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Chronic liver disease (CLD) and cirrhosis are associated with immune dysregulation, leading to concerns that affected patients may be at risk of adverse outcomes following SARS-CoV-2 infection. We aimed to determine the impact of COVID-19 on patients with pre-existing liver disease, which currently remains ill-defined.
In this paper, the authors reported that cirrhosis was significantly associated with coronavirus disease 2019 (COVID-19) mortality on multivariable analysis. Meanwhile, other studies have reported that cirrhosis is not significantly associated with the risk for COVID-19 mortality on multivariable analysis.
This suggested that the association between cirrhosis and COVID-19 mortality remains inconclusive. Therefore, we performed this meta-analysis to clarify the association between cirrhosis and COVID-19 mortality based on confounding cofactors-controlled effect estimates.
A systematic search was performed in PubMed, Web of Science, EMBASE, Springer Link, Wiley Library, Elsevier ScienceDirect and Cochrane Library to identify all relevant studies as of August 12, 2022. The search terms were: “coronavirus disease 2019”, “COVID-19”, “severe acute respiratory syndrome coronavirus 2”, “SARS-CoV-2”, “mortality”, “cirrhosis” and “liver cirrhosis”. We included the articles reporting the confounding cofactors-controlled effect estimates on the association between cirrhosis and COVID-19 mortality. We excluded preprints, reviews, duplications, errata, case reports and studies reporting the confounding cofactors-uncontrolled effect estimates. We also examined the reference lists of reviews and retrieved original literature to identify all relevant articles. Two authors independently performed literature search and data extraction. Any discrepancy was resolved by consulting the third author. This meta-analysis was reported following the Preferred Reporting Items for Systematic Reviews and Meta-analysis (PRISMA) guidelines.
Heterogeneity was assessed by using the I2 statistic and Cochran’s Q test. The pooled effects and 95% CIs were estimated using a random-effect model. Publication bias was evaluated by Begg’s test. Sensitivity analysis, subgroup analysis and meta-regression were also performed. All statistical analyses were conducted by Stata 11.2 software. p <0.05 was considered statistically significant.
We included 29 articles including data on 6,872,587 individuals with COVID-19. Our meta-analysis indicated that individuals with COVID-19 and cirrhosis had a significantly increased risk of mortality compared to those without cirrhosis based on confounding cofactors-controlled effect estimates (pooled effect = 1.64, 95% CI 1.37–1.96; Fig. 1A). Sensitivity analysis indicated our results were robust (Fig. 1B). We observed consistent results in the subgroup analyses by age (pooled effect = 2.10, 95% CI 1.47–2.99 for age <60, and pooled effect = 1.33, 95% CI 1.17–1.50 for age ≥60), proportion of males (pooled effect = 2.00, 95% CI 1.32–3.04 for proportion of males <50%, and pooled effect = 1.52, 95% CI 1.29–1.80 for proportion of males ≥50%), sample size (pooled effect = 1.86, 95% CI 1.26–2.75 for <3,000 cases, and pooled effect = 1.57, 95% CI 1.24–1.99 for ≥3,000 cases), study design (pooled effect = 1.46, 95% CI 1.25–1.71 for retrospective study, and pooled effect = 1.89, 95% CI 1.32-2.69 for prospective study) and setting (pooled effect = 1.42, 95% CI 1.23–1.64 for studies with all patients, and pooled effect = 1.76, 95% CI 1.27–2.45 for studies with hospitalized patients). Meta-regression indicated that no tested factors contributed to heterogeneity (age, p = 0.068; proportion of males, p = 0.093; sample size, p = 0.459; study design, p = 0.676; setting, p = 0.217). Begg’s test indicated that there was no publication bias in this meta-analysis (p = 0.138).
Cirrhosis is the end stage of many chronic liver diseases.
Immune dysfunction associated with cirrhosis and fragile physiological buffering may increase susceptibility to severe COVID-19, meanwhile, SARS-CoV-2 infection can precipitate new or worsening acute hepatic decompensation and acute-on-chronic liver failure in individuals with cirrhosis, leading to adverse outcomes.
will certainly play a role. The stage of cirrhosis (e.g., Child-Pugh and model for end-stage liver disease [MELD] score) is as important as the pandemic itself (the impact of the different SARS-CoV-2 variants and the impact of vaccination also play a role). Unfortunately, of the studies we included, only five studies described the stage of cirrhosis at baseline by different methods such as Child-Pugh score, MELD score, and chronic liver failure organ failure (CLIF-OF) score, etc. Few included studies addressed the effects of different SARS-CoV-2 variants and vaccination on the association between cirrhosis and COVID-19 mortality. Thus, limited data prevented us from performing further analysis.
In conclusion, this meta-analysis based on confounding cofactors-controlled data indicated that cirrhosis was an independent predictor for COVID-19 mortality. The analysis confirmed what the recent EASL position paper noted.
Further well-designed studies based on prospective study estimates are warranted to confirm our findings. We hope that the data from this quantitative meta-analysis will contribute to more accurate elaboration and substantiation of the study by Marjot et al.
The authors received no financial support to produce this manuscript.
Conflict of interest
All authors report that they have no potential conflicts of interest.
Please refer to the accompanying ICMJE disclosure forms for further details.
Haiyan Yang conceptualized the study. Ying Wang and Mengke Hu performed literature search and data extraction. Ying Wang analyzed the data. Ying Wang and Mengke Hu wrote the manuscript. All the authors approved the final manuscript.
Data availability statement
The data that support the findings of this study are included in this article and available from the corresponding author upon reasonable request.
We would like to thank Xueya Han, Shuwen Li, Ruiying Zhang, Jiahao Ren, Hongjie Hou, Peihua Zhang, Yang Li, Jian Wu, Xuan Liang, Wenwei Xiao, Jie Xu and Li Shi (All are from Department of Epidemiology, School of Public Health, Zhengzhou University) for their kind help in searching articles and collecting data, and valuable suggestions for analyzing data.
The following are the supplementary data to this article: