Abstract
Background
Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease associated with systemic changes in immune response, which might be associated with coronavirus disease 2019 (COVID-19) severity. The aim of this study was to investigate the impact of NAFLD on COVID-19 severity and outcomes.
Methods
A prospective observational study included consecutively hospitalized adult patients, hospitalized between March and June 2021, with severe COVID-19. Patients were screened for fatty liver by ultrasound and subsequently diagnosed with NAFLD. Patients were daily followed until discharge, and demographic, clinical, and laboratory data were collected and correlated to clinical outcomes.
Results
Of the 216 patients included, 120 (55.5%) had NAFLD. The NAFLD group had higher C-reactive protein (interquartile range [IQR]) (84.7 [38.6–129.8] mg/L vs 66.9 [32.2–97.3] mg/L; P = .0340), interleukin-6 (49.19 [22.66–92.04] ng/L vs 13.22 [5.29–39.75] ng/L; P < .0001), aspartate aminotransferase (58 [40–81] IU/L vs 46 [29–82] IU/L; P = .0123), alanine aminotransferase (51 [32–73] IU/L vs 40 [23–69] IU/L; P = .0345), and lactate dehydrogenase (391 [285–483] IU/L vs 324 [247–411] IU/L; P = .0027). The patients with NAFLD had higher disease severity assessed by 7-category ordinal scale, more frequently required high-flow nasal cannula or noninvasive ventilation (26, 21.66%, vs 10, 10.42%; P = .0289), had longer duration of hospitalization (IQR) (10 [8–15] days vs 9 [6–12] days; P = .0018), and more frequently had pulmonary thromboembolism (26.66% vs 13.54%; P = .0191). On multivariable analyses, NAFLD was negatively associated with time to recovery (hazard ratio, 0.64; 95% CI, 0.48 to 0.86) and was identified as a risk factor for pulmonary thrombosis (odds ratio, 2.15; 95% CI, 1.04 to 4.46).
Conclusions
NAFLD is associated with higher COVID-19 severity, more adverse outcomes, and more frequent pulmonary thrombosis.
Keywords: COVID-19, SARS-CoV2, non-alcoholic fatty liver disease, NAFLD, pulmonary thrombosis
The clinical spectrum of coronavirus disease 2019 (COVID-19) disease ranges in severity from asymptomatic to critical illness with acute respiratory distress syndrome, multiple organ failure, and high mortality rates in specific patient populations [1]. There is growing evidence that components of metabolic syndrome, such as diabetes, obesity, or hyperlipidemia, all related to nonalcoholic fatty liver disease (NAFLD), increase susceptibility to infection and adverse outcomes [2]. NAFLD is the most common chronic liver disease, affecting about 25% of the Western population, and is linked to chronic low-grade inflammation, impaired immune response, and microvascular endothelial dysfunction, which might have a profound impact on COVID-19 outcomes [2–4].
Surprisingly, the publications on the impact of NAFLD on infections in the pre-COVID era are scarce, and COVID-19 unveiled the magnitude of the growing NAFLD pandemic, indicating a potential significant role in infectious diseases. Still, the impact of NAFLD on COVID-19 remains unclear. According to limited data, it seems that patients with NAFLD have higher risk for infection and symptomatic disease [5–7]. In COVID-19, NAFLD was associated with liver injury of uncertain clinical significance [8]. However, the data on NAFLD as a predictor of disease severity and mortality in patients with COVID-19 are conflicting; while some studies show no difference in clinical presentations, other show increased mortality [8–12]. Most of the published data originate from retrospective studies from the beginning of pandemic, and there are no prospective studies from the later period.
Here we have designed a prospective cohort study with the aim to investigate a possible association between NAFLD and COVID-19 severity, complications, and outcomes.
METHODS
Study Design and Patients
A prospective, noninterventional monocentric observational study was conducted at the University Hospital for Infectious Diseases Zagreb (UHID), Croatia (COVID-FAT, ClinicalTrials.gov Identifier: NCT04982328). Included were consecutively hospitalized adult patients with confirmed COVID-19 between March and June 2021. Inclusion criteria were severe disease, defined as bilateral pneumonic infiltrates on chest imaging, Sp02 ≤94% on room air and/or dyspnea or respiratory frequency ≥24 breaths/min. Exclusion criteria were history of chronic liver disease, significant alcohol consumption, active cancer, pregnancy, immunocompromised patients, and palliative management. Patients who required oxygen supplementation for <24 hours, who were admitted to the intensive care unit (ICU) within the first 24 hours, and those who died in the first 48 hours of hospital admission were excluded from the study. A flowchart of the study’s design is presented in Supplementary Figure 1. All participants gave written informed consent. The study conformed to the ethical guidelines of the Declaration of Helsinki and was approved by Ethics Committee of the UHID Zagreb (code 01-673-4-2021).
Data Collection and Definitions
At the time of presentation, the following data were collected: demographic, clinical, comorbidities, use of chronic medications, body mass index, waist/hip ratio, baseline clinical status, and selected laboratory data. Clinical evolution, including oxygen requirements, invasive and noninvasive ventilation, and complication rates (including pulmonary thrombosis [PT]), was assessed daily.
Patients were treated according to standard of care with remdesivir (up to 5 days), corticosteroids, low–molecular weight heparin (LMWH), and tocilizumab at the discretion of the managing physician. Multislice computed tomography (MSCT) pulmonary angiography was performed according to hospital protocol in all patients who required high-flow nasal cannula (HFNC) oxygen therapy or noninvasive ventilation (NIV), in those who required oxygen supplementation >15 L/02, or if there was clinical suspicion of PT.
Upon admission, patients were screened for fatty liver by ultrasound and/or by measurement of the difference between liver and spleen computed tomography (CT) attenuation in patients who underwent CT angiography. Patients were subsequently diagnosed with NAFLD according to current guidelines that require: (1) evidence of liver steatosis, (2) no significant alcohol consumption, (3) no competing causes of liver steatosis, and (4) no coexisting causes of chronic liver disease [4, 13].
Outcomes
Patients’ clinical status was assessed daily using a 7-category ordinal scale from day 0 to day 28, hospital discharge, or death. The categories were defined as follows: (1) discharged, (2) hospitalized but ready to be discharged, (3) requiring low-flow supplemental oxygen, (4) requiring HFNC or NIV, (5) requiring invasive mechanical ventilation, (6) requiring extracorporeal membrane oxygenation, and (7) death. Overall survival and the proportion of patients with clinical improvement were assessed. Other outcomes measured were duration of hospitalization, time to recovery (measured as discharge or readiness for discharge), presence of complications, and pulmonary thrombosis.
Statistical Analysis
Clinical characteristics and laboratory and demographic data were evaluated and descriptively presented. The Fisher exact test and Mann-Whitney U test were used to compare the 2 groups. All tests were 2-tailed; a P value <.05 was considered statistically significant. Time to hospital discharge or readiness for discharge was evaluated using the Kaplan-Meier method. Risk factors associated with negative outcomes were investigated using a univariate model and, subsequently, a multivariable Cox regression model by estimating the hazard ratio (HR) and its 95% confidence intervals. Multivariable Cox proportional hazards models were developed using backward elimination with P < .1 to retain variables in the model. Binary logistic regression analysis was used to assess the independent predictors of PT. Variables were entered in a backward stepwise logistic regression model. Statistically nonsignificant predictors were progressively excluded based on a likelihood ratio test. The strength of an association was expressed as an odds ratio (OR) and its corresponding 95% CI. Statistical analyses were performed using GraphPad Prism, version 9.1.1 (San Diego, CA, USA), and MedCalc, version 20.008 (MedCalc Software, Ostend, Belgium).
RESULTS
Baseline Patient Characteristics
Overall, 216 Caucasian patients were included in the study (137; 63.43% males; median age [IQR], 61 [50–67] years). One hundred twenty patients (55.5%) were diagnosed with NAFLD, and 46 (38.33%) patients had “lean-weight NAFLD.” Patients with NAFLD were younger and had a higher median body mass index (BMI) and waist-hip ratio, as presented in Table 1. There were no differences in other comorbidities or in the use of chronic medications.
Table 1.
Baseline Patients’ Characteristics
| NAFLD (n = 120) | Non-NAFLD (n = 96) | Difference (95% CI)a | P Valueb | |
|---|---|---|---|---|
| Age, median (IQR), y | 59 (49.25–64.75) | 63 (55–71) | 4.00 (1.00 to 8.00) |
.0096 |
| Male, No. (%) | 78 (65) | 59 (61.46) | 0.006 (–0.12 to 0.14) |
.6700 |
| Overweight (BMI 25–30 kg/m2), No. (%) | 22 (18.33) | 22 (22.92) | 0.04 (–0.07 to 0.16) |
.4968 |
| Obesity (BMI >30 kg/m2), No. (%) | 74 (61.67) | 26 (27.08) | 0.34 (0.21 to 0.46) |
.0001 |
| BMI, median (IQR), kg/m2 | 31.25 (28.67–34.66) | 27.17 (24.22–30.67) | –4.08 (–6.45 to –2.81) |
<.0001 |
| Waist-hip ratio, median (IQR) | 1.04 (0.97–1.10) | 0.90 (0.84–1.05) | –0.13 (–0.17 to –0.06) |
<.0001 |
| Comorbidities, No. (%) | ||||
| Diabetes mellitus | 20 (16.67) | 10 (10.42) | 0.06 (–0.04 to 0.15) |
.2358 |
| Arterial hypertension | 47 (39.17) | 45 (46.88) | 0.07 (–0.06 to 0.21) |
.2707 |
| Gastritis/GERD | 5 (4.17) | 5 (5.21) | 0.01 (–0.06 to 0.07) |
.7539 |
| Dyslipidemia | 16 (13.33) | 15 (15.62) | 0.02 (–0.08 to 0.12) |
.6979 |
| Cardiovascular disease | 7 (5.83) | 10 (10.42) | 0.04 (–0.04 to 0.12) |
.3092 |
| Use of chronic medications, No. (%) | ||||
| ACE inhibitors | 33 (27.50) | 28 (29.17) | 0.02 (–0.11 to 0.14) |
.8793 |
| Beta blockers | 22 (18.33) | 22 (22.29) | 0.04 (–0.07 to 0.16) |
.4968 |
| Acetylsalicylic acid | 12 (10.00) | 15 (15.63) | 0.05 (–0.05 to 0.15) |
.2226 |
| Proton pump inhibitors | 14 (11.67) | 7 (7.29) | 0.04 (–0.05 to 0.13) |
.3576 |
| Statins | 11 (9.17) | 13 (13.54) | 0.04 (–0.05 to 0.13) |
.3847 |
| Metformin | 11 (9.17) | 6 (6.25) | 0.03 (–0.05 to 0.11) |
.4598 |
| Other perioral antidiabetic | 10 (8.33) | 3 (3.13) | 0.05 (–0.02 to 0.12) |
.1515 |
| Duration of illness on admission, median (IQR), d | 10 (7–12) | 10 (8–13) | 0.00 (0.00 to 2.00) |
.2297 |
| Laboratory findings on admission, median (IQR) | ||||
| C-reactive protein, mg/L | 84.7 (38.6–129.8) | 66.9 (32.2–97.3) | –17.7 (–30.0 to –1.1) |
.0340 |
| Procalcitonin, µg/L | 0.13 (0.09–0.25) | 0.09 (0.07–0.17) | –0.04 (–0.05 to –0.01) |
.0035 |
| Interleukin-6, ng/L | 49.19 (22.66–92.04) | 13.22 (5.29–39.75) | –35.9 (–51.4 to –13.5) |
<.0001 |
| Ferritin, µg/L | 899 (501–1378) | 623 (437–1417) | –275.5 (–431.0 to 128.0) |
.2581 |
| White blood cell count, ×109/L | 6.5 (4.9–9.3) | 7.2 (5.5–9.4) | 0.70 (–0.40 to 1.20) |
.3270 |
| Lymphocyte’s count, 109/L | 0.76 (0.57–1.08) | 0.75 (0.51–1.04) | –0.0004 (–0.17 to 0.14) |
.4431 |
| Neutrophil/lymphocyte ratio | 6.96 (3.94–10.49) | 8.09 (4.94–10.79) | 1.13 (–0.51 to 1.97) |
.2327 |
| Hemoglobin, g/L | 140 (132–147) | 138 (129–146) | –2.00 (–5.00 to 2.00) |
.2893 |
| Platelets, ×109/L | 183 (138–253) | 187 (151–251) | 4.00 (–10.00 to 33.00) |
.3182 |
| Bilirubin, µmol/L | 11 (9–14) | 11 (9–15) | 0.00 (–1.00 to 1.00) |
.6197 |
| Aspartate aminotransferase, IU/L | 58 (40–81) | 46 (29–82) | –12.00 (–17.00 to –2.00) |
.0123 |
| Alanine aminotransferase, IU/L | 51 (32–73) | 40 (23–69) | –11.00 (–15.00 to –1.00) |
.0345 |
| Gamma-glutamyl transferase, IU/L | 60 (34–116) | 44 (31–77) | –16.00 (–22.00 to –1.00) |
.0335 |
| Lactate dehydrogenase, IU/L | 391 (285–483) | 324 (247–411) | –67.00 (–96.00 to –20.00) |
.0027 |
| Creatinine kinase, IU/L | 146 (85–420) | 98 (59–351) | –48.00 (–69.00 to –2.00) |
.0357 |
| Serum albumins, g/L | 39.6 (36.9–41.3) | 39.3 (36.4–41.5) | –0.300 (–1.40 to 0.80) |
.7412 |
| Fibrinogen, g/L | 5.8 (5.2–6.4) | 5.9 (5.3–6.4) | 0.10 (–0.20 to 0.40) |
.5319 |
| D-dimers, mg/L | 0.76 (0.48–1.30) | 0.86 (0.53–1.53) | 0.09 (–0.05 to 0.24) |
.2327 |
Abbreviations: BMI, body mass index; GERD, gastroesophageal reflux disease; IQR, interquartile range; NAFLD, nonalcoholic fatty liver disease.
Presented are standardized differences between medians or proportions with corresponding 95% CIs.
Fisher exact or Mann-Whitney U test, as appropriate.
Time since symptom onset to hospital admission (IQR) was similar between groups (10 [7–12] days vs 10 [8–13] days; P = .2297). On admission, required oxygen supplementation to maintain SpO2 ≥90% was similar between groups (median [IQR], 7L [3–25] O2/min).
Patients with NAFLD had significantly higher inflammatory markers, including C-reactive protein (CRP), procalcitonin, and interleukin-6, and higher aspartate aminotransferase, alanine aminotransferase, and gamma-glutamyl transferase (Table 1). There were no differences in laboratory findings in patients with NAFLD and obesity compared with patients with NAFLD without obesity (Supplementary Table 1).
Patients were treated according to current standard of care: remdesivir (138, 63.88%), corticosteroids (dexamethasone [183, 84.72%] and/or methylprednisolone [55, 25.46%]), LMWH (214, 99.07%), and tocilizumab (21, 9.72%). Details of treatment regimens used are provided in Supplementary Table 1. Except for remdesivir, which was more frequently prescribed in patients with NAFLD (84, 70%, vs 54, 56.2%; P = .0459), there were no other differences in the choice of treatment between groups.
Clinical Course and Outcomes
At admission, patients with NAFLD had higher disease severity, assessed by a 7-category ordinal scale, as presented in Figure 1. Fourteen (11.7%) patients with NAFLD and 2 (2.1%) without NAFLD required HFNC within 24 hours after hospital admission (P = .0080).
Figure 1.
Seven-category ordinal scale at baseline and days 7, 14, and 28, stratified by the presence of NAFLD. Figure shows the patients’ clinical status as assessed on the 7-category ordinal scale on admission and at days 7, 14, and 28, according to the presence of NAFLD. Categories on the ordinal scale were as follows: (1) discharged or ready for discharge; (2) hospitalization in a non-ICU without supplemental oxygen; (3) non-ICU hospitalization with supplemental oxygen; (4) ICU or non-ICU hospitalization with noninvasive ventilation or high-flow oxygen; (5) ICU hospitalization with mechanical ventilation; (6) ICU hospitalization with ECMO or mechanical ventilation and additional organ support; and (7) death. The Wilcoxon rank-sum test was used to calculate differences between groups. Abbreviations: ECMO, extracorporeal membrane oxygenation; HFNC, high-flow nasal cannula; ICU, intensive care unit; NAFLD, nonalcoholic fatty liver disease; NIV, noninvasive ventilation.
The percentage of patients with clinical improvement by day 7 and day 14 was significantly higher in patients without NAFLD. By day 7, 27 (22.5%) patients with NAFLD compared with 39 (40.6%) without NAFLD were ready to discharge (P = .0048). By day 14, 86 (71.7%) patients with NAFLD and 85 (88.5%) without NAFLD were discharged from the hospital (P = .0024).
Patients with NAFLD more frequently required HFNC or NIV (26, 21.66%, vs 10, 10.42%; P = .0289) and had longer duration of hospitalization (IQR) (10 [8–15] vs 9 [6–12] days; P = .0018). Six (5%) patients with NAFLD and 3 (3.12%) controls required invasive mechanical ventilation. However, there were no differences in in-hospital mortality between groups (8, 6.67%, vs 3, 3.12%; P = .3529).
There were no differences in outcomes between obese and “lean-weight” NAFLD patients: requirement of HFNC/NIV (18, 24.32%, vs 8, 17.39%; P = .4950), PE (22, 29.73%, vs 10, 21.74%; P = .3992), mortality (5, 6.76%, vs 2, 4.35%; P = .7064), and duration of hospitalization (IQR) (10 [8–16] days vs 10 [7–15] days; P = .4873) (Supplementary Table 1).
Next, we examined the impact of NAFLD on time to recovery, as defined by time to hospital discharge or readiness for discharge. Multivariable Cox regression analysis identified age >60 years, pulmonary thrombosis, HFNC/NIV (Supplementary Figure 2), aspartate aminotransferase >60, and NAFLD (Figure 2) as being negatively associated with time to recovery (Table 2). Other comorbidities, use of chronic medications, inflammatory markers, and choice of treatment (remdesivir vs no remdesivir, tocilizumab vs no tocilizumab, dexamethasone in low [<8 mg] or high dose [>8 mg]) were not associated with readiness for discharge in our model.
Figure 2.
Kaplan-Meier curves and Cox proportional hazard ratios for time to discharge or readiness for discharge in patients with and without nonalcoholic fatty liver disease. Abbreviations: HR, hazard ratio; NAFLD, nonalcoholic fatty liver disease.
Table 2.
Multivariable Cox Regression Analysis of Factors Associated With Time to Discharge or Readiness for Discharge
| Hazard Ratio (95% CI) | P Value | |
|---|---|---|
| Age >60 y | 0.64 (0.48 to 0.85) | .0025 |
| Pulmonary thrombosis | 0.66 (0.45 to 0.95) | .0278 |
| HFNC/NIV | 0.26 (0.16 to 0.42) | <.0001 |
| AST >60 IU/L | 0.99 (0.99 to 0.99) | .0057 |
| NAFLD | 0.64 (0.48 to 0.86) | .0005 |
The strength of association was expressed as HR and its corresponding 95% CI. The area under the ROC curve in the fully adjusted model was 0.86 (95% CI, 0.81 to 0.90).
Abbreviations: AST, aspartate aminotransferase; HFNC/NIV, high-flow nasal cannula/noninvasive ventilation; HR, hazard ratio; NAFLD, nonalcoholic fatty liver disease; ROC, receiver operating characteristic.
Association of NAFLD With Pulmonary Thrombosis
Overall, 45 (20.83%) patients were diagnosed with pulmonary thrombosis during hospitalization: 32 (26.66%) with NAFLD and 13 (13.54%) without NAFLD (P = .0191). PT was described as massive in 6 patients with NAFLD, segmental in 14 patients with NAFLD and 5 non-NAFLD, and subsegmental in 12 patients with NAFLD and 8 non-NAFLD.
In order to identify factors associated with PT, we performed multivariable logistic regression analysis, which identified baseline CRP >100 mg/dL, lactate-dehydrogenase (LDH) >390 IU/L, lymphocyte count <1200 × 109/L, D-dimers >1.1 mg/L, and NAFLD as being associated with PT (Table 3). Age, BMI, obesity, and other comorbidities were not associated with PT in our model.
Table 3.
Multivariable Logistic Regression Analysis of Factors Associated With Pulmonary Thrombosis
| Odds Ratio (95% CI) | P Value | |
|---|---|---|
| C-reactive protein >100 mg/dL | 2.48 (1.17 to 5.24) | .0171 |
| Lactate dehydrogenase >390 IU/L | 2.36 (1.08 to 5.11) | .0299 |
| Lymphocyte count <1200 × 109/L | 4.74 (1.89 to 11.87) | .0011 |
| D-dimers >1.1 mg/L | 2.45 (1.19 to 5.58) | .0153 |
| NAFLD | 2.15 (1.04 to 4.46) | .0399 |
The strength of association was expressed as OR and its corresponding 95% CI. The area under the ROC curve in the fully adjusted model was 0.83 (95% CI, 0.77 to 0.88).
Abbreviations: NAFLD, nonalcoholic fatty liver disease; OR, odds ratio; ROC, receiver operating characteristic.
DISCUSSION
In this prospective cohort study, we found a significant association between NAFLD and COVID-19 severity, clinical course, and outcomes. In addition, this appears to be independent of other components of metabolic syndrome. This might have implications for clinical management and future studies for several reasons.
First, the prevalence of NAFLD (55%) was high in our cohort. Notably, only a few patients were previously diagnosed with NAFLD, which is consistent with the finding that 95% of patients are unaware of having NAFLD [14]. Overrepresentation of NAFLD in hospitalized COVID-19 patients has been reported with varied prevalence: 52% in the United States, 42% in Mexico, and 30% in Israel, the UK, and China [9, 10, 12, 15, 16]. The underdiagnosing of NAFLD emphasizes the need for large-scale health care campaigns and screening strategies.
Second, the patients with NAFLD had a more severe form of disease at admission, more frequently required HFNC or NIV, and had less probability for early discharge. Multivariable analysis identified NAFLD as being negatively associated with time to recovery. A significant association between NAFLD and COVID-19 severity has consistently been reported [2, 17]. A retrospective study from the United States showed that patients with NAFLD had significantly longer length of stay, ICU admission rate, and need for mechanical ventilation [18]. Similarly, Jin et al. in their retrospective study (n = 202, 76 patients with NAFLD, early 2020) showed that patients with NAFLD had a 2-fold higher risk of disease progression and longer viral shedding time [9].
Third, NAFLD was associated with COVID-19 disease severity regardless of BMI, and there was no significant difference between obese and “lean-weight NAFLD” in clinical outcomes. In contrast, a small retrospective study from China (n = 66) showed a 6-fold increased risk of severe COVID-19 in obese NAFLD patients [19]. While obesity was linked with COVID-19 severity in studies that did not include NAFLD as a variable, others showed no such association [20–22]. Similarly, a large UK study showed that obese patients without fatty liver are not at increased risk for symptomatic disease [7]. Our findings provide directions for future COVID-19 prognostic research, as NAFLD should be included as a variable, especially in patients with components of metabolic syndrome.
Next, we found that patients with NAFLD have higher inflammatory biomarkers, which were previously shown to be negative predictors of COVID-19 outcomes [23]. Several studies also showed higher CRP in patients with NAFLD and COVID-19 [12, 20]. As serum CRP and IL6 are natively elevated in NAFLD patients [24], this might be a possible link with worse outcomes. A recent comparative analysis of gene expression data sets offered additional explanations: Upregulation of ACE2 receptor and proprotein convertase FURIN might enable efficient viral replication, and increased expression of JAK1 and STAT1 corresponds with increased expression of cytokines and higher basal expression of CXCL10 and IL6 and proinflammatory signals [25]. Importantly, this was NAFLD-specific. Indeed, we have learned that not all patients respond to corticosteroids and IL-6R inhibitors. This might call for different anti-inflammatory therapeutic strategies in patients with NAFLD.
Finally, our study showed that patients with NAFLD have higher incidence of PT. Thromboembolic rates in COVID-19 are high and associated with higher mortality [26]. It seems that PT in COVID-19 patients is not associated with traditional risk factors such as age, history of malignancy, smoking, etc. A large multicenter cohort study showed that male sex, a longer delay from symptom onset to hospitalization, and systemic inflammation were independent predictors of PT [27]. The pathogenic mechanism includes COVID-19 endothelitis caused by direct viral infection and diffuse endothelial inflammation [28]. Several small postmortem analyses showed high steatosis prevalence in COVID-19 patients with thrombosis [29, 30]. To the best of our knowledge, this is the first prospective study suggesting an association between NAFLD and PT in COVID-19. The possible explanation includes higher levels of pro-inflammatory proteins and cytokines associated with systemic inflammation and higher plasma levels of von Willebrand factor and plasminogen activator inhibitor type 1 [31, 32]. There is an ongoing debate on dosing LMWH in patients with COVID-19 and the lack of protocols regarding who should be screened for PT [33]. Our findings might be important in identifying patients who might benefit from therapeutic doses of LMWH and who should be screened for PT. These should be confirmed in further studies.
In our study, NAFLD was associated with COVID-19 outcomes independently of other components of metabolic syndrome. This can be partially explained with low prevalence of class III obesity in our cohort. It seems that more than BMI, central fat distribution and metabolic consequences of obesity might be risk factors for COVID-19 severity, as recently described [34–36]. The specific role of NAFLD itself, not simply as a part of metabolic syndrome, has been already documented in noncommunicable diseases such as in heart failure, chronic kidney disease, and malignant diseases [37]. Similarly, NAFLD has been associated with severity of community-acquired pneumonia or Clostridioides difficile enterocolitis [38, 39]. It seems reasonable to speculate that altered immune responses and proinflammatory states in patients with NAFLD could predict COVID-19 severity, as described above.
Our study has a few associated caveats. The diagnosis of NAFLD was based on abdominal ultrasound, which is operator dependent; fibrosis stage was not evaluated as fibrosis scores may not be reliable in this setting, and elastography was not available at the COVID-19 department; therefore, the effect of advanced NAFLD on clinical outcomes was not analyzed; exclusion of patients who were admitted to the ICU in the first 24 hours or died during the first 48 hours could have led to selection bias, in which less severe patients were included, and this might be reflected in our mortality analysis.
Nevertheless, we report the first prospective data in a well-defined cohort study on the association of COVID-19 and NAFLD from the later phase of pandemic. The inconsistency in previously published data highlights the strengths of our study, as most of the studies were retrospective and from the mere beginning of the pandemic when there was no explicit classification of the COVID-19 disease, “standard of treatment” included possible hepatotoxic drugs, and standard of care was not well defined; a significant proportion of data are from Asian countries, mainly China, so there are not enough data from other ethnic populations. Furthermore, in previous studies, the definition of NAFLD varied and mainly included patients previously diagnosed with NAFLD, or the diagnosis was based on steatosis scores (mainly hepatic steatosis index, fatty liver index, or NAFLD score) or CT scans, which might not reliably distinguish preexisting steatosis from COVID-19-associated liver injury. The possible impact of different NAFLD diagnostic scores on COVID-19 outcomes was recently suggested in a large-scale population-based cohort study from South Korea [40]. The authors showed a significant association between the presence of NAFLD and COVID-19 severity using several diagnostic criteria, and they justifiably argue that the impact might vary depending on the definition used [40]. There is also an ongoing debate on the new definition of MAFLD [41], which was used in some studies, but has not yet been included in official guidelines. Due to the study design, we were not able to collect the patients’ prepandemic NAFLD scores; therefore, our results cannot directly be compared with previous studies.
In conclusion, we have shown a significant association between NAFLD, COVID-19 severity, and pulmonary thrombosis. The rapidly increasing prevalence of NAFLD requires novel therapeutic and prophylactic approaches based on better understanding of the immunopathogenesis of COVID-19 in these patients. Obviously, NAFLD should be included as a variable in future studies investigating COVID-19 outcomes and treatment strategies.
Supplementary Material
Acknowledgments
Financial support. This work was supported by the Croatian Science Foundation, project entitled “The Role of Immune Semaphorins in NAFLD and Sepsis” (principal investigator Neven Papić, project number UIP-2019-04-7194).
Disclaimer. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.
Potential conflicts of interest. The authors declare no conflicts of interest. All authors have submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
References
- 1. Serafim RB, Povoa P, Souza-Dantas V, Kalil AC, Salluh JIF.. Clinical course and outcomes of critically ill patients with COVID-19 infection: a systematic review. Clin Microbiol Infect 2021; 27:47–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2. Hegyi PJ, Vancsa S, Ocskay K, et al. Metabolic associated fatty liver disease is associated with an increased risk of severe COVID-19: a systematic review with meta-analysis. Front Med (Lausanne) 2021; 8:626425. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3. Van Herck MA, Weyler J, Kwanten WJ, et al. The differential roles of T cells in non-alcoholic fatty liver disease and obesity. Front Immunol 2019; 10:82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. European Association for the Study of the Liver, European Association for the Study of Diabetes, European Association for the Study of Obesity. EASL-EASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease. J Hepatol 2016; 64:1388–402. [DOI] [PubMed] [Google Scholar]
- 5. Bramante C, Tignanelli CJ, Dutta N, et al. Non-alcoholic fatty liver disease (NAFLD) and risk of hospitalization for Covid-19. medRxiv 2020.09.01.20185850 [Preprint]. 2 September 2020. Available at: 10.1101/2020.09.01.20185850. Accessed February 25, 2022. [DOI] [Google Scholar]
- 6. Ghoneim S, Butt MU, Hamid O, Shah A, Asaad I.. The incidence of COVID-19 in patients with metabolic syndrome and non-alcoholic steatohepatitis: a population-based study. Metabol Open 2020; 8:100057. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Roca-Fernández A, Dennis A, Nicolls R, et al. High liver fat associates with higher risk of developing symptomatic COVID-19 infection - initial UK biobank observations. medRxiv 2020.06.04.20122457 [Preprint]. 5 June 2020. Available at: 10.1101/2020.06.04.20122457. Accessed February 25, 2022. [DOI] [Google Scholar]
- 8. Mushtaq K, Khan MU, Iqbal F, et al. NAFLD is a predictor of liver injury in COVID-19 hospitalized patients but not of mortality, disease severity on the presentation or progression - the debate continues. J Hepatol 2021; 74:482–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Ji D, Qin E, Xu J, et al. Non-alcoholic fatty liver diseases in patients with COVID-19: a retrospective study. J Hepatol 2020; 73:451–3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Lopez-Mendez I, Aquino-Matus J, Gall SM, et al. Association of liver steatosis and fibrosis with clinical outcomes in patients with SARS-CoV-2 infection (COVID-19). Ann Hepatol 2021; 20:100271. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Zhou YJ, Zheng KI, Wang XB, et al. Metabolic-associated fatty liver disease is associated with severity of COVID-19. Liver Int 2020; 40:2160–3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Forlano R, Mullish BH, Mukherjee SK, et al. In-hospital mortality is associated with inflammatory response in NAFLD patients admitted for COVID-19. PLoS One 2020; 15:e0240400. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Chalasani N, Younossi Z, Lavine JE, et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology 2018; 67:328–57. [DOI] [PubMed] [Google Scholar]
- 14. Singh A, Dhaliwal AS, Singh S, et al. Awareness of nonalcoholic fatty liver disease is increasing but remains very low in a representative US cohort. Dig Dis Sci 2020; 65:978–86. [DOI] [PubMed] [Google Scholar]
- 15. Chen VL, Hawa F, Berinstein JA, et al. Hepatic steatosis is associated with increased disease severity and liver injury in coronavirus disease-19. Dig Dis Sci 2021; 66:3192–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Mahamid M, Nseir W, Khoury T, et al. Nonalcoholic fatty liver disease is associated with COVID-19 severity independently of metabolic syndrome: a retrospective case-control study. Eur J Gastroenterol Hepatol 2021; 33:1578–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Singh A, Hussain S, Antony B.. Non-alcoholic fatty liver disease and clinical outcomes in patients with COVID-19: a comprehensive systematic review and meta-analysis. Diabetes Metab Syndr 2021; 15:813–22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Younossi ZM, Stepanova M, Lam B, et al. Independent predictors of mortality among patients with NAFLD hospitalized with COVID-19 infection. Hepatol Commun. 2021: 10.1002/hep4.1802. doi: 10.1002/hep4.1802. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Zheng KI, Gao F, Wang XB, et al. Letter to the editor: obesity as a risk factor for greater severity of COVID-19 in patients with metabolic associated fatty liver disease. Metabolism 2020; 108:154244. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Yates T, Razieh C, Zaccardi F, et al. Obesity, walking pace and risk of severe COVID-19 and mortality: analysis of UK Biobank. Int J Obes (Lond) 2021; 45:1155–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Chu Y, Yang J, Shi J, Zhang P, Wang X.. Obesity is associated with increased severity of disease in COVID-19 pneumonia: a systematic review and meta-analysis. Eur J Med Res 2020; 25:64. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Taylor EH, Marson EJ, Elhadi M, et al. Factors associated with mortality in patients with COVID-19 admitted to intensive care: a systematic review and meta-analysis. Anaesthesia 2021; 76:1224–32. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Velavan TP, Meyer CG.. Mild versus severe COVID-19: laboratory markers. Int J Infect Dis 2020; 95:304–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Oruc N, Ozutemiz O, Yuce G, et al. Serum procalcitonin and CRP levels in non-alcoholic fatty liver disease: a case control study. BMC Gastroenterol 2009; 9:16. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Singh MK, Mobeen A, Chandra A, Joshi S, Ramachandran SA.. meta-analysis of comorbidities in COVID-19: which diseases increase the susceptibility of SARS-CoV-2 infection? Comput Biol Med 2021; 130:104219. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Malas MB, Naazie IN, Elsayed N, Mathlouthi A, Marmor R, Clary B.. Thromboembolism risk of COVID-19 is high and associated with a higher risk of mortality: a systematic review and meta-analysis. EClinicalMedicine 2020; 29:100639. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Fauvel C, Weizman O, Trimaille A, et al. Pulmonary embolism in COVID-19 patients: a French multicentre cohort study. Eur Heart J 2020; 41:3058–68. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Varga Z, Flammer AJ, Steiger P, et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet 2020; 395:1417–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Lax SF, Skok K, Zechner P, et al. Pulmonary arterial thrombosis in COVID-19 with fatal outcome: results from a prospective, single-center, clinicopathologic case series. Ann Intern Med 2020; 173:350–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30. Falasca L, Nardacci R, Colombo D, et al. Postmortem findings in Italian patients with COVID-19: a descriptive full autopsy study of cases with and without comorbidities. J Infect Dis 2020; 222:1807–15. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31. Verrijken A, Francque S, Mertens I, et al. Prothrombotic factors in histologically proven nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Hepatology 2014; 59:121–9. [DOI] [PubMed] [Google Scholar]
- 32. Magro C, Mulvey JJ, Berlin D, et al. Complement associated microvascular injury and thrombosis in the pathogenesis of severe COVID-19 infection: a report of five cases. Transl Res 2020; 220:1–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33. Porfidia A, Talerico R, Mosoni C, Porceddu E, Pola RC.. Pulmonary angiography for the diagnosis of pulmonary embolism in patients with COVID-19: when, why, and for who? Radiology 2021; 299:E287. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34. Kesztyus D, Lampl J, Kesztyus T.. The weight problem: overview of the most common concepts for body mass and fat distribution and critical consideration of their usefulness for risk assessment and practice. Int J Environ Res Public Health. 2021; 18:11070. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35. Bunnell KM, Thaweethai T, Buckless C, et al. Body composition predictors of outcome in patients with COVID-19. Int J Obes (Lond) 2021; 45:2238–43. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36. Goehler A, Hsu TH, Seiglie JA, et al. Visceral adiposity and severe COVID-19 disease: application of an artificial intelligence algorithm to improve clinical risk prediction. Open Forum Infect Dis 2021; 8:XXX–XX. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Zarghamravanbakhsh P, Frenkel M, Poretsky L.. Metabolic causes and consequences of nonalcoholic fatty liver disease (NAFLD). Metabol Open 2021; 12:100149. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38. Papic N, Jelovcic F, Karlovic M, Maric LS, Vince A.. Nonalcoholic fatty liver disease as a risk factor for Clostridioides difficile infection. Eur J Clin Microbiol Infect Dis 2020; 39:569–74. [DOI] [PubMed] [Google Scholar]
- 39. Nseir WB, Mograbi JM, Amara AE, Abu Elheja OH, Mahamid MN.. Non-alcoholic fatty liver disease and 30-day all-cause mortality in adult patients with community-acquired pneumonia. QJM 2019; 112:95–9. [DOI] [PubMed] [Google Scholar]
- 40. Yoo HW, Jin HY, Yon DK, et al. Non-alcoholic fatty liver disease and COVID-19 susceptibility and outcomes: a Korean nationwide cohort. J Korean Med Sci 2021; 36:e291. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41. Eslam M, Newsome PN, Sarin SK, et al. A new definition for metabolic dysfunction-associated fatty liver disease: an international expert consensus statement. J Hepatol 2020; 73:202–9. [DOI] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.