Altmetrics
Downloads
227
Views
72
Comments
0
A peer-reviewed article of this preprint also exists.
This version is not peer-reviewed
Preprints on COVID-19 and SARS-CoV-2
Submitted:
03 April 2023
Posted:
04 April 2023
You are already at the latest version
References | Was used in meta-analysis (total number) | Contry of study | Study design, included patients (total/NAFLD, MAFLD) | Outcomes | Limitations |
---|---|---|---|---|---|
Zhou et al., 2020 [57] | [72,73,74,75,76](5) | China | Retrospective, matched cohorts, 110/55 | Independent of other confounding factors, the presence of MAFLD among patients below 60 years of age is positively associated with the development of severe or critical COVID-19. | Matching of patients was not performed based on the primary outcome variable. |
Zhou et al., 2020 [58] | [72,73,74,75,77] (5) | China | Retrospective cohort study, 327/93 | Younger patients with MAFLD have a higher risk for severe COVID progression or mortality. | A minor sample size of the older cohort of patients |
Zheng et al., 2020 [59] | [73,74,76] (3) | China | Retrospective cohort study, 214/66 | Co-occurring obesity in patients with MAFLD was found to increase the risk of severe illness by over six times. | Patients did not undergo liver biopsy. Waist circumference was not measured in patients. Patients were only of Asian ethnicity |
Huang et al., 2020 [45] | [72,73,76] (3) | China | Retrospective cohort study, 280/66 | SARS-CoV-2 infection in patients NAFLD is positively associated with an elevated risk of liver injury development. However, no patient with COVID-19 with NAFLD developed severe liver injury. | HSI was employed for the purpose of identifying the presence of NAFLD in the absence of any known liver pathologies. |
Ji et al., 2020 [46] | [72,73,74,75,76,77] (6) | China | Retrospective cohort study, 202/76 | Injury in patients with COVID-19 was frequent but mild in nature. | Small sample size, the Asian cohort. Very different co-morbidities among groups, definition of NAFLD only through IHS. |
Targher et al., 2020 [47] | [72,73,74,75,76] (5) |
China | Retrospective cohort study, 310/94 | More severe COVID-19 with higher FIB-4 or NFS. | Small sample size, the Asian ancestry of the cohort and the use of NFS without a histological diagnosis of liver fibrosis. No full paper |
Gao et al., 2021 [60] | [72,73,74,75,76] (5) |
China | Retrospective case-control study, 130/65 | The presence of MAFLD in nondiabetic patients was associated with a four-fold increased risk of severe COVID-19. | Diagnosing NAFLD only by CT and clinical criteria. Same patients with Zhou et al. 2020 [57] |
Chen et al., 2021 [48] | [73,76] (2) | USA | Retrospective single-center cohort study, 342/178 | The presence of HS in COVID-19 patients was observed to correlate with augmented disease severity and transaminitis. | Comorbidities were not taken into account. Metabolic status is not balanced. Using the HSI and imaging to define HS. |
Hashemi et al., 2020 [61] | [72,73,77] (3) | USA | Retrospective cohort study,363/55 | NAFLD significantly associated with ICU admission and with needing mechanical ventilation. | Using both imaging studies and histopathology for diagnosing LCD. Patients with milder courses of COVID-19, potentially over-estimating the effects of SARS-CoV-2 on the liver |
Bramante et al., 2020 [49] | [72,73,76] (3) | USA | Retrospective cohort study, 6400/373 | Covid-19 hospitalization is significantly associated with the presence of NAFLD/NASH, and this risk appears to be attributable to obesity. | The presence of unmeasured confounders and residual bias may impact the validity of the results. |
Kim et al., 2021 [50] | [73,75] (2) | USA | Multicenter Observational cohort study, 867/456 | NAFLD does not have any risk factors for severe progression or mortality of COVID-19. | No control cohort wth liver disease, NAFLD ICD diagnosis. |
Steiner et al., 2020 [62] | [77] (1) | USA | Cross-sectional study, 396/213 | The likelihood of severe COVID-19 manifestation was higher among patients with NAFLD. | NAFLD was defined through imaging. Lack of information about metabolic status, no full paper. |
Marjot et al., 2021 [78] | [75] (1) | UK, USA | Retrospective cohort study, 932/362 | Patients with AIH were the same risk-averse outcomes as CLD causes (including NAFLD). | No clear NAFLD definition. Comparing only AIH and CLD cohorts. |
Marjot et al., 2021 [44] | [76] (1) | UK (origin) but data is multinational | Retrospective cohort study, 1345/322 | No increased mortality of patients with NAFLD. | There were no specific cohorts for NAFLD patients. No words about NAFLD definition. |
Forlano et al., 2020 [63] | [73,75,76,77] (4) | UK | Retrospective cohort study, 193/61 | The presence of NAFLD was not associated with worse outcomes in patients with COVID-19. NAFLD patients were younger on admission. | Study population was small. Only visualization methods were used. |
Vázquez-Medina et al., 2022 [51] | [75] (1) | Mexico | Retrospective cohort study, 359/ NAFLD – 79, MAFLD – 220. | The MAFLD cohort displayed a higher fatality rate, whereas the NAFLD group did not exhibit any marked distinction. | Using a noninvasive method for defining NAFLD and MAFLD. |
Moctezuma-Velázquez et al., 2021 [64] | [75] (1) | Mexico | Retrospective cohort study, 470/359 | NAFLD as per the DSI was associated with death and IMV need in hospitalized patients with COVID-19. | Definition NAFLD based on DSI, CT. |
Lopez-Mendez et al., 2020 [52] | [73,76](2) | Mexico | Retrospective, cross sectional study,155/66 | Prevalence of HS and significant liver fibrosis was high in COVID-19 patients but was not associated with clinical outcomes. | Estimating liver fibrosis through non-invasive models. |
Mahamid et al., 2021 [65] | [72,73,75,76,77] (5) |
Israel | Retrospective case-control study, 71/22 | The risk of severe COVID-19 is elevated in patients with NAFLD, regardless of gender and irrespective of the presence of metabolic syndrome. | Differences in metabolic status between groups, the small number of COVID-19 patients underwent CT to diagnose NAFLD |
Mushtaq et al., 2021 [53] | [77] (1) | Qatar | Retrospective cohort study, 269/320 | The presence of NAFLD is a predictor of mild or moderate liver injury, but not for mortality or COVID-19 severity. | Using HSI index for diagnosing. No full paper. |
Parlak et al., 2021 [66] | [76] (1) | Turkey | Retrospective cohort study, 343/55 | NAFLD was an independent risk factor for COVID-19 severity. | Definition NAFLD based on CT. Missed data comparing NAFLD and non-NAFLD cohorts |
Yoo et al., 2021 [54] | [75] (1) | South Korea | Retrospective cohort study, 72244/54913 (HIS - 26 041, FLI - 19 945, claims-based - 8 927). |
Patients with pre-existing NAFLD have a higher likelihood severe COVID-19 illness. | Using HIS, FLI and claims-based NAFLD for defining fat liver for the same patients. |
Vrsaljko et al., 2022 [67] | [75] (1) | Croatia | Prospective cohort study, 216/120 | NAFLD is associated with higher COVID-19 severity, more adverse outcomes, and more frequent pulmonary thrombosis. | Abdominal ultrasound was employed for the diagnosis of NAFLD. |
Valenti et al., 2020 [79] | N/A | UK | Mendelian randomization, 1460/526 | The predisposition for severe COVID-19 is not directly augmented by a genetic propensity for hepatic fat accumulation. | These results were obtained in an initial set of cases without detailed characterization. No full paper. |
Liu et al., 2022 [80] | N/A | UK | Mendelian randomization, N = 2 586 691 | No evidence to support a causal relationship between COVID-19 susceptibility/severity and NAFLD. | Potential data errors, limited patient characterization. Missing information about NAFLD cohort. No full paper |
Roca-Fernández et al., 2021 [81] | N/A | UK | Prospective cohort study (UK Biobank), 1043/327 | Patients with fatty liver disease were at increased risk of infection and hospitalization for COVID-19 | Small proportion of UKB participants. Restriction for blood biomarkers of liver disease. |
Simon et al., 2021 [68] | N/A | Sweden | Matched cohort study using the ESPRESSO, 182 147/42320-LCD, 6350-NAFLD | Patients with CLD had a higher risk of hospitalization for COVID-19, but did not have an increased risk of severe COVID-19. | There is no comparison for NAFLD cohort. Not every CLD was confirmed though biopsy. The cohort lacked detailed data regarding body mass index or smoking. |
Chang et al., 2022 [55] | N/A | South Korea | Retrospective cohort study, 3112 – FLI score | An augmented risk of severe COVID-19 complications was observed in patients with high fatty liver index (FLI), reflective of NAFLD. | Using FLI score for determining NAFLD. Dataset did not directly confirm NAFLD through biopsy or ultrasound. The time gap between body measurements in health screening and COVID-19 infection |
Okuhama et al., 2022 [69] | N/A | Japan | Retrospective cohort study, 222/ 89 – fatty liver | The manifestation of fatty liver on plain CT scan at the time of admission may constitute a risk factor for severe COVID-19. | No determination NAFLD/MAFLD. Using CT scan for screening fat liver disease. |
Tripon et al., 2022 [56] | N/A | French | Retrospective cohort study, 719/ 311 | Patients with NAFLD disease and liver fibrosis are at higher risk of progressing to severe COVID-19. | Using NFS for determining NAFLD. Missing some important parameters. |
Campos-Murguía et al., 2021 [70] | N/A | Mexico | Retrospective cohort study, 432/176 | In contrast to the presence of MAFLD, the occurrence of fibrosis is correlated with a heightened risk of severe COVID-19 and mortality. | Liver steatosis was diagnosed by CT scan, and fibrosis by non-invasive scores. |
Ziaee et al., 2021 [71] | N/A | Iran | Retrospective cohort study, 575/218 | Fatty liver is significantly more prevalent among COVID-19 against non-COVID-19 patients, they develop more severe disease and tend to be hospitalized for more extended periods. | There was no access to each patient's past medical history, so the term “fatty liver patients” was used. The lack of diagnosis data for control group patients |
Refferences | Number of studies/ included patients | Results | Advantages | Limitations |
Hegyi et al., 2021 [72] | 9 studies (8202 cases) | A 2.6-fold increased risk of severe COVID-19 is associated with MAFLD, while NAFLD is linked to a five-fold greater susceptibility; however, there was no discernable difference in hospital mortality between COVID-19 patients with MAFLD or NAFLD. | The study was executed with meticulous attention to methodological rigor. | Study involves only nine articles Most of the articles were published in Asian countries Data came mostly from retrospective studies; In-hospital mortality was not analyzed; High risk of bias in included articles. |
Singh et al., 2021 [73] | 14 studies (1851 cases) | In patients with COVID-19 infection, the presence of NAFLD increased the risk of severe disease and ICU admission; however, there was no discernable difference in mortality between COVID-19 patients with or without NAFLD. | The study's findings were adjusted for several possible confounding factors to provide a more accurate assessment of the relationship between the variables of interest. | The study involved only six articles; There was a lack of a robust and consistent definition of NAFLD in selected articles; Major covariates, such as age, sex, race, and co-morbidities, were adjusted in selected studies. There was a restricted scope for a robust subgroup analysis due to a fewer number of included studies. |
Tao et al., 2021 [77] | 7 studies (2141 cases) | The presence of MAFLD was linked to an elevated risk of severe COVID-19(odds ratios: 1.80, 95% CI: 1.53-2.13, P<0.00001), but not to an increased likelihood of death due to COVID-19 infection. | The study's robustness was further substantiated by a sensitivity analysis, which validated the initial findings. The inclusion of studies from both Chinese and foreign countries bolstered the generalizability of the results and improved the external validity of the study. | Insufficient representation of studies, notably those from China, limited the robustness of the meta-analysis. The majority of studies included in this analysis were cross-sectional, which may compromise their reliability as compared to more robust cohort studies. The etiology of the variation in the pooled prevalence could not be determined. |
Pan et al., 2020 [74] | 6 studies (1,293 cases) | The study demonstrated that MAFLD is independently associated with an elevated risk of severe COVID-19 and a higher prevalence of COVID-19 in individuals with MAFLD compared to the general population. | The heterogeneity observed in the studies was reasonably acceptable, thereby ensuring the reliability of the outcomes. | The included studies were limited in number and conducted exclusively within China. There were only six studies included in the final analysis; Only one study had a subgroup analysis; The studies included in the analysis were mainly cross-sectional and case-control studies, which are generally regarded as less robust than prospective cohort studies. |
Wang et al., 2022 [75] | 18 studies (22,056 cases) | The presence of NAFLD was found to be independently associated with severe COVID-19, particularly in younger patients compared to older ones. | The overall odds ratio was derived by considering the effects sizes adjusted for risk factors, mainly age, sex, smoking, obesity, diabetes, and hypertension. A sensitivity analysis was conducted (it showed no significant impact on the overall results). | There is no statement regarding protocol and registration Authors used free-text only in their search strategy without including the MeSH approach; Detailed flow diagram that would illustrate the study selection process, sample size, PICOS, follow-up period, and citations of the included studies was not provided. The authors did not report the odds ratio (OR) in a clear and specific manner. There is no corresponding analysis of the risk of bias; No full paper. |
Li et al., 2022 [82] | 3 genome-wide association study (8267 cases) | The available evidence does not suggest a direct cause-and-effect association between NAFLD and the severity of COVID-19. The correlation between NAFLD and COVID-19 reported in prior studies is likely explained by the interrelatedness of NAFLD and obesity. The impact of comorbid factors associated with NAFLD on severe COVID-19 is largely attributed to body mass index, waist circumference, and hip circumference, based on evidence of causality. | Mendelian Randomization analysis provides a possibility to examine the causal relationship between NAFLD and severe COVID-19; Using COVID-19 genome-wide association study summary statistics. | The findings of the study cannot be generalized to evaluate the relationship between the severity of NAFLD and the risk of severe COVID-19, as the analysis only considered the presence of liver fat as the exposure variable. One of the selected research studies utilized one-sample-based MR analysis, which may be susceptible to bias [79]; The present findings may be subject to limitations arising from the small size of the sample population, as well as potential confounding clinical covariates that remain unidentified. These results somewhat contradict the observational studies of the same authors in other studies [7,83]; |
Hayat et al., 2022 [76] | 16 studies (11484 cases) | The occurrence of COVID-19 was found to be 0.29 among individuals with MAFLD. A heightened likelihood of COVID-19 severity and higher ICU admission rate were observed among patients with MAFLD. The correlation between MAFLD and COVID-19 mortality did not achieve statistical significance. | This study represents a novel contribution to the field, as it is the first to comprehensively investigate COVID-19-related mortality in a large and diverse cohort of MAFLD patients. Additionally, the study uniquely examines both the prevalence of MAFLD and the associated COVID-19 outcomes in a broad and extensive MAFLD population. | The respective studies included in this meta-analysis did not include a robust and consistent definition of the severity of COVID-19. Some included studies do not account for confounding factors such as age, race, gender and certain other co-morbidities. There were multiple comorbidities in the study population, making it difficult to dissect the contribution of each comorbidity to COVID-19 outcomes.; Fewer studies were included in the subgroup analysis of the effect of MAFLD on the COVID-19 ICU entrance and mortality rate making it difficult to analyze the publication bias (fewer than ten articles). |
Study | Region | Sample size (n) | Elevated ALT | Elevated AST | Elevated ALP | Elevated GGT | Elevated TBIL | Elevated LDH | Reduced Albumin |
Guan et al., 2020 [95] | Nationwide, China | 722-757 | 158/741 (21.3%) | 168/757 (22.2%) | N/A | N/A | 76/722 (10.5%) | 277/675 (41,0%) | N/A |
Xu et al., 2020 [98] | Hubei, Zhejiang, Anhui, Shandong, Jiangsu, China | 430-581 | 95/504 (19%) | 82/460 (18%) | N/A | N/A | 60/430 (14%) | 171/383 (45%) | 260/581 (45%) |
Yang et al., 2020 [99] |
Hubei Province, China |
200 | 44 (22 %) | 74 (37 %) | N/A | N/A | N/A | 74/189 (38.5 %) | 144 (72%) |
Cai et al., 2020 [109] | Shenzhen, China | 417 | 54 (12.9%) | 76 (18.2%) | 101 (24.2%) | 68 (16.3%) | 99 (23.7%) | N/A | N/A |
Richardson et al., 2020 [110] | New York, America | 5700 | 2176 (39.0%) | 3263 (58.4%) | N/A | N/A | N/A | N/A | N/A |
Wang et al., 2020 [100] | Fujian Province, China | 199 | 22 (11.1%) | 47 (23.6%) | N/A | N/A | 34 (17.%1) | 65 (32.7%) | 26 (13.1%) |
Hu et al., 2020 [101] | Hunan Province, China | 213 | 33 (15.5%) | 27 (12.7%) | N/A | N/A | 44 (20.7%) | 27 (12.7%) | N/A |
Xiong et al., 2020 [111] | Wuhan, China | 116 | 23 (19.8) | 46 (39.7) | N/A | N/A | N/A | 69 (59.5%) | N/A |
Yang et al., 2020 [102] | Wenzhou, China | 149 | 18 (12.08%) | 27 (18.12%) | N/A | N/A | 4 (2.68%) | 45 (30.20%) | 9 (6.04%) |
Yu et al., 2020 [104] |
Wuhan, China |
1443-1445 | 298/1445 (20.6%) | 303/1445 (21.0%) | N/A | N/A | N/A | 1110/1444 (76.9%) | 723/1443 (50.1%) |
Shen et al., 2020 [103] |
Shanghai, China |
325 | 53 (16.3%) | 54 (16.6%) | N/A | N/A | N/A | 125 (38.5%) | N/A |
Zhang et al., 2021 [5] | Wuhan, China | 267 | 49 (18.4%) | 76 (28.5%) | N/A | N/A | N/A | N/A | N/A |
Xu et al., 2021 [105] | Shanghai, China | 1003 | 295 (29.4%) | 176 (17.5%) | 26 (2.6%) | 134 (13.4%) | 40 (4.0%) | N/A | 307 (30.6%) |
Ding et al., 2021 [112] | Wuhan, China | 2073 | 501 (24.2%) | 545 (26.3%) | 165 (8.0%) | 443 (21.4%) | 71 (3.4%) | N/A | N/A |
Fu et al., 2021 [106] | Wuhan, China | 482 | 96 (19.9%) | 98 (20.3%) | N/A | N/A | 23 (4.8%) | N/A | 199 (41.3%) |
Lv et al., 2021 [107] | Wuhan, China | 2912 | 662 (22.7%) | 221 (7.5%) | 135 (4.6%) | 536 (18.4%) | 52 (1.8%) | N/A | 2086 (71.6%) |
Benedé-Ubieto et al., 2021 [113] | Madrid, Spain | 799 | 204 (25.73%) | 446 (49.17%) | 186 (24.21%) | 270 (34.62%) | N/A | 400 (55.84%) | N/A |
Weber et al., 2021 [108] | Munich, Germany | 217 | 59 (27.2%) | 91 (41.9%) | 22 (10.1%) | 80 (36.9%) | 10 (4.6%) | N/A | 71 (32.7%) |
Liu et al., 2021 [114] | Changsha, China. | 209 | 20 (9,6%) | 24 (11,5%) | N/A | N/A | 179 (85,6%) | 30 (14,4%) | N/A |
Lu et al., 2022 [115] | Sichuan, China | 70 | 32 (45.7%) | 22 (31.4%) | 12 (17.1%) | 32 (45.7%) | 32 (45.7%) | 40/69 (58,0%) | N/A |
Krishnan et al., 2022 [116] |
Baltimore, MD, United States |
3830 | 2698 (70.4%) | 1637 (44.4%) | 611 (16.1%) | N/A | 221 (5.9%) | N/A | N/A |
MAFLD | COVID-19 | |||||
Gut metabolites and inflammatory factors | Gut microbiome changes | Overlap | Gut microbiome changes | Gut metabolites and inflammatory factors | ||
↑Endotoxins [153,154]: activating the TLR4; ↑TNF-α, IL-1β, IL-6 and IL-12; hepatocyte injury; oxidative stress; hepatocyte apoptosis. ↑Lipopolysaccharides [155]: Activating of TLR4; ↑IL-6,IL-1β, serum LBP TNF-α, chemokines; ↓↑Bile acid metabolites[147,156,157,158]: ↑IL-6,IL-8, IL-12,IL-1β, TNF-α, IL-1β, IFN-y; ↓ IL-10. ↑Bacterial DNAs [159]: activating the TLR9; activating of NF-κB/MAPK; macrophages, NK cells, B cells, dendritic cells; ↑IL-12 and TNF-α. ↑Peptidoglycan [160]: activating of NF-κB/MAPK, NOD1, NOD2; ↑pro-inflammatory cytokines. ↓Indole-3-acetic acid (IAA) [161]: ↑TNF-α, MCP-1 та IL-1β. |
↓Alistipes ↓Anaerosporobacter ↓Coprobacter ↓Haemophilus ↓Moryella ↓Oscillobacter ↓Pseudobutyrivibrio ↓Subdoligramulum ↓Methanobrevibacter ↓Oscillospira ↓Phascolarctobacterium [162] ↓Rhuminococcaceae ↓Rikenellaceae ↓Prevotella ↓Prevotellaceae ↓Clostridiaceae ↓Clostridium [163] |
↑Acidaminococcus ↑Akkermansia ↑Allisonella ↑Anaerococcus ↑Bradyrhizobium ↑Dorea ↑Eggerthella ↑Escherichia ↑Flavonifractor incertae sedis ↑Parabacteroides ↑Peptoniphilus ↑Porphyromonas ↑Robinsonella ↑Ruminococcus ↑Shigella [162] ↑Proteobacteria ↑Enterobacteria [164] ↑Subdoligranulum ↑Blautia sp ↑Firmicutes ↑Roseburia ↑Oscillibacter [165] ↑Fusobacteria [163] |
↑Bacteroides , ↓Bifidobacterium ↓Eubacterium , ↓Faecalibacterium [166]-COVID-19 [162]-MAFLD ↓Coprococcus [150]- COVID-19 [162]- MAFLD ↑Streptococcus [151]- COVID-19 [165]- MAFLD ↑Enterobacteriaceae [166]- COVID-19 [163]- MAFLD ↓Lactobacillus [167]- COVID-19 [162]- MAFLD |
↓Roseburia, ↓Lachnospiraceae ↓Bacteroidetes ↓Blautia wexlerae, [166] ↓Dorea ↓Ruminococus [150] ↓Ruminococcus bromii [167] |
↑Enterobacteriaceae ↑Enterococcus ↑Actinomyces ↑Clostridium [166] ↑Rothia ↑Veillonella [151] ↑Blautia spp ↑Campylobacter ↑Corynebacterium ↑Enterococcaceae ↑Pseudomonas ↑Staphylococcus [167] ↑Klebsiella [168] |
↓SCFA [169,170]: ↓effector T cells; ↓IL-17, IFN-γ, and/or IL-10. ↑Lipopolysaccharides [155,171]: Activating of TLR4; ↑IL-6,IL-1β, serum LBP TNF-α, chemokines; ↓↑Bile acid metabolites [147,149,156,157,158,171] inhibit NF-Κb ↑IL-6,IL-8, IL-12,IL-1β, TNF-α, IL-1β, IFN-y; ↓ IL-10; progression of respiratory failure [149]. |
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content. |
© 2024 MDPI (Basel, Switzerland) unless otherwise stated