An Updated Systematic Review and Meta-Analysis of the Association between the De Ritis Ratio and Disease Severity and Mortality in Patients with COVID-19

Patients with Coronavirus disease 2019 (COVID-19) often have elevations in markers of liver injury, particularly serum aspartate transaminase (AST) and alanine transaminase (ALT). Such alterations may affect the AST/ALT ratio (De Ritis ratio) and, potentially, clinical outcomes. We conducted an updated systematic review and meta-analysis of the association between the De Ritis ratio and COVID-19 severity and mortality in hospitalized patients. PubMed, Web of Science, and Scopus were searched between 1 December 2019 and 15 February 2023. The Joanna Briggs Institute Critical Appraisal Checklist and the Grading of Recommendations, Assessment, Development, and Evaluation were used to assess the risk of bias and the certainty of the evidence, respectively. Twenty-four studies were identified. The De Ritis ratio on admission was significantly higher in patients with severe disease and non-survivors vs. patients with non-severe disease and survivors (15 studies, weighted mean difference = 0.36, 95% CI 0.24 to 0.49, p < 0.001). The De Ritis ratio was also associated with severe disease and/or mortality using odds ratios (1.83, 95% CI 1.40 to 2.39, p ˂ 0.001; nine studies). Similar results were observed using hazard ratios (2.36, 95% CI 1.17 to 4.79, p = 0.017; five studies). In six studies, the pooled area under the receiver operating characteristic curve was 0.677 (95% CI 0.612 to 0.743). In our systematic review and meta-analysis, higher De Ritis ratios were significantly associated with severe disease and mortality in COVID-19 patients. Therefore, the De Ritis ratio can be useful for early risk stratification and management in this patient group (PROSPERO registration number: CRD42023406916).


Introduction
Coronavirus disease 2019 (COVID- 19), an infection caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global health emergency by the World Health Organization since 2020 [1]. According to recent estimates, at least 15 million people have died as a result of COVID-19 [2]. However, the long-term clinical and psychological impact of the disease on survivors remain to be fully established [3,4]. Despite significant advances in the prevention and management of COVID-19, particularly with the introduction of vaccination programs at the population level and several effective antiviral and anti-inflammatory treatments, a significant number of patients are still at risk of severe disease and adverse outcomes, including death [5]. One important factor responsible for the ongoing public health burden of COVID-19 is the systemic, multi-organ involvement during the acute phase following infection [6,7]. The onset and the progression of multi-organ dysfunction, particularly in severe cases, is primarily driven by the

Statistical Analysis
We generated forest plots from weighted mean differences (WMDs) to assess the De Ritis ratio in patients with non-severe disease or survivor status and patients with severe disease or non-survivor status (p < 0.05 for statistical significance). Adjusted ORs or HRs were transformed into log ORs and log HRs, and the standard error was calculated based on the corresponding 95% CI. Heterogeneity was assessed using the Q statistic (p < 0.10 for statistical significance). We used a random-effect model in case of moderatesubstantial heterogeneity (I 2 values ≥ 30%) [39]. We assessed the influence of individual studies through sensitivity analysis [40]. Publication bias was assessed with the Begg's and Egger's tests (p < 0.05 for statistical significance) and the Duval and Tweedie "trim-and-fill" procedure [41][42][43]. In univariate meta-regression analysis, we investigated associations between the WMD/OR/HR and participant age, sex, study sample size, year of study publication, study design, markers of inflammation (WBC, CRP), markers of coagulation (D-dimer), and a history of diabetes, hypertension, and cardiovascular disease. In subgroup analyses, we investigated possible differences in effect size according to the clinical outcome studied (disease severity vs. mortality) and study continent. The prognostic performance of the De Ritis ratio was assessed by calculating the weighted summary AUROC using the fixed and/or random effects model [44]. Stata 14 software was used for statistical analysis (StataCorp LLC, College Station, TX, USA).
Development, and Evaluation (GRADE) [37]. The study complied with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement (Supplementary Tables S1 and S2) [38]. The study protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO, CRD42023406916).

Statistical Analysis
We generated forest plots from weighted mean differences (WMDs) to assess the De Ritis ratio in patients with non-severe disease or survivor status and patients with severe disease or non-survivor status (p < 0.05 for statistical significance). Adjusted ORs or HRs were transformed into log ORs and log HRs, and the standard error was calculated based on the corresponding 95% CI. Heterogeneity was assessed using the Q statistic (p < 0.10 for statistical significance). We used a random-effect model in case of moderatesubstantial heterogeneity (I 2 values ≥ 30%) [39]. We assessed the influence of individual studies through sensitivity analysis [40]. Publication bias was assessed with the Begg's and Egger's tests (p < 0.05 for statistical significance) and the Duval and Tweedie "trimand-fill" procedure [41][42][43]. In univariate meta-regression analysis, we investigated associations between the WMD/OR/HR and participant age, sex, study sample size, year of study publication, study design, markers of inflammation (WBC, CRP), markers of coagulation (D-dimer), and a history of diabetes, hypertension, and cardiovascular disease. In subgroup analyses, we investigated possible differences in effect size according to the clinical outcome studied (disease severity vs. mortality) and study continent. The prognostic performance of the De Ritis ratio was assessed by calculating the weighted summary AUROC using the fixed and/or random effects model [44]. Stata 14 software was used for statistical analysis (StataCorp LLC, College Station, TX, USA).

Results of Individual Studies and Syntheses
The forest plot of De Ritis ratios in patients with non-severe vs. severe disease or survivor vs. non-survivor status is shown in Figure 2. Random-effects models were used given the moderate-substantial heterogeneity observed (I 2 = 94.9%, p < 0.001). Pooled results showed that the De Ritis ratios were significantly higher in patients with severe disease or non-survivor status (WMD = 0.36, 95% CI 0.24 to 0.49, p < 0.001). The sequential removal of individual studies did not substantially alter the corresponding pooled WMD values (range 0.34-0.40).

Results of Individual Studies and Syntheses
The forest plot of De Ritis ratios in patients with non-severe vs. severe disease or survivor vs. non-survivor status is shown in Figure 2. Random-effects models were used given the moderate-substantial heterogeneity observed (I 2 = 94.9%, p < 0.001). Pooled results showed that the De Ritis ratios were significantly higher in patients with severe disease or non-survivor status (WMD = 0.36, 95% CI 0.24 to 0.49, p < 0.001). The sequential removal of individual studies did not substantially alter the corresponding pooled WMD values (range 0.34-0.40).

Publication Bias
There was no publication bias according to the Begg's (p = 1.00) or the Egger's (p = 0.25) test. Accordingly, no missing study to be added to the funnel plot was identified using the "trim-and-fill" method (Supplementary Figure S1).

Certainty of Evidence
The certainty of evidence was downgraded to very low (rating 1) as a consequence of the presence of substantial and unexplained heterogeneity.

Results of Individual Studies and Syntheses
Pooled results showed that the De Ritis ratio was significantly associated with the risk of severe disease or death (OR = 1.83, 95% CI 1.40 to 2.39, p < 0.001; Figure 3). The substantial between-study heterogeneity observed (I 2 = 65.2%, p = 0.001) warranted randomeffects models. The removal of individual studies did not markedly affect the pooled ORs, suggesting the stability of the results (range 1.68-1.96).

Publication Bias
Both the Begg's (p = 0.013) and the Egger's (p = 0.011) tests identified the presence of publication bias. The "trim-and-fill" approach led to the identification of three missing studies that were required as additions to the left side of the funnel plot in order to ensure

Publication Bias
Both the Begg's (p = 0.013) and the Egger's (p = 0.011) tests identified the presence of publication bias. The "trim-and-fill" approach led to the identification of three missing studies that were required as additions to the left side of the funnel plot in order to ensure symmetry (Supplementary Figure S4). The resulting effect size, albeit attenuated, was similar to the primary analysis (OR = 1.60, 95% CI 1.16 to 2.19, p = 0.004).

Subgroup and Meta-Regression Analysis
In meta-regression, no significant associations were observed between the OR and age

Certainty of Evidence
The certainty of evidence remained low (rating 2) after considering all relevant criteria.

Results of Individual Studies and Syntheses
The substantial between-study heterogeneity observed (I 2 = 86.1%, p = 0.001) warranted random-effects models. The De Ritis ratio was significantly higher in non-survivors than survivors (HR = 2.36, 95% CI 1.17 to 4.79, p = 0.017; Figure 4). The removal of individual studies did not substantially alter the corresponding pooled HRs, suggesting that the results were stable (range 2.24-3.04).

Publication Bias, Subgroup, and Meta-Regression Analysis
The limited number of studies precluded the assessment of publication bias and subgroup and meta-regression analyses.

Certainty of Evidence
The certainty of evidence was downgraded to extremely low (rating 0) as a consequence of the substantial and unexplained heterogeneity and the lack of assessment of publication bias. The substantial between-study heterogeneity observed (I 2 = 86.1%, p = 0.001) warranted random-effects models. The De Ritis ratio was significantly higher in nonsurvivors than survivors (HR = 2.36, 95% CI 1.17 to 4.79, p = 0.017; Figure 4). The removal of individual studies did not substantially alter the corresponding pooled HRs, suggesting that the results were stable (range 2.24-3.04).

Publication Bias, Subgroup, and Meta-Regression Analysis
The limited number of studies precluded the assessment of publication bias and subgroup and meta-regression analyses.

Certainty of Evidence
The certainty of evidence was downgraded to extremely low (rating 0) as a consequence of the substantial and unexplained heterogeneity and the lack of assessment of publication bias.

Results of Individual Studies and Syntheses
The pooled AUROC for the De Ritis ratio was 0.677 (95% CI 0.612 to 0.743, Figure 5). The elevated between-study heterogeneity observed (I 2 = 85.8%, p = 0.001) warranted random-effects models. In sensitivity analysis, the sequential removal of individual studies did not substantially alter the corresponding pooled AUROCs, suggesting that the results were stable (range 0.65-0.70). The cut-off value, sensitivity, and specificity ranges were 1.22-1.65, 0.58-0.74, and 0.56-0.82, respectively (Supplementary Table S7).

Publication Bias
Assessment of publication bias was not possible because of the relatively small number of studies.

Publication Bias
Assessment of publication bias was not possible because of the relatively small number of studies.

Discussion
In our updated systematic review and meta-analysis, the De Ritis ratio on admission was significantly higher in hospitalized COVID-19 patients with severe disease manifestation or non-survivor status when compared to patients with non-severe disease or survivor status. Such between-group differences were statistically significant regardless of whether they were expressed as WMD, OR, or HR. The capacity of the De Ritis ratio to discriminate between COVID-19 patients with different disease severity and survival status was considered satisfactory, according to a pooled AUROC of 0.677. However, the pooled AUROC was higher (0.74) when considering only studies investigating mortality. Although a moderate-substantial between-study heterogeneity was generally observed, the sequential omission of individual studies did not

Discussion
In our updated systematic review and meta-analysis, the De Ritis ratio on admission was significantly higher in hospitalized COVID-19 patients with severe disease manifestation or non-survivor status when compared to patients with non-severe disease or survivor status. Such between-group differences were statistically significant regardless of whether they were expressed as WMD, OR, or HR. The capacity of the De Ritis ratio to discriminate between COVID-19 patients with different disease severity and survival status was considered satisfactory, according to a pooled AUROC of 0.677. However, the pooled AUROC was higher (0.74) when considering only studies investigating mortality. Although a moderate-substantial between-study heterogeneity was generally observed, the sequential omission of individual studies did not substantially affect the overall WMD, OR, or HR, suggesting stability of the results. The absence of significant associations between the effect size and a range of clinical characteristics suggests that the De Ritis ratio may offer clinical information that complements, rather than duplicates, the information provided by routine clinical and biochemical parameters in COVID-19. Furthermore, the lack of significant associations between the effect size and the year of study publication indicates that the capacity of the De Ritis ratio to discriminate between patients with different disease severity and survival outcomes is not influenced by temporal changes in the characteristics of the study populations, e.g., different SARS-CoV-2 variants, vaccination type and uptake, and immunomodulatory treatments.
The potential clinical utility of the De Ritis ratio AST/ALT ratio as a biomarker was initially described in 1957 [28]. Whilst the physiological circulating concentrations of ALT and AST represent the equilibrium between hepatocyte turnover and enzyme clearance from serum, their elevations generally indicate the presence of significant hepatocellular damage or death. An increase in serum concentrations of ALT, primarily located in the cytosol of hepatocytes, generally reflects alterations in the cell membrane. By contrast, AST is present not only in the cytoplasm and the mitochondria of hepatocytes but also in the skeletal muscle, heart muscle, brain, kidneys, lungs, pancreas, erythrocytes, and leucocytes, which limits its specificity for liver damage compared to ALT [64][65][66]. The De Ritis ratio has been increasingly studied as a diagnostic and prognostic marker, particularly in acute and chronic viral hepatitis, alcoholic hepatitis, fatty liver, non-alcoholic fatty liver disease, and cirrhosis [29,67,68]. The median and interquartile physiological ranges of the De Ritis ratio have been reported to be 0.90 (0.75-1.10) in healthy females and 0.81 (0.66-1.01) in healthy males [69].
Several mechanisms may account for the onset and progression of liver damage in COVID-19 [16,[70][71][72]. For example, SARS-CoV-2 RNA and viral particles have been de-Life 2023, 13, 1324 9 of 13 tected in the liver parenchyma of patients with COVID-19 [73][74][75]. Angiotensin-converting enzyme 2, transmembrane serine protease 2, and paired basic amino acid-cleaving enzyme, critical components for the entry and invasion of host cells by SARS-CoV-2, are expressed in liver cells [76][77][78][79]. Intercellular adhesion molecule-3-grabbing integrin, a liver-specific receptor, CD147, highly expressed in inflammation and infection sites, and antibody-dependent enhancement have also been proposed to facilitate the entry of SARS-CoV-2 in liver cells [80][81][82][83]. Additional potential mechanisms responsible for liver injury in COVID-19 patients include the exposure of the liver parenchyma to high concentrations of circulating pro-inflammatory cytokines [84], the occurrence of hypoxia-reperfusion tissue injury, particularly in the presence of microvascular dysfunction and thrombosis [85], and the occurrence of drug-induced liver injury caused by potentially hepatotoxic medications such as the antiviral remdesivir and the immunomodulating agent tocilizumab [86].
Our meta-analysis provides robust evidence that relatively greater elevations in the De Ritis ratio reflect the presence of more significant structural and functional liver abnormalities, which, in turn, are associated with severe disease and mortality in patients with COVID-19. Therefore, this simply derived biochemical parameter may be particularly useful for early risk stratification and appropriate management in this group. In a systematic review and meta-analysis of eight studies in a total of 4606 patients published in 2021, the De Ritis ratio was significantly higher in COVID-19 patients with poor prognosis, defined as a composite of death, clinical severity, admission to the ICU, and intubation (mean difference = 0.41, 95% CI 0.31 to 0.50, p < 0.001). Furthermore, an elevated De Ritis ratio was significantly associated with poor prognosis (OR 3.28, 95% CI 2.39 to 4.52, p < 0.001), while the AUC was 0.67 (95% CI 0.63-0.71) [35]. Our updated systematic review and metaanalysis captured a significantly higher number of studies (n = 24), which also allowed the conduct of separate sensitivity analyses. Furthermore, we performed subgroup and meta-regression analyses to investigate potential sources of heterogeneity and associations with other variables, including the type of endpoint assessed and the geographical location.
The general moderate-substantial between-study heterogeneity represents a significant limitation of our study, although subgroup analysis identified potential sources of heterogeneity when the effect size was expressed as OR (geographical location and type of endpoint). There was also a significant publication bias in studies reporting the OR, and no assessment could be performed for studies reporting the HR and the AUROC. Furthermore, no study reported long-term, e.g., post-discharge outcomes in COVID-19 patients. By contrast, a significant strength is represented by the wide number of the study geographical locations, which supports the generalizability of our results.

Conclusions
In our updated systematic review and meta-analysis, higher De Ritis ratios on admission, indicating significant liver injury in the context of excessive systemic inflammation, have been shown to be significantly associated with severe disease and mortality in hospitalized COVID-19 patients. Prospective studies are warranted to determine whether this easily derived parameter of liver function, singly or in combination with other clinical, demographic, or biochemical parameters, can further enhance early risk stratification for short-and long-term outcomes and facilitate treatment strategies to improve clinical outcomes in this group.  Table S5: Studies reporting the association between the De Ritis ratio and disease severity and survival status in COVID-19 patients using odds ratios; Table S6: Studies reporting the association between the De Ritis ratio and disease severity and survival status in COVID-19 patients using hazard ratios; Table S7: Studies investigating the accuracy of the De Ritis ratio for disease severity or survival status in COVID-19 patients; Figure S1: Funnel plot of studies investigating disease severity and survival status after "trimming-and-filling". Dummy studies and genuine studies are represented by enclosed circles and free circles, respectively; Figure S2: Forest plot of studies examining the De Ritis ratio in patients with COVID-19 according to disease severity or survival status; Figure S3: Forest plot of studies examining the De Ritis ratio in patients with COVID-19 according to geographical area; Figure S4: Funnel plot of studies investigating the association between the De Ritis ratio and clinical outcomes by means of OR, after "trimming-and-filling"; Figure S5: Forest plot of studies examining the relationship between the De Ritis ratio and clinical outcomes by means of OR, according to measures of disease severity or mortality; Figure S6: Forest plot of studies examining the association between the De Ritis ratio and clinical outcomes by means of OR, according to geographical area; Figure S7: Forest plot of studies investigating the prognostic accuracy of the De Ritis ratio according to measures of disease severity or survival status.

Conflicts of Interest:
The authors declare no conflict of interest.