namely prothrombin time (PT), activated partial thromboplastin time (APTT), D-dimer and fibrinogen (FIB), were included in this study. All coagulation variables were available for comparisons between non-survivors and survivors of COVID-19. The detailed forest plots are presented in Fig. E4. Severe Versus Non-severe COVID-19 The included four coagulation variables were significantly increased in patients with severe versus those with non-severe COVID-19 (PT = 0.60 [95%CI, 0.46 to 0.75], P < 0.001, I2 = 76.7%; APTT = 0.40 [95%CI, 0.13 to 0.67], P = 0.0033, I2 = 91.5%; D-dimer = 0.79 [95%CI, 0.65 to 0.93], P < 0.001, I2 = 86.8%; FIB = 0.62 [95%CI, 0.43 to 0.81], P < 0.001, I2 = 79.1%). Non-survivors Versus Survivors of COVID-19 Similarly, all the four coagulation variables were significantly increased in non-survivors versus survivors of COVID-19 (PT = 0.77 [95%CI, 0.55 to 0.98], P < 0.001, I2 = 90.1%; APTT = 0.26 [95%CI, 0.04 to 0.48], P = 0.0187, I2 = 86%; D-dimer = 0.94 [95%CI, 0.80; 1.09], P < 0.001, I2 = 91.8%). However, there was no difference in FIB between the two groups.

Inflammatory Results

Five inflammatory variables, C-reactive protein (CRP), procalcitonin (PCT), erythrocyte sedimentation rate (ESR), serum amyloid A (SAA) and ferritin, were included for comparisons between patients with severe and those with non-severe COVID-19, Of these, CRP, PCT, ESR and ferritin were available for comparisons between non-survivors and survivors infected with SARS-CoV-2. The detailed forest plots are presented in Fig. E5. Severe Versus Non-severe COVID-19 Levels of all five inflammatory variables were significantly increased in patients with severe versus those with non-severe COVID-19 (CRP = 1.09 [95%CI, 0.96 to 1.22], P < 0.001, I2 = 88.4%; PCT = 0.76 [95%CI, 0.36 to 1.15], P < 0.001, I2 = 97.4%; ESR = 0.68 [95%CI, 0.44 to 0.93], P < 0.001, I2 = 90.4%; ferritin = 0.83 [95%CI, 0.63 to 1.02], P < 0.001, I2 = 86.3%; SAA = 1.13 [95%CI, 0.71 to 1.56], P < 0.001, I2 = 90.8%). Non-survivors Versus Survivors of COVID-19 CRP, PCT, and ferritin were significantly increased in non-survivors versus survivors of COVID-19 (CRP = 1.08 [95%CI, 0.95 to 1.21], P < 0.001, I2 = 91.2%; PCT = 1.00 [95%CI, 0.83 to 1.17], P < 0.001, I2 = 92%; ferritin = 0.78 [95%CI, 0.62 to 0.93], P < 0.001, I2 = 89.9%). There was no difference in ESR between the two groups.

Biochemical Results

Ten biochemical variables, namely creatine kinase (CK), cardiac troponin I (cTnI), myoglobin (MYO), lactate dehydrogenase (LDH), aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin (TBIL), creatinine (CRN), albumin (ALB), and blood urea nitrogen (BUN), were included in this study. All biochemical variables were available for comparisons between non-survivors and survivors of COVID-19. The detailed forest plots are presented in Fig. E6. Severe Versus Non-severe COVID-19 CK, cTnI, MYO, LDH, AST, ALT, TBIL, CRN, and BUN were significantly increased in patients with severe versus those with non-severe COVID-19 (CK = 0.62 [95%CI, 0.41 to 0.82], P < 0.001, I2 = 88.2%; cTnI = 0.54 [95%CI, 0.33 to 0.76], P < 0.001, I2 = 82.9%; MYO = 0.77 [95%CI, 0.51 to 1.06], P < 0.001, I2 = 81.5%; LDH = 1.19 [95%CI, 1.02 to 1.35], P < 0.001, I2 = 88%; AST = 0.71 [95%CI, 0.55 to 0.87], P < 0.001, I2 = 88.8%; ALT = 0.39 [95%CI, 0.31 to 0.47], P < 0.001, I2 = 54.1%; TBIL = 0.36 [95%CI, 0.20 to 0.52],P < 0.001, I2 = 78.9%; CRN = 0.41 [95%CI, 0.29 to 0.52], P < 0.001, I2 = 75.8%; BUN = 0.69 [95%CI, 0.53 to 0.85], P < 0.001, I2 = 80.5%;), whereas ALB was significantly decreased in patients with severe versus non-severe COVID-19 (ALB =  −0.96 [95%CI, −1.08 to −0.83], P < 0.001, I2 = 65.9%). Non-survivors Versus Survivors of COVID-19 Similarly, CK, cTnI, MYO, LDH, AST, ALT, TBIL, CRN, and BUN were significantly increased in non-survivors versus survivors of COVID-19 (CK = 0.79 [95%CI, 0.57 to 1.02], P < 0.001, I2 = 92.3%; cTnI = 1.24 [95%CI, 1.01 to 1.47], P < 0.001, I2 = 92.5%; MYO = 2.67 [95%CI, 1.57 to 3.77], P < 0.001, I2 = 97.3%; LDH = 1.14 [95%CI, 0.94 to 1.34], P < 0.001, I2 = 94.8%; AST = 0.66 [95%CI, 0.53; 0.80], P < 0.001, I2 = 89.9%; ALT = 0.27 [95%CI, 0.10 to 0.43], P = 0.013, I2 = 93.3%; TBIL = 0.47 [95%CI, 0.32 to 0.63], P < 0.001, I2 = 83.7%; CRN = 0.61 [95%CI, 0.37 to 0.84], P < 0.001, I2 = 96%; BUN = 1.07 [95%CI, 0.88 to 1.26], P < 0.001, I2 = 88.1%). In contrast, ALB was significantly decreased in patients with severe versus non-severe COVID-19 (ALB =  −0.86 [95%CI, –1.03 to −0.70], P < 0.001, I2 = 90.9%).

Publication Bias

Funnel plots are shown in Figs. E7 and E8. In severe and non-severe patients of COVID-19, the obvious publication bias was presented in B cell (ab), NK cell (ab), IL-1β, IL-4, IL-6, IL-10, TNF-α, NLR, CRP, D-dimer, and cTnI. In contrast, in non-survivors and survivors of COVID-19, obvious publication bias was present in IL-6, IL-8, IL-10, TNF-α, PLT, HB, CRP, Ferritin, ALT, and ALB. Many factors may have led to the publication bias, such as not enough amounts of originally included studies, different characteristics, and the wide ranges of the parameter results.

Sensitivity Analysis

Results of the sensitivity analysis, using the leave-to-out method, showed that most parameters presented good reliability and stability. However, there were also some parameters showed high sensitivity. Detailed results of each parameter are shown in Figs. E9, E10, E11, E12, and E13.

Investigation of Heterogeneity

A majority of included variables in the current review presented significant heterogeneity (I2 > 50%). The heterogeneity might have come from various factors, such as demographic and clinical characteristics of included patients, time of the symptom onset and laboratory parameters measured, and treatment intervention before the admission. Therefore, we conducted a meta-regression analysis with three potential factors, including the approach of combining disease severity, age, and region, to identify the sources of heterogeneity. The included variables presenting high heterogeneity (I > 50%) and reported by an adequate number of studies (n ≥ 10) were applied to the analysis. Regarding the approach of combing disease severity, we identified four subgroups in our severe group according to the originally reported disease severity: severe and critical (severe/critical), severe alone, critical alone, and other. The findings showed that the potential heterogeneity of 16 of 39 variables, including CD3+T(%), B cell(ab), NK(ab), IL-4, IL-6, IL-8, Lym, Eos, HB, NLR, CRP, Ferritin, LDH, ALB, CRN, and BUN, were related to the originally reported disease severity. The detailed results are presented in Table E1. Second, based on the available average age of severely ill patients and non-survivors of COVID-19, we classified the studies into six subgroups (average age ≤ 18 years(y), 30 ~ 49y, 50 ~ 59y, 60 ~ 69y, 70 ~ 79y, and ≥ 80y). In severe patients, the findings showed that the potential heterogeneity of 13 of 38 variables, including CD3+T(%), IL-8, PLT, HB, ESR, Ferritin, APTT, PT, FIB, cTnI, ALB, CRN, and BUN, were related to the different ages of the patients in the included studies. The detailed results are presented in Table E2. Similarly, the potential heterogeneity of 14 of 30 variables in non-survivors, including CD3+T(%), CD4+T(ab), CD8+T(ab), Neu, PLT, CRP, PCT, Ferritin, D-dimer, cTnI, AST, ALT, TBIL, and CRN, were related to the ages of the patients in different included studies. The detailed results are presented in Table E3. Moreover, we divided the four subgroups according to the continents (Asia, Europe, North America and Africa). In severe groups, the findings showed that the potential heterogeneity of 28 of 30 variables, including CD3+T(ab), CD3+T(%), CD4+T(ab), CD8+T(ab), B cell(ab), NK(ab), IL-4, IL-6, IL-8, TNF-α, WBC, Neu, Lym, Eos, HB, NLR, PCT, Ferritin, APTT, PT, FIB, CK, cTnI, LDH, AST, ALT, TBIL, and CRN, were related to the region. The detailed results are presented in Table E4. In non-survivors, the findings showed that the potential heterogeneity of 25 of 27 variables, including CD4+T/CD8+T ratio, IL-6, IL-8, TNF-α, WBC, Neu, Lym, PLT, HB, NLR, CRP, PCT, Ferritin, APTT, D-dimer, FIB, CK, cTnI, LDH, AST, ALT, TBIL, ALB, CRN and BUN, were related to the region. The detailed results are presented in Table E5. We considered the major source of heterogeneity as the regional differences among our included studies, while the approach of combining disease severity and the age of patients partially contributed to the marked heterogeneity observed.

Discussion

In the current updated meta-analysis, our synthetic results of 145 included studies identified a hypercytokinemia profile, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ, which was associated with increased severity and mortality in patients with COVID-19 infection. By contrast, patients with non-severe COVID-19 and survivors exhibited functional innate and adaptive immune responses, presenting by higher levels of eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells and its subset CD4+ T, and CD8+T. Furthermore, in line with an elevated concentration of proinflammatory cytokines, augmented information (indicated by increased WBC, Neu, NLR, PLR, PCT, ESR, CRP, ferritin, or SAA), coagulation dysfunction (indicated by abnormal D-dimer, FIB, APTT and PT) as well as myocardial/liver/renal injury (indicated by elevated CK, cTnI, MYO, LDH, ALT, AST, TBIL, ALB, CRN, and BUN) were the main clinical abnormalities of patients with COVID-19 infection in the severe and fatal cohort. SARS-CoV-2 infection can initiate a potent immune response, which includes innate immune activation and antiviral immune responses [169, 170]. However, the transition between innate and adaptive immune responses is the core of determining the clinical outcomes and prognosis of COVID-19 infection [171]. Early immune responses against COVID-19 primarily play a protective role in viral clearance, whereas exacerbated and dysregulated immune responses, otherwise known as the “cytokine storm,” can cause tissue damage contributing to poor disease outcomes [172]. An overreactive immune response releases excess pro-inflammatory cytokines and chemokines of which has been well documented [173]. Of these elevated pro-inflammatory cytokines, IL-6 is the most investigated and is a key driver of cytokine dysregulation, which is responsible for the hyper-inflammation in lungs in patients infected with COVID-19 [174]. A recent meta-analysis showed that the anti-IL-6 agent (Tocilizumab) was associated with a lower relative risk of mortality in patients with COVID-19 infection [175]. Other cytokines, such as IL-8 and IL-10, were also proposed to that play a significant role in the inflammatory cascade [176, 177]. We identified an updated abnormal cytokine profile, including IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ, relating to severe COVID-19 infection and fatality. It is well known that cytokine storm and the subsequent inflammation cascade relay on a complex cytokine network. Our synthesis results offer updated evidence on revealing the structure of cytokine networks related to the poor clinical outcomes, which helps clarify the underlying complex inflammatory pathways, so we can target new treatment agents. Current management of COVID-19 is supportive, and respiratory failure from acute respiratory distress syndrome (ARDS) is the leading cause of mortality [178]. Hyperinflammation is the prominent feature of patients with ARDS and those non-survivors. Our previous longitudinal study of 548 revealed that patients who died from COVID-19 infection commonly showed an upward trend for neutrophils, IL-6, and C-reactive protein [5]. Other inflammatory parameters, including WBC, PCT, ESR, and SAA, were also proposed as the predictors of fatality. Our synthesis agrees with the findings of previous studies [179-183]. All patients with COVID-19, regardless of the severity, should be screened for hyperinflammation as precaution for potential ARDS once increases in these indicators are detected. Identification of the early signs of ARDS is critical for early intervention (such as low tidal volumes and prone ventilation) to improve oxygenation and lung compliance. Currently, the rates of bacterial/fungal co-infection reported in patients with COVID-19 appear to be low. Timothy et al. included nine studies and found that only 8% (62/806) of cases of bacterial/fungal co-infection were reported [184]. Nevertheless, our data observed that an increased infectious parameter profile detected on admission was strongly associated with poor clinical outcomes, which suggested that prompt antibiotic therapy should be considered after a comprehensive infectious assessment. Additionally, a combined assessment of using abnormal inflammatory parameters and increased cytokine levels might better identify the subgroup of patients for whom immunosuppression could improve mortality. Beneficial anti-inflammatory effects should be weighed against the potentially detrimental effects of inhibiting anti-viral immunity, thereby delaying virus clearance and perpetuating illness [185]. In addition, we observed substantial decreases in B cells, NK cells, T cells, and its subsets, including CD4+T cells and CD8+ T cells in patients with severe disease, compared to those with non-severe disease. We also found that decreased CD3+T, CD4+T, CD8+ T cells, and higher ratio of CD4+ to CD8+ T cells were associated with a fatal outcome. Our findings were in line with the results from a recent meta-analysis targeting lymphocytes and their subset counts [186] as well as observations from clinical practice. However, the underlying mechanism of observed lymphopenia in severe or fatal COVID-19 patients remains unclear. Based on the current evidence, it is proposed that lymphopenia be relating to the following causes: (1) suppression by cytokine mediation; (2) T cells infected by the virus; (3) T cell exhaustion (4) T cell expansion interfered with by the virus; and (5) organ inflation. Furthermore, our data supported that eosinopenia was associated with both severe disease and a fatal outcome. Our previous study suggested that dynamic changes in blood eosinophil counts might predict COVID-19 progression and recovery [5]. However, the pathophysiology for eosinopenia in COVID-19 remains unclear but is likely multifactorial [187], involving (1) reduced expression of adhesion/chemokine/cytokine, (2) direct eosinophil apoptosis, (3) blockade of eosinophilopoiesis, and (4) inhibition of eosinophil egress from the bone marrow. The finding that eosinophil levels improved in patients before discharge might serve as an indicator of improving clinical status. The presence of the hypercoagulable state in patients with COVID-19 was another marked clinical feature of patients with increased mortality and a more severe form of the disease. The underlying pathophysiology mechanism was also associated with impaired immune responses [188]. SARS-CoV-2 infects host endothelial cells through ACE2 (an integral membrane protein) [189]. Patients with COVID-19 tend to exhibit greater numbers of ACE2-positive endothelial cells [190]. Therefore, vascular endothelial injury is commonly presented in patients with COVID-19. Vascular endothelial injury caused by COVID-19 infection would lead to the formation of microvascular microthrombi, which would trigger active tissue factor expression on macrophages and endothelial cells [191] Elevated tissue factor levels alongside local hypoxia from COVID-19 induced ARDS create a positive thromboinflammatory feedback loop, also known as a cytokine storm [191] The strong interaction between coagulation cascade activation and the cytokine storm might be responsible for the increased incidence of thrombotic events and aggressive inflammatory reactions. Based on our meta-analysis, increased APTT, PT, D-dimer, and FIB were identified as the indicators of coagulation dysfunction contributing to the unfavorable clinical outcomes. Simultaneously increased coagulation parameters and immune index might imply the interplay between overreactive immune responses and coagulation dysfunction which might serve as a more sensitive predicted index of a poor prognosis of COVID-19 infection. Additionally, we also identified several abnormal biochemical parameters representative of myocardial, liver, or renal injury in the severe and non-survivors cohort, such as CK, cTnI, MYO, LDH, ALT, AST, TBIL, ALB, CRN, and BUN. Although the pathophysiological mechanisms underlying myocardial/liver/renal injury by COVID-19 are not well-known so far, innate dysfunction and adaptive immune systems driving the cytokine storm seem to play a role in non-pulmonary organ damage [192-196], particularly those with comorbidities of cardiovascular, liver, and renal diseases. The purpose of this meta-analysis is two-fold. First, to provide robust evidence of identifying a series of abnormal immunological indicators early to distinguish patients with poor clinical outcomes and to offer valuable information for exploring the underlying mechanism of COVID-19 progression. Second, to draw a picture of the interaction between immune abnormality and other body system dysfunction, including coagulation, inflammation, and non-pulmonary function. However, our meta-analysis has limitations. In line with the heterogeneity that characterized these observational studies [197, 198], a majority of included variables presented large I values, indicating significant variations in terms of outcomes observed. Although we attempted to manage this by performing subgroup analysis and meta-regression by disease severity, the age of included patients, and genetic characteristics, the results could not fully explain the source of heterogeneity. We were confined by the methodologies of the studies included, as well as the heterogeneity in characteristics of included patients, such as comorbidities, the therapeutic approach before hospital admission, and the time of symptom onset, which were not provided in the included studies. However, the observed heterogeneity did not impair our main conclusion that severe COVID-19 and mortality were associated with significant abnormalities in the immunological, hematological, coagulation, inflammatory, and biochemical variables. What the heterogeneity suggests is that these abnormalities might show some variation from one country to another, from one city to another, and from one clinical setting to another.

Conclusions

The currently updated meta-analysis primarily identified a hypercytokinemia profile with the severity and mortality of COVID-19, containing IL-1β, IL-1Ra, IL-2R, IL-4, IL-6, IL-8, IL-10, IL-18, TNF-α, and IFN-γ. Impaired innate and adaptive immune responses, reflected by decreased eosinophils, lymphocytes, monocytes, B cells, NK cells, T cells and their subtype CD4+ and CD8+ T cells, and augmented inflammation, coagulation dysfunction, and nonpulmonary organ injury, were marked features of patients with a poor prognosis. Given the strong interplay between immune response dysfunction, aggressive inflammation, coagulation abnormality, and nonpulmonary organ injury, parameters of immune response dysfunction combined with either inflammatory, coagulated, or nonpulmonary organ injury indicators may be more sensitive to predict outcomes in severe patients versus non-survivors. Below is the link to the electronic supplementary material. Supplementary file1: Quality assessment of the included studies (Newcastle–Ottawa Scale). +: high quality; –: low quality; ?: unclear quality (PNG 93 KB) Supplementary file2 (PDF 9025 KB) Supplementary file3 (PDF 7313 KB) Supplementary file4 (PDF 2648 KB) Supplementary file5 (PDF 3906 KB) Supplementary file6 (PDF 8901 KB) Supplementary file7 (DOCX 1391 KB) Supplementary file8 (DOCX 1114 KB) Supplementary file9 (PDF 4437 KB) Supplementary file10 (PDF 4823 KB) Supplementary file11 (PDF 1821 KB) Supplementary file12 (PDF 2378 KB) Supplementary file13 (PDF 4279 KB) Supplementary file14 (DOCX 17 KB) Supplementary file15 (DOCX 17 KB) Supplementary file16 (DOCX 17 KB) Supplementary file17 (DOCX 16 KB) Supplementary file18 (DOCX 15 KB)
  189 in total

1.  Clinical characteristics and outcomes of cancer patients with COVID-19.

Authors:  Fan Yang; Shaobo Shi; Jiling Zhu; Jinzhi Shi; Kai Dai; Xiaobei Chen
Journal:  J Med Virol       Date:  2020-06-02       Impact factor: 2.327

2.  "Real-life" Effectiveness Studies of Omalizumab in Adult Patients with Severe Allergic Asthma: Meta-analysis.

Authors:  Abdulaziz Alhossan; Christopher S Lee; Karen MacDonald; Ivo Abraham
Journal:  J Allergy Clin Immunol Pract       Date:  2017-03-27

3.  [Risks factors for death among COVID-19 patients combined with hypertension, coronary heart disease or diabetes].

Authors:  H Yang; L C Yang; R T Zhang; Y P Ling; Q G Ge
Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2020-06-18

4.  Clinical and immunological features of severe and moderate coronavirus disease 2019.

Authors:  Guang Chen; Di Wu; Wei Guo; Yong Cao; Da Huang; Hongwu Wang; Tao Wang; Xiaoyun Zhang; Huilong Chen; Haijing Yu; Xiaoping Zhang; Minxia Zhang; Shiji Wu; Jianxin Song; Tao Chen; Meifang Han; Shusheng Li; Xiaoping Luo; Jianping Zhao; Qin Ning
Journal:  J Clin Invest       Date:  2020-05-01       Impact factor: 14.808

5.  Predictive factors for disease progression in hospitalized patients with coronavirus disease 2019 in Wuhan, China.

Authors:  Jun Zhang; Miao Yu; Song Tong; Lu-Yu Liu; Liang-V Tang
Journal:  J Clin Virol       Date:  2020-04-28       Impact factor: 3.168

6.  A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster.

Authors:  Jasper Fuk-Woo Chan; Shuofeng Yuan; Kin-Hang Kok; Kelvin Kai-Wang To; Hin Chu; Jin Yang; Fanfan Xing; Jieling Liu; Cyril Chik-Yan Yip; Rosana Wing-Shan Poon; Hoi-Wah Tsoi; Simon Kam-Fai Lo; Kwok-Hung Chan; Vincent Kwok-Man Poon; Wan-Mui Chan; Jonathan Daniel Ip; Jian-Piao Cai; Vincent Chi-Chung Cheng; Honglin Chen; Christopher Kim-Ming Hui; Kwok-Yung Yuen
Journal:  Lancet       Date:  2020-01-24       Impact factor: 79.321

7.  Characteristics and outcomes of coronavirus disease 2019 (COVID-19) patients with cancer: a single-center retrospective observational study in Tokyo, Japan.

Authors:  Shohei Nakamura; Yusuke Kanemasa; Yuya Atsuta; Sho Fujiwara; Masaru Tanaka; Kazuaki Fukushima; Taiichiro Kobayashi; Tatsu Shimoyama; Yasushi Omuro; Noritaka Sekiya; Akifumi Imamura
Journal:  Int J Clin Oncol       Date:  2020-11-23       Impact factor: 3.402

8.  Myocardial injury and risk factors for mortality in patients with COVID-19 pneumonia.

Authors:  Chongtu Yang; Fen Liu; Wei Liu; Guijuan Cao; Jiacheng Liu; Songjiang Huang; Muxin Zhu; Chao Tu; Jianwen Wang; Bin Xiong
Journal:  Int J Cardiol       Date:  2020-09-23       Impact factor: 4.164

9.  Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention.

Authors:  Zunyou Wu; Jennifer M McGoogan
Journal:  JAMA       Date:  2020-04-07       Impact factor: 56.272

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  8 in total

1.  Helminthiasis, eosinophils, COVID-19 and vaccination.

Authors:  Miles B Markus
Journal:  S Afr J Infect Dis       Date:  2022-06-29

2.  T-Cell Subsets and Interleukin-10 Levels Are Predictors of Severity and Mortality in COVID-19: A Systematic Review and Meta-Analysis.

Authors:  Amal F Alshammary; Jawaher M Alsughayyir; Khalid K Alharbi; Abdulrahman M Al-Sulaiman; Haifa F Alshammary; Heba F Alshammary
Journal:  Front Med (Lausanne)       Date:  2022-04-28

3.  Persistence of SARS-CoV-2 total immunoglobulins in a series of convalescent plasma and blood donors.

Authors:  M Carmen Martin; Ana Jimenez; Nuria Ortega; Alba Parrado; Isabel Page; M Isabel Gonzalez; Lydia Blanco-Peris
Journal:  PLoS One       Date:  2022-02-24       Impact factor: 3.240

4.  C-Reactive Protein and Serum Albumin Ratio: A Feasible Prognostic Marker in Hospitalized Patients with COVID-19.

Authors:  Vicente Giner-Galvañ; Francisco José Pomares-Gómez; José Antonio Quesada; Manuel Rubio-Rivas; Javier Tejada-Montes; Jesús Baltasar-Corral; María Luisa Taboada-Martínez; Blanca Sánchez-Mesa; Francisco Arnalich-Fernández; Esther Del Corral-Beamonte; Almudena López-Sampalo; Paula María Pesqueira-Fontán; Mar Fernández-Garcés; Ricardo Gómez-Huelgas; José Manuel Ramos-Rincón
Journal:  Biomedicines       Date:  2022-06-13

Review 5.  Implications of NKG2A in immunity and immune-mediated diseases.

Authors:  Xiaotong Wang; Huabao Xiong; Zhaochen Ning
Journal:  Front Immunol       Date:  2022-08-10       Impact factor: 8.786

6.  The GNB3 c.825C>T (rs5443) polymorphism and protection against fatal outcome of corona virus disease 2019 (COVID-19).

Authors:  Birte Möhlendick; Kristina Schönfelder; Christoph Zacher; Carina Elsner; Hana Rohn; Margarethe J Konik; Laura Thümmler; Vera Rebmann; Monika Lindemann; Karl-Heinz Jöckel; Winfried Siffert
Journal:  Front Genet       Date:  2022-08-09       Impact factor: 4.772

7.  Cytokine levels as predictors of mortality in critically ill patients with severe COVID-19 pneumonia: Case-control study nested within a cohort in Colombia.

Authors:  Francisco José Molina; Luz Elena Botero; Juan Pablo Isaza; Luz Elena Cano; Lucelly López; Lina Marcela Hoyos; Elizabeth Correa; Antoni Torres
Journal:  Front Med (Lausanne)       Date:  2022-09-29

8.  Performance evaluation of the BC-720 auto hematology analyzer and establishment of the reference intervals of erythrocyte sedimentation rate in healthy adults.

Authors:  Guofang Shu; Rui Ding; Rong Ding; Zhi He; Yimin Shen; Dongmei Liu; Zhaohui Duan
Journal:  Ann Transl Med       Date:  2022-09
  8 in total

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