Coronavirus Disease (COVID-19) and the Liver: A comprehensive systematic review and meta-analysis

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Methods: We searched Pubmed and Embase with terms COVID and SARS-COV-2 from December 1, 2019 till April 5, 2020. We estimated overall prevalence, stratified prevalence based on severity, estimated risk ratio (RR) and estimated standardized mean difference (SMD) of liver function parameters in severe as compared to nonsevere COVID. Random effect method utilizing inverse variance approach was used for pooling the data. Results: In all, 128 studies were included. The most frequent abnormalities were hypoalbuminemia [61.27% (48.24 - 72.87)], elevations of gamma-glutamyl transferase (GGT) [27.94%(18.22 -40.27)], alanine aminotransferase (ALT) [23.28%(19.92 - 27.01)] and aspartate aminotransferase (AST) [23.41%(18.84 - 28.70)]. Further the relative risk of these abnormalities was higher in the patients with severe COVID-19 when compared to non-severe disease [Hypoalbuminemia - 2.65(1.38 - 5.07); GGT - 2.31(1.6 - 3.33); ALT - 1.76(1.44 - 2.15); AST 2.30(1.82 - 2.90)]. The SMD of hypoalbuminemia, GGT, ALT and AST elevation in severe as compared to nonsevere were -1.05(-1.27 - -0.83), 0.76(0.40 - 1.12), 0.42(0.27 - 0.56) and 0.69 (0.52 - 0.86) respectively. The pooled prevalence and RR of chronic liver disease as a comorbidity was 2.64% (1.73- 4) and 1.69(1.05-2.73) respectively. Conclusion: The most frequent abnormality in liver functions was hypoalbuminemia followed by derangements in gamma-glutamyl transferase and aminotransferases and these abnormalities were more frequent in severe disease. The systematic review was, however, limited by heterogeneity in definitions of severity and liver function derangements. Critical Care & Emergency Medicine Gastroenterology & Hepatology Infectious Diseases SARS-CoV-2 COVID Cirrhosis aminotransferases alkaline phosphatase Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Coronavirus disease (COVID-19) was first brought to light with the appearance of cases of viral pneumonia in December 2019 in Wuhan city of the Chinese Hubei province. 1 Since then the disease has spread globally and is recognized as a global pandemic by the World Health Organization (WHO). The disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been responsible for large numbers of hospital admissions and mortality resulting in a severe stress on health care resources. With time the understanding of the disease has also improved and it has become apparent that it involves not just the pulmonary system but also the gastrointestinal system, heart and the liver. 2 The hepatic involvement has been well recognized in the two recent pathogenic coronaviruses i.e SARS-COV and Middle east respiratory syndrome coronavirus (MERS-COV). These two viruses had striking genetic similarity (especially SARS-COV) with the novel coronavirus i.e SARS-CoV-2 and therefore hepatic involvement in this is not entirely unexpected. 3 Indeed multiple reports have suggested that elevation of liver transaminases do occur with the infection of SARS-CoV-2. The purported mechanisms include the possibility of direct effect of the the virus on hepatocytes or biliary epithelium, liver injury related to accentuated immune response (cytokine storm) and immune mediated damage, drug toxicity (because of drugs like acetaminophen, antivirals and hydroxychloroquine) and ischemic hepatitis which could occur in patients having multiorgan dysfunction including hemodynamic instability. 4 The biliary epithelium expresses the angiotensin converting enzyme (ACE-2) receptor which is the known binding site of SARS-CoV-2 while the expression in hepatocytes is possibly much lower. However, the receptor expression has been shown to be upregulated in animals models of liver injury. 4 The literature regarding hepatic involvement in COVID-19 is heterogenous with variability in the definitions of liver dysfunction and differences in the clinical presentation and disease severity of patients included in the published reports. 5,6 Therefore, we planned to systematically study the occurrence of liver injury in COVID-19 and also determine the frequency of liver involvement in COVID-19. We also planned to identify any differences in frequency of liver dysfunction with varying disease severity, identify differences in frequency of liver dysfunction in COVID-19 vis-a-vis non-COVID disease and also the frequency of underlying liver disease as a comorbidity in COVID-19 disease. Materials And Methods We conducted this systematic review and meta-analysis as per the guidance provided by the PRISMA statement. 7 Search and Study Selection We searched Pubmed and Embase on 5th April 2019 for publications using the keywords ‘COVID”, “Novel coronavirus” or “SARS-CoV-2” for all publications after 1st December 2019. No other restrictions for language or ethnicity or type of papers were used. The detailed search strategy is shown in Supplementary Table 1. The results obtained from the two databases were then combined and duplicates removed. Two reviewers (PKM, SM) separately did a title and abstract screening to select any studies reporting on data about underlying hepatic comorbidities or liver dysfunction. The studies selected for full texts screening were seen by two authors (SM and VS) for data extraction. Three other authors checked the data for accuracy and completeness (DKJ, JS, AC). The bibliography of selected papers and relevant reviews was also sought to identify any additional eligible papers and an additional search was done using the original search terms AND “Liver” (both databases) to identify any additional papers as on 23rd April 2020. The detailed flow of the study selection is shown using the PRISMA flowchart (Figure 1). Selection of Studies Two investigators (VS and SM) separately determined if the studies were eligible for inclusion in the meta-analysis and the disagreements were discussed with the third author (PKM) for final decision. We included studies 1) reporting on frequency of various liver function abnormalities including serum bilirubin, alanine aminotransferases (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) or gamma glutamyl transferase (GGT) in human patients infected with SARS-CoV-2 2) reporting their median/mean levels for severe and non-severe disease or 3) reporting the frequency of underlying liver disease as a comorbidity in patients with COVID-19. These studies were included irrespective of age, gender, ethnicity of the reported population, the study designs (cohort, case series, randomized trials) and the language of publication. We excluded the studies 1) if number of patients were < 5 2) if studies did not have confirmed cases of COVID-19 3) if none of the relevant liver functions or data on liver disease as a comorbidity were reported and 4) study designs like comments, editorials, reviews and systematic reviews which did not provide primary data. These studies were however, looked at to identify additional papers from bibliography. Study groups and analysis plan We planned to find the pooled prevalence of liver function abnormalities in cases of COVID-19 and compare the frequencies of liver derangements between severe and non-severe COVID-19. We also planned to compare the frequencies of liver derangements between COVID cases and non-COVID cases, if such data were available. We also planned to determine the pooled prevalence of underlying liver disease in patients with COVID-19 and compare if this frequency was different between severe and non-severe disease and between COVID and non-COVID disease. Additionally, we planned to compare the standard mean difference between severe and non-severe COVID and COVID and non-COVID cases. Data Extraction We extracted data as per: authors, location of study, type of study, type of included patients, number of included patients, frequency of various hepatic derangements (elevation of serum bilirubin, ALT, AST, GGT, ALP, serum albumin) in patients with COVID-19 and separately for those with severe and non-severe disease, mean/median values with standard deviation /interquartile range/ range of these parameters from studies which compared severe and non-severe disease and also COVID & non-COVID cases. The details regarding the definition of disease severity in each study and details of definition of acute hepatic injury (or hepatic dysfunction) were also extracted. Statistical analysis The statistical analysis was performed using R statistical software (version 3.6.1). 8 In addition to the base package, meta, readxl and ggplot2 packages were used. 9,10, 11 The number of events were summarized as events per 100 observations. The inverse variance method with logit transformation along with Clopper Pearson confidence interval for individual studies was used for the meta-analytic pooled prevalence in the overall and subgroup population. For difference in prevalence between subgroups, the inverse variance method was used for summarizing. A continuity correction of 0.5 was applied for studies with zero cell frequency. For continuous variable standardized mean differences (SMD) were computed between the evaluated sub-groups and inverse variance method was used for summarizing. Hedges’s g correction was used for bias correction of standardized mean differences. For studies reporting mean and standard deviation, we directly took the reported values for analysis. For studies reporting median and interquartile range or median and range, the mean and standard deviation were computed from the reported values based on Luo 2018 and Wan 2014 methodology. 12,13 For studies reporting only mean along with p value, the t statistics were computed, which was then used for calculation of standard deviation. For studies reporting individual data, we computed mean and SD from the data. Heterogeneity of prevalence, RR and SMD were tested with P value of heterogeneity (p<0.10) and I 2 was computed. I 2 value was taken for reporting for heterogeneity as in addition to quantifying heterogeneity it also assesses the impact of heterogeneity on the meta-analysis. Random effects models were used for summarizing results irrespective of heterogeneity. For prevalence, 95% C.I of pooled prevalence was reported. For studies comparing prevalence and SMD between two groups, p value of <0.05 was considered statistically significant and 95% confidence intervals (CIs) were reported. The forest plots were constructed for visualization of results. Results Search Results and Included Studies The search yielded a total of 6053 citations and additional 28 papers were identified from other sources like bibliography search. After removal of 2206 duplicates, 3875 papers were screened for title and abstract. After removal of 3559 papers for various reasons (Figure 1), a total of 316 papers were eligible for full text screening. Eventually a total of 128 papers were included in at least one of the different analyses which were conducted as part of the meta-analysis (Supplementary Table 2). Overall frequency of various abnormalities in liver function in COVID-19 The pooled prevalence of hyperbilirubinemia reported in various studies was 10.98% (95% CI: 6.87 - 17.08; I 2 : 94%) (Figure 2A) . The pooled prevalence of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation reported in various studies were 23.28% (19.92 - 27.01; 90%) and 23.41% (18.84 - 28.70; 95%) respectively (Figures 3A and 4A). The pooled prevalence of ALP and GGT elevation among overall reported studies were 7.48% (3.91 - 13.83; 75%) and 27.94% (18.22 - 40.27; 93%) respectively (Supplementary Figure 1 and Figure 5A) . The pooled prevalence of hypoalbuminemia among overall reported studies was 61.27% (48.24 - 72.87; 91%) (Figure 6A). The overall pooled frequency of increased globulin levels reported was 20.17% (4.73 - 56.25; 95%) respectively (Supplementary Figure 2). The pooled frequency of acute hepatic injury as reported in various studies is shown in Supplementary Figure 3. The pooled prevalence of hepatitis B, fatty liver, total liver disease and chronic liver disease as a comorbidity are shown in Supplementary Figure 4-7. The pooled prevalence of chronic liver disease as a comorbidity in various studies was 2.49% (1.79-3.46, 84%) (Supplementary Figure 7). The pooled frequency of hepatitis B, nonalcoholic fatty liver disease and total frequency of any liver disease is shown in Supplementary Figures 4, 5 and 6. Comparison between severe and nonsevere COVID-19 The pooled prevalence of bilirubin abnormality among the studies which reported the finding on the basis of underlying severity of COVID-19 was 13.71% (95% CI: 7.53 - 23.69; I 2 : 95%). The pooled frequency of hyperbilirubinemia in severe COVID disease was 18.80% (9.55 - 33.67; 91%) while in non-severe disease it was 9.24% (3.15 - 24.17; 97%) (Figure 2B). The risk ratio (RR) of deranged bilirubin concentration in severe as compared to non-severe subgroups was 1.82 (95% CI: 1.22-2.73; I 2 : 66%) (Figure 2C).The SMD for bilirubin concentration between the severe and non-severe group was 0.43 (95% CI: 0.26 - 0.61; I 2 : 66% ) (Figure 2D). The pooled prevalence of ALT and AST abnormality among the studies reporting severity were 31.31% (25.82 - 37.37; 87%) (Figure 3B) and 33.95% (26.90 - 41.79; 91%) (Figure 4B). The pooled frequency of ALT elevation was 39.58% (30.92 - 48.94; 80%) for severe & 24.15% (17.98 - 31.63; 90%) for nonsevere disease (Figure 3C). The pooled frequency of AST elevation was 49.68% (41.90 - 57.49; 73%) & 19.40% (13.27 - 27.45; 91%) respectively for severe and non-severe disease (Figure 4C). The RR of SGPT and SGOT abnormality in the severe as compared to non-severe subgroups were 1.76(1.44 - 2.15; 65%) and 2.30 (1.82 - 2.90, 67%) respectively (Figures 3D and 4D). The SMD for SGPT and SGOT concentration between the severe and non-severe group were 0.42 (0.27 - 0.56; 70%) and 0.69 (0.52 - 0.86; 76%) respectively (Figures 3E and 4E). The pooled prevalence of ALP and GGT abnormality among the studies reporting severity were 6.99% (4.08 - 11.72; 59%) (Supplementary Figure 1B) and 30.62% (18.13 - 46.79; 94%) (Figure 5B) with subdivision for ALP being 11.33% (5.89 - 20.69; 42%) for severe & 4% (1.68 - 9.26; 64%) for nonsevere and for GGT being 46.90% (25.13 - 69.92; 89%) & 18.66% (9.20 - 34.18; 93%). The RR of ALP and GGT abnormality in severe as compared to non-severe subgroups were 1.99 (0.85 - 4.68; 22%) (Supplementary Figure 1C) and 2.31 (1.6 - 3.33; 55%) (Figure 5C) respectively. The SMD for ALP and GGT concentration between the severe and non-severe group were 0.24 (-0.12 - 0.60; 83%) (Supplementary Figure 1D) and 0.76 (0.40 - 1.12; 82%) (Figure 5D) respectively. The pooled prevalence of albumin abnormality among the studies reporting severity was 61.57% (42.73 - 77.48; 90%) with subdivision of 75.91% (67.02 - 83.02; 35%) for severe and 31.04% (13.72 - 56.02; 84%) for nonsevere (Figure 6B). The RR of albumin abnormality in severe as compared to non-severe subgroup was 2.65 (1.38 - 5.07; 79%) (Figure 6C). The SMD for albumin concentration between the severe and non-severe group was -1.05 (-1.27 - -0.83; 77%) (Figure 6D). The SMD for globulin concentration between severe and nonsevere group was 2.46 (0.24 - 4.69, 99%) (Supplementary Figure 2B) The pooled prevalence of chronic liver disease (CLD) among studies reporting severity was 2.64% (1.73- 4; 72%) with 3.03 (1.97 - 4.64; 21%) among severe and 2.20% (1.16 - 4.15; 83%) among nonsevere (Supplementary Figure 7B). The RR of CLD in severe as compared to non-severe subgroup was 1.69 (1.05-2.73; 0%) (Supplementary Figure 7C) Presence of Acute Hepatic injury (Supplementary Figure 3) The pooled prevalence of acute hepatic injury among overall reported studies was 23.70% (95% CI: 16.31 - 33.11; I 2 : 97%) (Supplementary Figure 3A). Among the studies reporting severity the total frequency of acute hepatic injury was 31.66% (22.66 - 42.27; 91%), whereas in severe disease it was 44.63% (30.13 - 60.11; 88%) and in nonsevere disease it was 20.02% (12.74 - 30.02; 88%) (Supplementary Figure 3B). The RR of acute hepatic injury in severe as compared to nonsevere were: LD 2.18 (1.49 - 3.18, 67%) (Supplementary Figure 3C). Comparison between COVID and non-COVID disease The RR of ALT and AST abnormality in the COVID as compared to non-COVID subgroups were 1.09 (95% CI: 0.55 - 2.15; I 2 : 21%) and 1.02 (0.45 - 2.30; 48%), both statistically non-significant (Figure 2E and 3E). The SMD for SGPT and SGOT concentration between the COVID and non-COVID group were 0.18 (0.05-0.32; 0%) and 0.02 (-0.47 - 0.52; 91%) (Figure 2F and 3F). The SMD of bilirubin, GGT and albumin concentration between COVID and non-COVID subgroup were -0.27 (-0.49 - -0.05, 28%), 0.12 (-0.24 - 0.48; 58%) and 0.82 (0.30 - 1.33; 82%) respectively (Figure 2E, Figure 5E, Figure 6E). Hepatic histological findings in COVID-19 Only limited cases have reported findings on liver histology using either post-mortem histology or liver biopsy in patients with COVID-19 and are tabulated in Supplementary Table 3. The findings reported are non-specific and include sinusoidal dilatation, mild activity in portal area and lobules and occasional necrosis. It is unclear if these are a manifestation of virus mediated liver injury or due to other factors like drugs or immune injury. COVID-19 in Liver transplant recipients Some case reports and studies have reported the outcomes of COVID-19 in patients with liver transplant and are shown in Supplementary Table 4. Discussion In this systematic review, we found that the derangements of liver functions were frequently noted in patients with COVID-19. The most frequent abnormality noted was hypoalbuminemia followed by elevations of gamma-glutamyl transferase, aminotransferases, bilirubin and alkaline phosphatase. Further, when comparison of severe with nonsevere COVID-19 cases was done, liver function abnormalities like hypoalbuminemia, GGT and aminotransferase and bilirubin elevations were more frequent in those with severe disease. However, serum alkaline phosphatase elevations were not significantly higher in the severe group of patients. The pooled frequency of elevation of ALT and AST were similar in the overall COVID cases but interestingly the prevalence of AST elevations was more than ALT in the severe COVID disease. The most frequent abnormality noted in our meta-analysis was hypoalbuminemia. This is possibly related to the fact that albumin is a negative acute phase reactant rather than a manifestation of a hepatic synthetic dysfunction. Our meta-analysis confirms that the liver enzyme elevations in COVID-19, even in the severe COVID category, are mild to moderate in most of the cases. Although there are a few reports of aminotransferase elevation to a high degree (>10 times of upper limit), this is an uncommon phenomenon. 14-15 Further, liver failure is exceedingly rare with only a single case report is available in a patient who had severe COVID associated with use of multiple drugs and progression of liver function derangement after admission. 14 As of now, it is not possible to conclusively ascribe these elevations to be related to direct viral injury. Most of the studies included in our analysis reported use of multiple drugs like antibiotics, antivirals (lopinavir/ritonavir combination, arbidol, oseltamivir, favipiravir, remdesvir, hydroxychloroquine) and steroids. Many of these drugs could have contributed to occurrence of liver dysfunction after hospitalization. Further, ischemia and immune mediated injury due to cytokine storm could be responsible for liver dysfunction in patients with severe COVID disease. SARS-CoV-2 uses the ACE-2 receptor for gaining entry into the cells including the type 2 alveolar epithelial cells in the lungs. Chai et al analyzed the expression of ACE-2 receptors in liver tissue and found that their expression on cholangiocytes (59.7 %) was much stronger than on hepatocytes (2.6%). 16 It has also been observed that ACE-2 expression increases in hepatocytes, in cases of liver injury. 4, 17 At least, one report suggests that viral RNA could be detected in liver tissue raising the possibility of viral mediated liver injury. 18 On the other hand, Chu et al demonstrated significant replication of SARS-CoV-2 on Huh7 (hepatic) cell lines. They also noted that cytopathic effects were seen in a minority of cases, cautioning against an over reliance on the same. 19 Yet the limited histological reports available fail to demonstrate clear cytopathic changes of SARS-Cov-2 ( See Supplementary Table 3) . Further, the comparison of liver function showed that most abnormalities were equally frequent in non-COVID disease suggesting the lack of any specificity for the diagnosis of COVID. Another interesting finding was that the elevations in GGT were similar in frequency to elevations in aminotransferases and were higher than the elevations in alkaline phosphatase. Further, the frequency of patients with elevation of GGT was higher in severe COVID disease when compared to non-severe disease but this was not noted with alkaline phosphatase. The exact reason for this is unclear but GGT is recognized as a surrogate marker for increased oxidative stress and chronic inflammation. 20 It is uncertain if these elevations are related to acute inflammatory stress or are a marker of biliary injury and this finding needs further evaluation. We also looked at the prevalence of underlying liver disease as a comorbidity in the patients with COVID-19 disease and compared the frequency of liver disease as a comorbidity in severe and non-severe COVID cases. We found that the underlying liver disease was found in a significant number of patients with COVID-19. However, the frequency of underlying liver disease was statistically not different between severe and nonsevere disease. Unfortunately, our meta-analysis cannot directly provide evidence regarding the effect of underlying liver disease on outcomes of disease or whether it predisposes to severe COVID illness. Further the group ‘total liver disease’ is also a heterogeneous group comprising chronic hepatitis B, nonalcoholic fatty liver disease and chronic liver disease. Therefore, we also did additional analysis of the frequency of chronic liver disease and underlying hepatitis B separately and the findings regarding frequency of underlying liver disease in severe and non-severe COVID did not seem to change except that the relative risk of underlying chronic liver disease was more in those with severe COVID disease. The effect of COVID on patients with previous transplant has been reported infrequently and data is still unclear if these patients are at an increased risk of severe disease. (Supplementary Table 4). There are some limitations to the current systematic review and meta-analysis. The most important concern is the variability in the definitions of liver dysfunction or acute liver injury (Supplementary Table 5 ), differences in the normal values of liver enzymes in various studies and heterogeneity in definition of severe and non-severe COVID groups. While most studies defined severe disease as per WHO criteria many others have defined severe disease as ICU admissions, non-survivors etc ( Supplementary Table 6) . This adds significant heterogeneity because a study only on ICU patients (which compares survivors and nonsurvivors), is likely to have almost all cases qualifying to the WHO definition of severity. 1 Similarly, although we compared the liver dysfunction in COVID and non-COVID disease, the analysis was limited by the small number of participating studies and heterogeneity in definition of non-COVID cases in various reports. Further although some studies indicate that the elevation of liver enzymes is a delayed phenomenon and may occur in the second week of illness, we were not able to clarify if this is because of worsening inflammation as part of disease course, or other factors like multiple drugs used in these patients. 21 Also, most of the included studies are from China, the country of initial impact of COVID-19 and therefore may not be representative of differences amongst various populations. Further the impact of COVID-19 on outcomes in patients with underlying liver disease is less clear. Some case reports have suggested that SARS-CoV2 could be the cause of Acute deterioration in patients with underlying chronic liver disease resulting in Acute on Chronic Liver Failure (ACLF) 22-23 . However, there are multiple strengths of the meta-analysis, as we have compared multiple parameters of liver function and for most of these a fair number of studies were available. Also, the study clarifies the frequency of liver function abnormalities in severe and non-severe disease. Further, the pooled prevalence of underlying liver disease as a comorbidity has also been clarified. To conclude, liver function abnormalities especially hypoalbuminemia, GGT and aminotransferase elevations are frequent in patients with COVID disease and the patients with severe disease are more likely to have these liver function derangements. Declarations Conflict of interest: None Funding: None Acknowledgements : None Author Contributions PKM: Conception, Data extraction and validation, Analysis, Manuscript review and approval SM: Data extraction, Initial Draft, Manuscript review and approval DKJ, JS, AC: Data extraction and validation, Manuscript review and approval RM, HSM, UD: Important intellectual content, Manuscript review and approval VS: Conception, Data Extraction, validation, Initial draft, Important intellectual content, Manuscript review and approval References World Health Organisation. Interim guidance: Clinical management of severe acute respiratory infection (SARI) when COVID-19 disease is suspected. 2 nd WHO/2019-nCoV/clinical/2020.4 Cheung KS, Hung IF, Chan PP, Lung KC, Tso E, Liu R, et al. Gastrointestinal Manifestations of SARS-CoV-2 Infection and Virus Load in Fecal Samples from the Hong Kong Cohort and Systematic Review and Meta-analysis. Gastroenterology. 2020 Apr 3. pii: S0016-5085(20)30448-0. doi: 10.1053/j.gastro.2020.03.065 Xu L, Liu J, Lu M, Yang D, Zheng X. Liver injury during highly pathogenic human coronavirus infections. Liver Int. 2020 Mar 14. doi: 10.1111/liv.14435. Guan GW, Gao L, Wang JW, Wen XJ, Mao TH, Peng SW, Zhang T, Chen XM, Lu FM. [Exploring the mechanism of liver enzyme abnormalities in patients with novel coronavirus-infected pneumonia]. Zhonghua Gan Zang Bing Za Zhi. 2020 Feb 20;28(2):E002. doi: 10.3760/cma.j.issn.1007-3418.2020.02.002 Bangash MN, Patel J, Parekh D. COVID-19 and the liver: little cause for concern. Lancet Gastroenterol Hepatol. 2020 Mar 20. pii: S2468-1253(20)30084-4. doi: 10.1016/S2468-1253(20)30084-4. Zhang C, Shi L, Wang FS. Liver injury in COVID-19: management and challenges. Lancet Gastroenterol Hepatol. 2020 May;5(5):428-430. doi: 10.1016/S2468-1253(20)30057-1. Moher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern 2009 Aug 18;151(4):264-9 R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ . Guido Schwarzer (2007), meta: An R package for meta-analysis, R News, 7(3), 40-45. Hadley Wickham and Jennifer Bryan (2019). readxl: Read Excel Files. R package version 1.3.1. https://CRAN.R-project.org/package=readxl Wickham. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York, 2016. Luo D, Wan X, Liu J, Tong T. Optimally estimating the sample mean from the sample size, median, mid-range, and/or mid-quartile range. Stat Methods Med Res. 2018;27(6):1785-1805. Wan X, Wang W, Liu J, Tong T. Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range. BMC Med Res Methodol. 2014;14:135. Weber S, Mayerle J, Irlbeck M, Gerbes AL. Severe liver failure during SARS-CoV-2 infection. Gut. 2020 doi: 10.1136/gutjnl-2020-321350. Wander P, Epstein M, Bernstein D. COVID-19 Presenting as Acute Hepatitis. Am J Gastroenterol. 2020 doi: 10.14309/ajg.0000000000000660. Chai X, Hu L, Zhang Y, Han W, Lu Z, Ke A, et al. Specific ACE2 Expression in Cholangiocytes May Cause Liver Damage After 2019-nCoV Infection. bioRxiv doi: 1101/2020.02.03.931766 Herath CB, Warner FJ, Lubel JS, Dean RG, Jia Z, Lew RA,et al . Upregulation of hepatic angiotensin-converting enzyme 2 (ACE2) and angiotensin-(1-7) levels in experimental biliary fibrosis. J Hepatol. 2007 Sep;47(3):387-95. Tian S, Xiong Y, Liu H, Niu L, Guo J, Liao M, Xiao SY. Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies. Mod Pathol. 2020 Apr 14. doi: 10.1038/s41379-020-0536-x. Chu H, Chan JF, Yuen TT, Shuai H, Yuan S, Wang Y, et al. Comparative tropism, replication kinetics, and cell damage profiling of SARS-CoV-2 and SARS-CoV with implications for clinical manifestations, transmissibility, and laboratory studies of COVID-19: an observational study. Lancet Microbe doi : 1016/S2666-5247(20)30004-5 Yamada J, Tomiyama H, Yambe M, Koji Y, Motobe K, Shiina K,et al. Elevated serum levels of alanine aminotransferase and gamm glutamyltransferase are markers of inflammation and oxidative stress independent of the metabolic syndrome. Atherosclerosis. 2006 Nov;189(1):198-205. Yao N, Wang SN, Lian JQ, Sun YT, Zhang GF, Kang WZ et al. [Clinical characteristics and influencing factors of patients with novel coronavirus pneumonia combined with liver injury in Shaanxi region]. Zhonghua Gan Zang Bing Za Zhi. 2020 Mar;28:E003. doi: 10.3760/cma.j.cn501113-20200226-00070. Qiu H, Wander P, Bernstein D, Satapathy SK. Acute on chronic liver failure from novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Liver Int. 2020; doi:10.1111/liv.14506 Große K, Kramer M, Trautwein C, Bruns T. SARS-CoV-2 as an extrahepatic precipitator of acute-on-chronic liver failure Liver Int. 2020; doi:10.1111/liv.14540 Additional File Legends Supplementary Table 1: Detailed Search strategy for the meta-analysis Supplementary Table 2: Details of included studies and the details of each analysis Supplementary Table 3: Reports of liver histology amongst patients with COVID-19 Supplementary Table 4: Reports of COVID-19 with outcomes in patients with liver transplant Supplementary Table 5: Various definitions of acute hepatic injury used in different studies Supplementary Table 6: Various definitions of severe and non-severe COVID-19 disease used in different studies Supplementary Figure 1: Forest plots of alkaline phosphatase (ALP). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of ALP elevation reported in various studies B) Pooled prevalence of ALP elevation among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of ALP elevation in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for ALP elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval. Supplementary Figure 2: Forest plots of globulin. Random effects summary were reported. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of globulin elevation reported in various studies B) SMD for globulin elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. Abbreviation: SMD - standardized mean difference CI - Confidence interval. Supplementary Figure 3: Forest plots of acute hepatic injury (AHI). Random effects summary were reported. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of AHI reported in various studies B) Pooled prevalence of AHI among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of AHI in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference. Abbreviation: RR - Risk ratio. CI - Confidence interval. Supplementary Figure 4: Forest plots of hepatitis B. Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of hepatitis B reported in various studies B) Pooled prevalence of hepatitis B among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of hepatitis B in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference Abbreviation: RR - Risk ratio. CI - Confidence interval. Supplementary Figure 5: Forest plots of fatty liver. Random effects summary were reported. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of fatty liver reported in various studies B) Pooled prevalence of fatty liver among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of fatty liver in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference Abbreviation: RR - Risk ratio. CI - Confidence interval. Supplementary Figure 6: Forest plots of total liver disease (TLD). Random effects summary were reported. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of TLD reported in various studies B) Pooled prevalence of TLD among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of TLD in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference Abbreviation: RR - Risk ratio. CI - Confidence interval. Supplementary Figure 7: Forest plots of chronic liver disease (CLD). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I 2 and P value of heterogeneity. A) Pooled prevalence of CLD reported in various studies B) Pooled prevalence of CLD among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of CLD in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference Abbreviation: RR - Risk ratio. CI - Confidence interval. Supplementary Files SF7CLD.tiff SF6Allliverdisease.tiff SF5FattyLiver.tiff SF4HepB.tiff SF3AHI.tiff SF2Glo.tiff SF1ALP.tiff SupplementaryTablesHep.pdf Cite Share Download PDF Status: Published Journal Publication published 03 Jul, 2020 Read the published version in Hepatology International → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-37723","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":713500,"identity":"f5df3d68-280c-4606-94a3-3cd5815d8e69","order_by":0,"name":"Praveen Kumar-M","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Praveen","middleName":"","lastName":"Kumar-M","suffix":""},{"id":713501,"identity":"7f7ccaea-c4ed-435c-bfc6-4bb2c0aac19e","order_by":1,"name":"Shubhra Mishra","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Shubhra","middleName":"","lastName":"Mishra","suffix":""},{"id":713502,"identity":"c50b6f1c-b325-42b5-9b8c-060fc30228f2","order_by":2,"name":"Daya Krishna Jha","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Daya","middleName":"Krishna","lastName":"Jha","suffix":""},{"id":713503,"identity":"10b93a41-ca6f-49f0-a598-630e5f69209c","order_by":3,"name":"Jayendra Shukla","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Jayendra","middleName":"","lastName":"Shukla","suffix":""},{"id":713504,"identity":"bdf033b6-de11-4dcd-8d83-b9b7317a4ba0","order_by":4,"name":"Arup Choudhury","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Arup","middleName":"","lastName":"Choudhury","suffix":""},{"id":713505,"identity":"cc34231a-1bda-4685-a1d8-bcc73d05e386","order_by":5,"name":"Ritin Mohindra","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Ritin","middleName":"","lastName":"Mohindra","suffix":""},{"id":713506,"identity":"edb06928-0a3a-4669-be4d-da40404b4ae0","order_by":6,"name":"Harshal S Mandavdhare ","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Harshal","middleName":"S","lastName":"Mandavdhare","suffix":""},{"id":713507,"identity":"ea0a3932-455d-4270-854a-c741ecf9fc71","order_by":7,"name":"Usha Dutta ","email":"","orcid":"","institution":"","correspondingAuthor":false,"prefix":"","firstName":"Usha","middleName":"","lastName":"Dutta","suffix":""},{"id":713508,"identity":"4ea72b2f-994c-4cbe-8c32-d690d25c23d7","order_by":8,"name":"Vishal Sharma ","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABBklEQVRIiWNgGAWjYDCCA0CcACT5GHjAfDmw4ANitLBBtRiDBRMIaWFA0pLYwAA2BDfgO978TOLBnzvybPxnD36uzLFLnx92+CHQFjs53QbsWiTPHDOTSGx7ZtgmkZcseXZbcu7G22kGQC3JxmYHsGsxuJHDbJDYcJixTYLHQLJxG3PuxtkJIC0HErfh05Lw57B9G/8Z45+N2+rTDWenfyCkhfFBAtvhxDaGHDOgLYcT5KVz8NsC9Ivhg8S2w8ltEjlmlo3bjhtukM4pOJBggNsvwBB7cPDHn8O2/UCH3WzcVi0vPzt984cPFXZyuLRgcSpYpQGxykFAvoEU1aNgFIyCUTASAADplGju6SMNXQAAAABJRU5ErkJggg==","orcid":"","institution":"PGIMER","correspondingAuthor":true,"prefix":"","firstName":"Vishal","middleName":"","lastName":"Sharma","suffix":""}],"badges":[],"createdAt":"2020-06-24 09:29:32","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-37723/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-37723/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s12072-020-10071-9","type":"published","date":"2020-07-04T02:40:48+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":1416421,"identity":"e23c8730-d0e4-4163-8f09-6e27b05300bf","added_by":"auto","created_at":"2020-06-25 15:41:56","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":66994,"visible":true,"origin":"","legend":"PRISMA Chart showing the flow of study inclusion for the metaanalysis. ","description":"","filename":"fig1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig1.jpg"},{"id":1416422,"identity":"ed2d648b-0c07-4106-9a31-534672dc3394","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":228601,"visible":true,"origin":"","legend":"Forest plots of bilirubin. Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I2 and P value of heterogeneity. A) Pooled prevalence of hyperbilirubinemia reported in various studies B) Pooled prevalence of hyperbilirubinemia among the studies which reported the findings on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of hyperbilirubinemia in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for bilirubin concentration between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. E) SMD of bilirubin concentration between COVID and non-COVID subgroup. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval. ","description":"","filename":"fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig2.jpg"},{"id":1416423,"identity":"ae43dd61-1ed1-43be-9b32-68612c16bbb7","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":336679,"visible":true,"origin":"","legend":"Forest plots of alanine aminotransferase (ALT). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I2 and P value of heterogeneity. A) Pooled prevalence of ALT elevation reported in various studies B) Pooled prevalence of ALT elevation among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of ALT elevation in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for ALT elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. E) RR of ALT elevation in the COVID as compared to non-COVID subgroups F) SMD of ALT elevation between COVID and non-COVID subgroup. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval. ","description":"","filename":"fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig3.jpg"},{"id":1416424,"identity":"1c34c67a-ff8c-4772-9931-6f3038c719be","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":189516,"visible":true,"origin":"","legend":"Forest plots of aspartate aminotransferase (AST). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I2 and P value of heterogeneity. A) Pooled prevalence of AST elevation reported in various studies B) Pooled prevalence of AST elevation among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of AST elevation in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for AST elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. E) RR of AST elevation in the COVID as compared to non-COVID subgroups F) SMD of AST elevation between COVID and non-COVID subgroup. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval. ","description":"","filename":"fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig4.jpg"},{"id":1416425,"identity":"a4b29e6b-965c-44f8-9591-37400e376e66","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":154437,"visible":true,"origin":"","legend":"Forest plots of gamma glutamyl transferase (GGT). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I2 and P value of heterogeneity. A) Pooled prevalence of GGT elevation reported in various studies B) Pooled prevalence of GGT elevation among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of GGT elevation in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for GGT elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. E) SMD of GGT elevation between COVID and non-COVID subgroup. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval.","description":"","filename":"fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig5.jpg"},{"id":1416426,"identity":"04f1a31a-31e9-4c6f-902c-047d6c6aae56","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":218608,"visible":true,"origin":"","legend":"Forest plots of albumin. Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I2 and P value of heterogeneity. A) Pooled prevalence of hypoalbuminemia reported in various studies B) Pooled prevalence of hypoalbuminemia among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of hypoalbuminemia in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for hypoalbuminemia between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. E) SMD of hypoalbuminemia between COVID and non-COVID subgroup. Abbreviation: SMD - standardized mean difference RR - Risk ratio. CI - Confidence interval.","description":"","filename":"fig6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/fig6.jpg"},{"id":1416427,"identity":"8377004c-9c76-40a7-adca-0f0e5ac0c5b5","added_by":"auto","created_at":"2020-06-25 15:41:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2371928,"visible":true,"origin":"","legend":"","description":"","filename":"FileforPreprint.pdf","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/FileforPreprint.pdf"},{"id":13511910,"identity":"42056514-7369-410f-ba7d-00e5eae0e379","added_by":"auto","created_at":"2021-09-16 23:53:50","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1562895,"visible":true,"origin":"","legend":"","description":"","filename":"FileforPreprint.pdf","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1_covered.pdf"},{"id":1416436,"identity":"15262437-8439-4b78-a82a-144cf03272fa","added_by":"auto","created_at":"2020-06-25 15:42:00","extension":"tiff","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5106374,"visible":true,"origin":"","legend":"","description":"","filename":"SF7CLD.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF7CLD.tiff"},{"id":1416435,"identity":"7bb6b0b0-c59d-4af4-8956-e08be3725efd","added_by":"auto","created_at":"2020-06-25 15:41:59","extension":"tiff","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":5778382,"visible":true,"origin":"","legend":"","description":"","filename":"SF6Allliverdisease.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF6Allliverdisease.tiff"},{"id":1416434,"identity":"bb8653a5-f27d-42d2-a6b9-68ae4f1043bb","added_by":"auto","created_at":"2020-06-25 15:41:59","extension":"tiff","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1995050,"visible":true,"origin":"","legend":"","description":"","filename":"SF5FattyLiver.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF5FattyLiver.tiff"},{"id":1416433,"identity":"32c7cc0d-1a56-4a26-9cdd-7d267668e0bb","added_by":"auto","created_at":"2020-06-25 15:41:59","extension":"tiff","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2390674,"visible":true,"origin":"","legend":"","description":"","filename":"SF4HepB.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF4HepB.tiff"},{"id":1416432,"identity":"ef8f7d3c-23e3-45a0-89de-a7f8a4a437a7","added_by":"auto","created_at":"2020-06-25 15:41:58","extension":"tiff","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":4379014,"visible":true,"origin":"","legend":"","description":"","filename":"SF3AHI.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF3AHI.tiff"},{"id":1416431,"identity":"004f7e31-f17e-4fa8-b603-036b4f9696bd","added_by":"auto","created_at":"2020-06-25 15:41:58","extension":"tiff","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":1031846,"visible":true,"origin":"","legend":"","description":"","filename":"SF2Glo.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF2Glo.tiff"},{"id":1416430,"identity":"39a11dc3-a750-4e4f-b4be-d27cc01d8f07","added_by":"auto","created_at":"2020-06-25 15:41:58","extension":"tiff","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":3397278,"visible":true,"origin":"","legend":"","description":"","filename":"SF1ALP.tiff","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SF1ALP.tiff"},{"id":1416429,"identity":"fea7d152-3fc5-470e-8248-2bada59c855e","added_by":"auto","created_at":"2020-06-25 15:41:58","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":467861,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesHep.pdf","url":"https://assets-eu.researchsquare.com/files/rs-37723/v1/SupplementaryTablesHep.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eCoronavirus Disease (COVID-19) and the Liver: A comprehensive systematic review and meta-analysis\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCoronavirus disease (COVID-19) was first brought to light with the appearance of cases of viral pneumonia in December 2019 in Wuhan city of the Chinese Hubei province.\u003csup\u003e1\u003c/sup\u003e Since then the disease has spread globally and is recognized as a global pandemic by the World Health Organization (WHO).\u0026nbsp; The disease, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been responsible for large numbers of hospital admissions and mortality resulting in a severe stress on health care resources. With time the understanding of the disease has also improved and it has become apparent that it involves not just the pulmonary system but also the gastrointestinal system, heart and the liver.\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe hepatic involvement has been well recognized in the two recent pathogenic coronaviruses i.e SARS-COV and Middle east respiratory syndrome coronavirus (MERS-COV). These two viruses had striking genetic similarity (especially SARS-COV) with the novel coronavirus i.e SARS-CoV-2 and therefore hepatic involvement in this is not entirely unexpected.\u003csup\u003e3\u003c/sup\u003e Indeed multiple reports have suggested that elevation of liver transaminases do occur with the infection of SARS-CoV-2. The purported mechanisms include the possibility of direct effect of the the virus on hepatocytes or biliary epithelium, liver injury related to accentuated immune response (cytokine storm) and immune mediated damage, drug toxicity (because of drugs like acetaminophen, antivirals and hydroxychloroquine) and ischemic hepatitis which could occur in patients having multiorgan dysfunction including hemodynamic instability.\u003csup\u003e4\u003c/sup\u003e The biliary epithelium expresses the angiotensin converting enzyme (ACE-2) receptor which is the known binding site of SARS-CoV-2 while the expression in hepatocytes is possibly much lower. However, the receptor expression has been shown to be upregulated in animals models of liver injury.\u003csup\u003e4\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe literature regarding hepatic involvement in COVID-19 is heterogenous with variability in the definitions of liver dysfunction and differences in the clinical presentation and disease severity of patients included in the published reports.\u003csup\u003e5,6\u003c/sup\u003e\u0026nbsp; Therefore, we planned to systematically study the occurrence of liver injury in COVID-19 and also determine the frequency of liver involvement in COVID-19. We also planned to identify any differences in frequency of liver dysfunction with varying disease severity, identify differences in frequency of liver dysfunction in COVID-19 vis-a-vis non-COVID disease and also the frequency of underlying liver disease as a comorbidity in COVID-19 disease.\u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003eWe conducted this systematic review and meta-analysis as per the guidance provided by the PRISMA statement. \u003csup\u003e7\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSearch and Study Selection \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe searched Pubmed and Embase on 5th April 2019 for publications using the keywords \u0026lsquo;COVID\u0026rdquo;, \u0026ldquo;Novel coronavirus\u0026rdquo; or \u0026ldquo;SARS-CoV-2\u0026rdquo; for all publications after 1st December 2019. No other restrictions for language or ethnicity or type of papers were used. The detailed search strategy is shown in \u003cstrong\u003eSupplementary Table 1.\u003c/strong\u003e The results obtained from the two databases were then combined and duplicates removed. Two reviewers (PKM, SM) separately did a title and abstract screening to select any studies reporting on data about underlying hepatic comorbidities or liver dysfunction. The studies selected for full texts screening were seen by two authors (SM and VS) for data extraction. Three other authors checked the data for accuracy and completeness (DKJ, JS, AC). The bibliography of selected papers and relevant reviews was also sought to identify any additional eligible papers and an additional search was done using the original search terms AND \u0026ldquo;Liver\u0026rdquo; (both databases) to identify any additional papers as on 23rd April 2020. The detailed flow of the study selection is shown using the PRISMA flowchart \u003cstrong\u003e(Figure 1). \u003c/strong\u003e\u0026nbsp;\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSelection of Studies\u0026nbsp; \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTwo investigators (VS and SM) separately determined if the studies were eligible for inclusion in the meta-analysis and the disagreements were discussed with the third author (PKM) for final decision.\u003c/p\u003e\n\u003cp\u003eWe included studies 1) reporting on frequency of various liver function abnormalities including serum bilirubin, alanine aminotransferases (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP) or gamma glutamyl transferase (GGT) in human patients infected with SARS-CoV-2 2) reporting their median/mean levels for severe and non-severe disease or 3) reporting the frequency of underlying liver disease as a comorbidity in patients with COVID-19.\u003c/p\u003e\n\u003cp\u003eThese studies were included irrespective of age, gender, ethnicity of the reported population, the study designs (cohort, case series, randomized trials) and the language of publication. We excluded the studies\u0026nbsp; 1) if\u0026nbsp; number of patients were \u0026lt; 5\u0026nbsp; 2) if studies did not have confirmed cases of COVID-19 3) if none of the relevant liver functions or data on liver disease as a comorbidity were reported and 4) study designs like comments, editorials, reviews and systematic reviews which did not provide primary data. These studies were however, looked at to identify additional papers from bibliography.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy groups and analysis plan \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe planned to find the pooled prevalence of liver function abnormalities in cases of COVID-19 and compare the frequencies of liver derangements between severe and non-severe COVID-19. We also planned to compare the frequencies of liver derangements between COVID cases and non-COVID cases, if such data were available. We also planned to determine the pooled prevalence of underlying liver disease in patients with COVID-19 and compare if this frequency was different between severe and non-severe disease and between COVID and non-COVID disease. Additionally, we planned to compare the standard mean difference between severe and non-severe COVID and COVID and non-COVID cases.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Extraction \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe extracted data as per: authors, location of study, type of study, type of included patients, number of included patients, frequency of various hepatic derangements (elevation of serum bilirubin, ALT, AST, GGT, ALP, serum albumin) in patients with COVID-19 \u0026nbsp;and separately for those with severe and non-severe disease, mean/median values with standard deviation /interquartile range/ range of these parameters from studies which compared severe and non-severe disease and also COVID \u0026amp; non-COVID cases. The details regarding the definition of disease severity in each study and details of definition of acute hepatic injury (or hepatic dysfunction) were also extracted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe statistical analysis was performed using R statistical software (version 3.6.1).\u003csup\u003e8\u003c/sup\u003e In addition to the base package, meta, readxl and ggplot2 packages were used.\u003csup\u003e9,10, 11\u003c/sup\u003e The number of events were summarized as events per 100 observations. The inverse variance method with logit transformation along with Clopper Pearson confidence interval for individual studies was used for the meta-analytic pooled prevalence in the overall and subgroup population. For difference in prevalence between subgroups, the inverse variance method was used for summarizing. A continuity correction of 0.5 was applied for studies with zero cell frequency. For continuous variable standardized mean differences (SMD) were computed between the evaluated sub-groups and inverse variance method was used for summarizing. Hedges\u0026rsquo;s g correction was used for bias correction of standardized mean differences. For studies reporting mean and standard deviation, we directly took the reported values for analysis. For studies reporting median and interquartile range or median and range, the mean and standard deviation were computed from the reported values based on Luo 2018 and Wan 2014 methodology. \u003csup\u003e12,13\u003c/sup\u003e For studies reporting only mean along with p value, the t statistics were computed, which was then used for calculation of standard deviation. For studies reporting individual data, we computed mean and SD from the data. Heterogeneity of prevalence, RR and SMD were tested with P value of heterogeneity (p\u0026lt;0.10) and I\u003csup\u003e2 \u003c/sup\u003ewas computed. I\u003csup\u003e2 \u003c/sup\u003evalue was taken for reporting for heterogeneity as in addition to quantifying heterogeneity it also assesses the impact of heterogeneity on the meta-analysis. Random effects models were used for summarizing results irrespective of heterogeneity. For prevalence, 95% C.I of pooled prevalence was reported. For studies comparing prevalence and SMD between two groups, p value of \u0026lt;0.05 was considered statistically significant and 95% confidence intervals (CIs) were reported.\u0026nbsp; The forest plots were constructed for visualization of results.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSearch Results and Included Studies \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe search yielded a total of 6053 citations and additional 28 papers were identified from other sources like bibliography search. After removal of 2206 duplicates, 3875 papers were screened for title and abstract. After removal of 3559 papers for various reasons (Figure 1), a total of 316 papers were eligible for full text screening. Eventually a total of 128 papers were included in at least one of the different analyses which were conducted as part of the meta-analysis (Supplementary Table 2). \u003csup\u003e\u0026nbsp;\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOverall frequency of various abnormalities in liver function in COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of hyperbilirubinemia reported in various studies was 10.98% (95% CI: 6.87 - 17.08; I\u003csup\u003e2\u003c/sup\u003e: 94%) (Figure 2A) . The pooled prevalence of alanine aminotransferase (ALT) and aspartate aminotransferase (AST) elevation reported in various studies were 23.28% (19.92 - 27.01; 90%)\u0026nbsp; and 23.41% (18.84 - 28.70; 95%) respectively (Figures 3A and 4A). The pooled prevalence of ALP and GGT elevation among overall reported studies were 7.48% (3.91 - 13.83; 75%) and 27.94% (18.22 - 40.27; 93%) respectively (Supplementary Figure 1 and Figure 5A) . The pooled prevalence of hypoalbuminemia among overall reported studies was 61.27% (48.24 - 72.87; 91%) (Figure 6A). The overall pooled frequency of increased globulin levels reported was 20.17% (4.73 - 56.25; 95%) respectively (Supplementary Figure 2). The pooled frequency of acute hepatic injury as reported in various studies is shown in Supplementary Figure 3. The pooled prevalence of hepatitis B, fatty liver, total liver disease and chronic liver disease as a comorbidity are shown in Supplementary Figure 4-7. The pooled prevalence of chronic liver disease as a comorbidity in various studies was 2.49% (1.79-3.46, 84%) (Supplementary Figure 7). The pooled frequency of hepatitis B, nonalcoholic fatty liver disease and total frequency of any liver disease is shown in Supplementary Figures 4, 5 and 6.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison between severe and nonsevere COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of bilirubin abnormality among the studies which reported the finding on the basis of underlying severity of COVID-19\u0026nbsp; was 13.71% (95% CI: 7.53 - 23.69; I\u003csup\u003e2\u003c/sup\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003e95%). The pooled frequency of hyperbilirubinemia in severe COVID disease was 18.80% (9.55 - 33.67; 91%) while in non-severe disease it was\u0026nbsp; 9.24% (3.15 - 24.17; 97%) (Figure 2B).\u0026nbsp; The risk ratio (RR) of deranged bilirubin concentration in severe as compared to non-severe subgroups was 1.82 (95% CI: 1.22-2.73; I\u003csup\u003e2\u003c/sup\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003e66%) (Figure 2C).The SMD for bilirubin concentration between the severe and non-severe group was 0.43 (95% CI: 0.26 - 0.61; I\u003csup\u003e2\u003c/sup\u003e: 66% ) (Figure 2D).\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of ALT and AST abnormality among the studies reporting severity were 31.31% (25.82 - 37.37; 87%) (Figure 3B) and 33.95% (26.90 - 41.79; 91%) (Figure 4B). The pooled frequency of ALT elevation was 39.58% (30.92 - 48.94; 80%) for severe \u0026amp; 24.15% (17.98 - 31.63; 90%) for nonsevere disease (Figure 3C). The pooled frequency of AST elevation was 49.68% (41.90 - 57.49; 73%) \u0026amp; 19.40% (13.27 - 27.45; 91%) respectively for severe and non-severe disease (Figure 4C). The RR of SGPT and SGOT abnormality\u0026nbsp; in the severe as compared to non-severe subgroups were 1.76(1.44 - 2.15; 65%) and 2.30 (1.82 - 2.90, 67%) respectively (Figures 3D and 4D). The SMD for SGPT and SGOT concentration between the severe and non-severe group were 0.42 (0.27 - 0.56; 70%) and 0.69 (0.52 - 0.86; 76%) respectively (Figures 3E and 4E).\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of ALP and GGT abnormality among the studies reporting severity were 6.99% (4.08 - 11.72; 59%) (Supplementary Figure 1B) and 30.62% (18.13 - 46.79; 94%) (Figure 5B) with subdivision for ALP being 11.33% (5.89 - 20.69; 42%) for severe \u0026amp; 4% (1.68 - 9.26; 64%) for nonsevere and for GGT being 46.90% (25.13 - 69.92; 89%) \u0026amp; 18.66% (9.20 - 34.18; 93%). The RR of ALP and GGT abnormality in severe as compared to\u0026nbsp; non-severe subgroups were 1.99 (0.85 - 4.68; 22%) (Supplementary Figure 1C) and 2.31 (1.6 - 3.33; 55%) (Figure 5C) respectively. The SMD for ALP and GGT concentration between the severe and non-severe group were 0.24 (-0.12 - 0.60; 83%) (Supplementary Figure 1D) and 0.76 (0.40 - 1.12; 82%) (Figure 5D) respectively.\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of albumin abnormality among the studies reporting severity was 61.57% (42.73 - 77.48; 90%) with subdivision of 75.91% (67.02 - 83.02; 35%) for severe and 31.04% (13.72 - 56.02; 84%) for nonsevere (Figure 6B). The RR of albumin abnormality in severe as compared to non-severe subgroup was 2.65 (1.38 - 5.07; 79%) (Figure 6C). The SMD for albumin concentration between the severe and non-severe group was -1.05 (-1.27 - -0.83; 77%) (Figure 6D). The SMD for globulin concentration between severe and nonsevere group was 2.46 (0.24 - 4.69, 99%) (Supplementary Figure 2B)\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of chronic liver disease (CLD) among studies reporting severity was 2.64% (1.73- 4; 72%) with 3.03 (1.97 - 4.64; 21%) among severe and 2.20% (1.16 - 4.15; 83%) among nonsevere (Supplementary Figure 7B). The RR of CLD in severe as compared to non-severe subgroup was 1.69 (1.05-2.73; 0%) (Supplementary Figure 7C)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePresence of Acute Hepatic injury (Supplementary Figure 3)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe pooled prevalence of acute hepatic injury among overall reported studies was 23.70% (95% CI: 16.31 - 33.11; I\u003csup\u003e2\u003c/sup\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003e97%) (Supplementary Figure 3A). Among the studies reporting severity the total frequency of acute hepatic injury was 31.66% (22.66 - 42.27; 91%), whereas in severe disease it was 44.63% (30.13 - 60.11; 88%) and in nonsevere disease it was 20.02% (12.74 - 30.02; 88%) (Supplementary Figure 3B). The RR of acute hepatic injury in severe as compared to nonsevere were: LD 2.18 (1.49 - 3.18, 67%)\u0026nbsp; (Supplementary Figure 3C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison between COVID and non-COVID disease \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe RR of\u0026nbsp; ALT and AST\u0026nbsp; abnormality in the\u0026nbsp; COVID as compared to non-COVID subgroups were 1.09 (95% CI: 0.55 - 2.15; I\u003csup\u003e2\u003c/sup\u003e:\u003csup\u003e\u0026nbsp; \u003c/sup\u003e21%) and 1.02 (0.45 - 2.30; 48%), both statistically non-significant (Figure 2E and 3E). The SMD for SGPT and SGOT concentration between the COVID and non-COVID group were 0.18 (0.05-0.32; 0%) and 0.02 (-0.47 - 0.52; 91%) (Figure 2F and 3F). The SMD\u0026nbsp; of bilirubin, GGT and albumin concentration between COVID and non-COVID subgroup were\u0026nbsp; -0.27 (-0.49 - -0.05, 28%), 0.12 (-0.24 - 0.48; 58%) and 0.82 (0.30 - 1.33; 82%) respectively (Figure 2E, Figure 5E, Figure 6E).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHepatic histological findings in COVID-19\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOnly limited cases have reported findings on liver histology using either post-mortem histology or liver biopsy in patients with COVID-19 and are tabulated in Supplementary Table 3. The findings reported are non-specific and include sinusoidal dilatation, mild activity in portal area and lobules and occasional necrosis. It is unclear if these are a manifestation of virus mediated liver injury or due to other factors like drugs or immune injury.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCOVID-19 in Liver transplant recipients \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSome case reports and studies have reported the outcomes of COVID-19 in patients with liver transplant and are shown in Supplementary Table 4.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this systematic review, we found that the derangements of liver functions were frequently noted in patients with COVID-19. The most frequent abnormality noted was hypoalbuminemia followed by elevations of gamma-glutamyl transferase, aminotransferases, bilirubin and alkaline phosphatase. Further, when comparison of severe with nonsevere COVID-19 cases was done, liver function abnormalities like hypoalbuminemia, GGT and aminotransferase and bilirubin elevations were more frequent in those with severe disease. However, serum alkaline phosphatase elevations were not significantly higher in the severe group of patients. The pooled frequency of elevation of ALT and AST were similar in the overall COVID cases but interestingly the prevalence of AST elevations was more than ALT in the severe COVID disease.\u003c/p\u003e\n\u003cp\u003eThe most frequent abnormality noted in our meta-analysis was hypoalbuminemia. This is possibly related to the fact that albumin is a negative acute phase reactant rather than a manifestation of a hepatic synthetic dysfunction. Our meta-analysis confirms that the liver enzyme elevations in COVID-19, even in the severe COVID category, are mild to moderate in most of the cases. Although there are a few reports of aminotransferase elevation to a high degree (\u0026gt;10 times of upper limit), this is an uncommon phenomenon.\u003csup\u003e14-15\u003c/sup\u003e Further, liver failure is exceedingly rare with only a single case report is available in a patient who had severe COVID associated with use of multiple drugs and progression of liver function derangement after admission.\u003csup\u003e14\u003c/sup\u003e As of now, it is not possible to conclusively ascribe these elevations to be related to direct viral injury.\u0026nbsp; Most of the studies included in our analysis reported use of multiple drugs like antibiotics, antivirals (lopinavir/ritonavir combination, arbidol, oseltamivir, favipiravir, remdesvir, hydroxychloroquine) and steroids. Many of these drugs could have contributed to occurrence of liver dysfunction after hospitalization. Further, ischemia and immune mediated injury due to cytokine storm could be responsible for liver dysfunction in patients with severe COVID disease.\u003c/p\u003e\n\u003cp\u003eSARS-CoV-2 uses the ACE-2 receptor for gaining entry into the cells including the type 2 alveolar epithelial cells in the lungs. Chai et al analyzed the expression of ACE-2 receptors in liver tissue and found that their expression on cholangiocytes (59.7 %) was much stronger than on hepatocytes (2.6%).\u003csup\u003e16\u003c/sup\u003e It has also been observed that ACE-2 expression increases in hepatocytes, in cases of liver injury.\u003csup\u003e4, 17\u003c/sup\u003e At least, one report suggests that viral RNA could be\u0026nbsp; detected in liver tissue raising the possibility\u0026nbsp; of viral mediated liver injury.\u003csup\u003e18\u003c/sup\u003e On the other hand, Chu et al demonstrated significant replication of SARS-CoV-2 on Huh7 (hepatic) cell lines. They also noted that cytopathic effects were seen in a minority of cases, cautioning against an over reliance on the same.\u003csup\u003e19\u003c/sup\u003e Yet the limited histological reports available fail to demonstrate clear cytopathic changes of SARS-Cov-2 (\u003cstrong\u003eSee Supplementary Table 3)\u003c/strong\u003e. Further, the comparison of liver function showed that most abnormalities were equally frequent in non-COVID disease suggesting the lack of any specificity for the diagnosis of COVID.\u003c/p\u003e\n\u003cp\u003eAnother interesting finding was that the elevations in GGT were similar in frequency to elevations in aminotransferases and were higher than the elevations in alkaline phosphatase. Further, the frequency of patients with elevation of GGT was higher in severe COVID disease when compared to non-severe disease but this was not noted with alkaline phosphatase. The exact reason for this is unclear but GGT is recognized as a surrogate marker for increased oxidative stress and chronic inflammation.\u003csup\u003e20\u003c/sup\u003e It is uncertain if these elevations are related to acute inflammatory stress or are a marker of biliary injury and this finding needs further evaluation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe also looked at the prevalence of underlying liver disease as a comorbidity in the patients with COVID-19 disease and compared the frequency of liver disease as a comorbidity in severe and non-severe COVID cases. We found that the underlying liver disease was found in a significant number of patients with COVID-19. However, the frequency of underlying liver disease was statistically not different between severe and nonsevere disease. Unfortunately, our meta-analysis cannot directly provide evidence regarding the effect of underlying liver disease on outcomes of disease or whether it predisposes to severe COVID illness. Further the group \u0026lsquo;total liver disease\u0026rsquo; is also a heterogeneous group comprising chronic hepatitis B, nonalcoholic fatty liver disease and chronic liver disease. Therefore, we also did additional analysis of the frequency of chronic liver disease and underlying hepatitis B separately and the findings regarding frequency of underlying liver disease in severe and non-severe COVID did not seem to change except that the relative risk of underlying chronic liver disease was more in those with severe COVID disease. The effect of COVID on patients with previous transplant has been reported infrequently and data is still unclear if these patients are at an increased risk of severe disease. \u003cstrong\u003e(Supplementary Table 4).\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere are some limitations to the current systematic review and meta-analysis. The most important concern is the variability in the definitions of liver dysfunction or acute liver injury \u003cstrong\u003e(Supplementary Table 5\u003c/strong\u003e), differences in the normal values of liver enzymes in various studies and heterogeneity in definition of severe and non-severe COVID groups. While most studies defined severe disease as per WHO criteria many others have defined severe disease as ICU admissions, non-survivors etc (\u003cstrong\u003eSupplementary Table 6)\u003c/strong\u003e. This adds significant heterogeneity because a study only on ICU patients (which compares survivors and nonsurvivors), is likely to have almost all cases qualifying to the WHO definition of severity.\u003csup\u003e1\u003c/sup\u003e\u0026nbsp; Similarly, although we compared the liver dysfunction in COVID and non-COVID disease, the analysis was limited by the small number of participating studies and heterogeneity in definition of non-COVID cases in various reports.\u0026nbsp; Further although some studies indicate that the elevation of liver enzymes is a delayed phenomenon and may occur in the second week of illness, we were not able to clarify if this is because of worsening inflammation as part of disease course, or other factors like multiple drugs used in these patients.\u003csup\u003e21\u003c/sup\u003eAlso, most of the included studies are from China, the country of initial impact of COVID-19 and therefore may not be representative of differences amongst various populations. Further the impact of COVID-19 on outcomes in patients with underlying liver disease is less clear. Some case reports have suggested that SARS-CoV2 could be the cause of Acute deterioration in patients with underlying chronic liver disease resulting in Acute on Chronic Liver Failure (ACLF)\u003csup\u003e22-23\u003c/sup\u003e.\u0026nbsp; However, there are multiple strengths of the meta-analysis, as we have compared multiple parameters of liver function and for most of these a fair number of studies were available. Also, the study clarifies the frequency of liver function abnormalities in severe and non-severe disease. Further, the pooled prevalence of underlying liver disease as a comorbidity has also been clarified.\u003c/p\u003e\n\u003cp\u003eTo conclude, liver function abnormalities especially hypoalbuminemia, GGT and aminotransferase elevations are frequent in patients with COVID disease and the patients with severe disease are more likely to have these liver function derangements.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eNone\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: None\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePKM: Conception, Data extraction and validation, Analysis, Manuscript review and approval\u003c/p\u003e\n\u003cp\u003eSM: Data extraction, Initial Draft, Manuscript review and approval\u003c/p\u003e\n\u003cp\u003eDKJ, JS, AC: Data extraction and validation, Manuscript review and approval\u003c/p\u003e\n\u003cp\u003eRM, HSM, UD: Important intellectual content, Manuscript review and approval\u003c/p\u003e\n\u003cp\u003eVS: Conception, Data Extraction, validation, Initial draft, Important intellectual content, Manuscript review and approval\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organisation. Interim guidance: Clinical management of severe acute respiratory infection (SARI) when COVID-19 disease is suspected. 2\u003csup\u003end\u003c/sup\u003e WHO/2019-nCoV/clinical/2020.4\u003c/li\u003e\n\u003cli\u003eCheung KS, Hung IF, Chan PP, Lung KC, Tso E, Liu R, et al. Gastrointestinal Manifestations of SARS-CoV-2 Infection and Virus Load in Fecal Samples from the Hong Kong Cohort and Systematic Review and Meta-analysis. Gastroenterology. 2020 Apr 3. pii: S0016-5085(20)30448-0. doi: 10.1053/j.gastro.2020.03.065\u003c/li\u003e\n\u003cli\u003eXu L, Liu J, Lu M, Yang D, Zheng X. Liver injury during highly pathogenic human coronavirus infections. Liver Int. 2020 Mar 14. doi: 10.1111/liv.14435.\u003c/li\u003e\n\u003cli\u003eGuan GW, Gao L, Wang JW, Wen XJ, Mao TH, Peng SW, Zhang T, Chen XM, Lu FM. [Exploring the mechanism of liver enzyme abnormalities in patients with novel coronavirus-infected pneumonia]. Zhonghua Gan Zang Bing Za Zhi. 2020 Feb 20;28(2):E002. doi: 10.3760/cma.j.issn.1007-3418.2020.02.002\u003c/li\u003e\n\u003cli\u003eBangash MN, Patel J, Parekh D. COVID-19 and the liver: little cause for concern. Lancet Gastroenterol Hepatol. 2020 Mar 20. pii: S2468-1253(20)30084-4. doi: 10.1016/S2468-1253(20)30084-4.\u003c/li\u003e\n\u003cli\u003eZhang C, Shi L, Wang FS. Liver injury in COVID-19: management and challenges. Lancet Gastroenterol Hepatol. 2020 May;5(5):428-430. doi: 10.1016/S2468-1253(20)30057-1.\u003c/li\u003e\n\u003cli\u003eMoher D, Liberati A, Tetzlaff J, Altman DG; PRISMA Group. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. Ann Intern\u0026nbsp; 2009 Aug 18;151(4):264-9\u003c/li\u003e\n\u003cli\u003eR Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. 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Pathological study of the 2019 novel coronavirus disease (COVID-19) through postmortem core biopsies. Mod Pathol. 2020 Apr 14. doi: 10.1038/s41379-020-0536-x.\u003c/li\u003e\n\u003cli\u003eChu H, Chan JF, Yuen TT, Shuai H, Yuan S, Wang Y, et al. Comparative tropism, replication kinetics, and cell damage profiling of SARS-CoV-2 and SARS-CoV with implications for clinical manifestations, transmissibility, and laboratory studies of COVID-19: an observational study. Lancet Microbe doi : \u003ca href=\"https://doi.org/10.1016/S2666-5247(20)30004-5\"\u003e1016/S2666-5247(20)30004-5\u003c/a\u003e\u003c/li\u003e\n\u003cli\u003eYamada J, Tomiyama H, Yambe M, Koji Y, Motobe K, Shiina K,et al. Elevated serum levels of alanine aminotransferase and gamm glutamyltransferase are markers of inflammation and oxidative stress independent of the metabolic syndrome. Atherosclerosis. 2006 Nov;189(1):198-205.\u003c/li\u003e\n\u003cli\u003eYao N, Wang SN, Lian JQ, Sun YT, Zhang GF, Kang WZ et al. [Clinical characteristics and influencing factors of patients with novel coronavirus pneumonia combined with liver injury in Shaanxi region]. Zhonghua Gan Zang Bing Za Zhi. 2020 Mar;28:E003. doi: 10.3760/cma.j.cn501113-20200226-00070.\u0026nbsp;\u003c/li\u003e\n\u003cli\u003eQiu H, Wander P, Bernstein D, Satapathy SK. Acute on chronic liver failure from novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Liver Int. 2020; doi:10.1111/liv.14506\u0026nbsp;\u0026nbsp;\u003c/li\u003e\n\u003cli\u003eGro\u0026szlig;e K, Kramer M, Trautwein C, Bruns T. SARS-CoV-2 as an extrahepatic precipitator of acute-on-chronic liver failure\u0026nbsp;Liver Int. 2020; doi:10.1111/liv.14540\u0026nbsp;\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Additional File Legends","content":"\u003cp\u003eSupplementary Table 1: Detailed Search strategy for the meta-analysis\u003c/p\u003e\n\u003cp\u003eSupplementary Table 2: Details of included studies and the details of each analysis\u003c/p\u003e\n\u003cp\u003eSupplementary Table 3: Reports of liver histology amongst patients with COVID-19\u003c/p\u003e\n\u003cp\u003eSupplementary Table 4: Reports of COVID-19 with outcomes in patients with liver transplant\u003c/p\u003e\n\u003cp\u003eSupplementary Table 5: Various definitions of acute hepatic injury used in different studies\u003c/p\u003e\n\u003cp\u003eSupplementary Table 6: Various definitions of severe and non-severe COVID-19 disease used in different studies\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 1: Forest plots of alkaline phosphatase (ALP). Random effects summary were reported\u0026nbsp; in the manuscript. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of ALP elevation reported in various studies\u0026nbsp; B) Pooled prevalence of ALP elevation among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of ALP elevation in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference D) SMD for ALP elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. \u003cem\u003eAbbreviation: \u003c/em\u003eSMD - standardized mean difference RR - Risk ratio. CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 2: Forest plots of globulin. Random effects summary were reported. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of globulin elevation reported in various studies B) SMD for globulin elevation between the severe and non-severe group. For SMD, the middle vertical line at 0 stands for line of no difference. \u003cem\u003eAbbreviation:\u003c/em\u003e SMD - standardized mean difference CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 3: Forest plots of acute hepatic injury (AHI). Random effects summary were reported. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of AHI reported in various studies\u0026nbsp; B) Pooled prevalence of AHI\u0026nbsp; among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of AHI in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference. \u003cem\u003eAbbreviation: \u003c/em\u003eRR - Risk ratio. CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 4: Forest plots of hepatitis B. Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of hepatitis B reported in various studies \u0026nbsp;B) Pooled prevalence of hepatitis B\u0026nbsp; among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of hepatitis B in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference \u003cem\u003eAbbreviation:\u003c/em\u003e RR - Risk ratio. CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 5: \u0026nbsp;Forest plots of fatty liver. Random effects summary were reported. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of fatty liver reported in various studies\u0026nbsp; B) Pooled prevalence of fatty liver\u0026nbsp; among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of fatty liver in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference \u003cem\u003eAbbreviation:\u003c/em\u003e RR - Risk ratio. CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 6:\u0026nbsp; Forest plots of total liver disease (TLD). Random effects summary were reported. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of TLD reported in various studies\u0026nbsp; B) Pooled prevalence of TLD\u0026nbsp; among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of TLD in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference \u003cem\u003eAbbreviation: \u003c/em\u003eRR - Risk ratio. CI - Confidence interval.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSupplementary Figure 7: Forest plots of chronic liver disease (CLD). Random effects summary were reported in the manuscript. The heterogeneity was measured across studies by I\u003csup\u003e2\u003c/sup\u003e and P value of heterogeneity. A) Pooled prevalence of CLD reported in various studies\u0026nbsp; B) Pooled prevalence of CLD among the studies which reported the finding on the basis of underlying severity of COVID-19 C) Risk ratio (RR) of CLD in severe as compared to non-severe subgroups. For RR, the middle vertical line at 1 stands for line of no-difference \u003cem\u003eAbbreviation:\u003c/em\u003e RR - Risk ratio. CI - Confidence interval.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"SARS-CoV-2, COVID, Cirrhosis, aminotransferases, alkaline phosphatase","lastPublishedDoi":"10.21203/rs.3.rs-37723/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-37723/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eLiver function derangements have been reported in coronavirus disease (COVID-19) but reported rates are variable. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e We searched Pubmed and Embase with terms COVID and SARS-COV-2 from December 1, 2019 till April 5, 2020. We estimated overall prevalence, stratified prevalence based on severity, estimated risk ratio (RR) and estimated standardized mean difference (SMD) of liver function parameters in severe as compared to nonsevere COVID. Random effect method utilizing inverse variance approach was used for pooling the data.\u003c/p\u003e\u003cp\u003e\u0026nbsp;\u003cstrong\u003eResults: \u003c/strong\u003eIn all, 128 studies were included. The most frequent abnormalities were hypoalbuminemia [61.27% (48.24 - 72.87)], elevations of gamma-glutamyl transferase (GGT) [27.94%(18.22 -40.27)], alanine aminotransferase (ALT) [23.28%(19.92 - 27.01)] and aspartate aminotransferase (AST) [23.41%(18.84 - 28.70)]. Further the relative risk of these abnormalities was higher in the patients with severe COVID-19 when compared to non-severe disease [Hypoalbuminemia - 2.65(1.38 - 5.07); GGT - 2.31(1.6 - 3.33); ALT - 1.76(1.44 - 2.15); AST 2.30(1.82 - 2.90)]. The SMD of hypoalbuminemia, GGT, ALT and AST elevation in severe as compared to nonsevere were -1.05(-1.27 - -0.83), 0.76(0.40 - 1.12), 0.42(0.27 - 0.56) and 0.69 (0.52 - 0.86) respectively.\u0026nbsp;The pooled prevalence and RR of chronic liver disease as a comorbidity was 2.64% (1.73- 4) and 1.69(1.05-2.73) respectively. \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eThe most frequent abnormality in liver functions was hypoalbuminemia followed by derangements in gamma-glutamyl transferase and aminotransferases and these abnormalities were more frequent in severe disease. \u0026nbsp;The systematic review was, however, limited by heterogeneity in definitions of severity and liver function derangements.\u0026nbsp;\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Coronavirus Disease (COVID-19) and the Liver: A comprehensive systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2020-06-25 15:41:56","doi":"10.21203/rs.3.rs-37723/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f2fa453c-c7a8-4809-bab0-c2dd8c108edb","owner":[],"postedDate":"June 25th, 2020","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":129807,"name":"Critical Care \u0026 Emergency Medicine"},{"id":129808,"name":"Gastroenterology \u0026 Hepatology"},{"id":129809,"name":"Infectious Diseases"}],"tags":[],"updatedAt":"2021-07-22T02:40:48+00:00","versionOfRecord":{"articleIdentity":"rs-37723","link":"https://doi.org/10.1007/s12072-020-10071-9","journal":{"identity":"hepatology-international","isVorOnly":false,"title":"Hepatology International"},"publishedOn":"2020-07-04 02:40:48","publishedOnDateReadable":"July 4th, 2020"},"versionCreatedAt":"2020-06-25 15:41:56","video":"","vorDoi":"10.1007/s12072-020-10071-9","vorDoiUrl":"https://doi.org/10.1007/s12072-020-10071-9","workflowStages":[]},"version":"v1","identity":"rs-37723","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-37723","identity":"rs-37723","version":["v1"]},"buildId":"J0_U0BvcaRcwD8yVFaRlm","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}