According to the findings of this study, certain hematological/biochemical markers, pre-existing conditions, and complications were associated with mortality in COVID-19 patients and should be taken into account for patient care. Furthermore, a multilevel approach based on network analysis and correlation analysis will aid in the deeper understanding of interactions within and between exposures and outcomes.
Our meta-analysis revealed that COVID-19 non- survivors had higher NEU and lower LYM counts. According to the study of Qin et al.115, lymphopenia (low LYM counts) and an increased NEU–LYM ratio were frequently observed in patients with severe COVID-19. This was also a more common characteristic in COVID-19-related death.12 Inflammatory mediators, such as IL-2 and IL-6, can cause serious lymphopenia, resulting in LYM loss.115 Qin et al.115 indicated that SARS-CoV-2 infection affects LYMs, resulting in secondary bacterial infections and an increased NEU count. Indeed, neutrophilia (NEU count > 7.5×109/L) has been linked to bacterial inflammation, cytokine storm, and hyper-inflammation116, all of which play significant pathogenetic roles in COVID-19 infection.115,117 In line with previous study, we found an increase in WBC and NEU counts, as well as a decrease in LYM in COVID-19 non-survivors.32 Therefore, changes in WBC, NEU, and LYM counts were associated with the risk of death in COVID-19 patients.
GGT and AST concentrations were found to be higher in non-survivors in this Meta-analysis. Concentrations of alanine aminotransferase (ALT), AST, and GGT have been found to be markedly greater in dead patients than in recovered patients.32,118 In a previous study119, GGT levels were shown to be elevated in COVID-19 patients. Higher GGT levels were associated with lower albumin and higher CRP, ALT, and ALP levels in the 82 COVID-19 patients who did not have chronic liver disease or an alcohol history. This elevation suggests that the liver is involved in COVID-19 patients.120 Bernal-Monterde et al reported that increased levels of GGT and ALP, as well as decreased albumin levels, were associated with increased risk of death in COVID-19.119 Indeed, viral infections that commonly affect the respiratory tract cause hypoxia.119 In patients with pandemic H1N1 influenza infection, serum levels of ALT, AST, and GGT were found to be positively correlated with hypoxia.121 These findings were consistent with our Pearson analysis, which found a strong relationship between GGT levels and respiratory failure (r = 0.91) or heart failure (r = 0.88), but not with liver failure (r = 0.14). As mentioned above, heart failure was found to be the most common complications in non-survivors. Increased ALT, AST, and GGT levels in COVID-19 patients, particularly in non-survivors, appeared to be caused by heart failure-induced hypoxia, although further research is required to understand the details.
Since meta-analysis cannot establish relationships between variables, Pearson correlation and VIF were used to determine relationships and multicollinearity among influencing factors (i.e., blood indices and pre-existing conditions). Data showed that some complications found in COVID-19 patients, such as heart failure, were correlated with pre-existing conditions (i.e., age), as well as lower PLT and LYM counts or higher GGT levels. Moreover, network analysis was used to visualize the structure of relationships between factors affecting the COVID-19 outcome. Indeed, this approach will help in explaining the relationships between variables like blood indices, pre-existing conditions and complications, as well as the relationships between these variables and the outcome, i.e., mortality and survival. Network analysis identified a link between heart failure and increased mortality in COVID-19 patients. Therefore, combining a multi-level analysis with meta-analysis would help to achieve a better understanding of the relationships between patient characteristics and outcome.
This meta-analysis found greater concentrations of GGT, BUN, and creatinine in non-survivors, indicating that SARS-CoV-2 has a clear effect on human kidneys.122 A study of 701 patients revealed that elevated serum creatinine levels on admission were associated with severity due to severe coagulation pathway abnormalities.123 Furthermore, increased urea levels had comparable, if not greater, impacts on hazard ratios. Another kidney failure marker is GGT124, which is a cell-surface enzyme that metabolizes extracellular glutathione, the primary antioxidant in mammalian cells.125 A high level of GGT is often regarded as an early and marker of oxidative stress126 and it can be a source of reactive oxygen species in the presence of iron126,127. This, in turn, may result in renal vasoconstriction, salt retention, and subsequent kidney damage.128 Abnormalities in the routine urine test performed on admission have been linked to disease progression and an increased risk of in-hospital death.129 As a result, renal abnormalities on admission revealed a greater risk of deterioration, requiring proper triaging129; further research is needed.
Current evidence indicates that complications in COVID-19 patients may be caused by the virus’s direct effect, immune-mediated inflammation or drug-induced toxicity, assuming that the majority of patients were given high doses of antibiotics, antiviral drugs, and steroids.118 The Pearson correlation revealed that some complications (e.g., heart failure) in COVID-19 patients were associated with both pre-existing conditions (such as age and cerebrovascular disease) and blood parameters (such as PLT and LYM numbers); however, it is unclear to what extent complications are exacerbated by COVID-19 infection. Zhou et al.12 found that sepsis was the most common complication, followed by respiratory failure, ARDS, and heart failure. In our meta-analysis, heart failure and septic shock were the most common complications diagnosed in dead patients. Sahu et al.130 found that COVID-19 patients who died from infection had a gradual increase in CRP levels. Li et al.131 suggested that direct viral disruption, hyper-inflammation, and hypoxemia may all contribute to cardiac injury. Serum CRP, as an inflammatory marker, has been linked to disease severity132, lung lesions133, acute kidney damage134, and cardiac injuries135 in COVID-19 patients. Our findings suggested that CRP is a potential biomarker for COVID-19 mortality, highlighting the importance of closely monitoring CRP changes.
According to the current mea-analysis, COVID-19 non-survivors had a lower PLT count as well as lower hemoglobin and albumin concentrations. Our findings corroborated the previous study that showed a decrease in the number of PLTs in non-survivors but an increase in survivors.136 Zhao et al.136 found that PLT count may dramatically reflect pathophysiological changes in COVID-19 patients, and an early decrease in PLT was associated with COVID-19 mortality. Viral infection appears to have damaged lung tissue, resulting in PLT activation, aggregation, and entrapment, which lead to thrombosis and increased PLT consumption.136 PLTs have a short life cycle (8–10 days) and very few PLTs are preserved in bone marrow;137 it may be responsive to the severity of the patient’s conditions. Furthermore, viruses may cause a decrease in PLT production as a result of megakaryocyte infection, which may contribute to megakaryocyte apoptosis.138 Therefore, PLT measurement may be beneficial in the care of COVID-19 patients, leading to a much earlier and more effective prognosis.
Liu et al.139 reported that COVID-19 patients had the most consistent decreases in hemoglobin levels. The first case of COVID-19 in the United States revealed a minor decrease in hemoglobin on day 6 of illness.30 Notably, patients with a composite outcome (i.e., ICU admission, invasive ventilation, and death) had lower hemoglobin levels.18 Inflammation caused by SARS-CoV-2 can disrupt erythropoiesis and decrease hemoglobin production. For example, IL-6 has been shown to be elevated in severe COVID-19 infection117 and disrupts hemoglobin production.140 The current meta-analysis revealed that COVID-19 non-survivors had higher levels of IL-6. Our findings suggested that lower hemoglobin levels may be attributed to higher levels of IL-6, which requires further study in COVID-19 patients.
Age, hypertension, cerebrovascular disease, and diabetes were found to be common risk factors among non-survivors in our meta-analysis. In accordance with the previous study12, we found that non-survivors were older (46.6 vs. 76.5 years) and had a greater proportion of hypertension and diabetes than survivors. ACE2 has been shown to be over-expressed in diabetic or hypertensive patient.141,142 Diabetes and hypertension are treated with ACE inhibitors and angiotensin II type-I receptor blockers, which causes an increase in ACE2 expression and infection with COVID-19.142,143 Moreover, another study found a link between cerebrovascular disease and the risk of death in COVID-19 patients144, which was consistent with our findings. SARS-CoV-2 has been shown to have neuro-invasive properties and the ability to spread from the respiratory system to the central nervous system.145 COVID-19 can also cause cerebrovascular complications as a result of inflammation, hypoxia, and diffuse intravascular coagulation.146 Therefore, pre-existing conditions, such as cerebrovascular disease, diabetes and hypertension, may contribute to a higher risk of death in COVID-19 patients. Thus, COVID-19 patients with these pre-existing conditions should be closely monitored.
We found that exposures, i.e., demographic factors (e.g., age, gender, smoking, and alcohol consumption), as well as pre-existing conditions or comorbidities, were the primary sources of heterogeneity in this study. This may be due to inconsistencies in study designs, large differences in sample size, and differences in study characteristics. In this study, we focused on a large particular subgroup (e.g., survivors or non-survivors, which included patients of various ages, genders, and pre-existing health conditions). This basically results in heterogeneity as confirmed by I2 index and multivariate meta-regression analysis. Moreover, the high heterogeneity in this meta-analysis may be explained by studies that reported either individual patient data or the mean for a cohort of patients. Other factors such as heterogeneity in survival group (which included mild to severe cases) and non-survival groups (who had various treatments) can also lead to publication bias.147 According to the QUIPS assessment, the majority of the studies used had a moderate risk of bias. The majority of the studies included in this meta-analysis lacked data on the impact of blood parameters and pre-existing conditions on comorbidities, as well as the relationship between such comorbidities and mortality. QUIPS assessment suggested that future research should consider experiments with adequate statistical power and appropriate statistical methods to address the potential interrelationships between all prognostic factors, complications, and outcomes in COVID-19 patients.
In this study, we used a multi-level approach, including meta-analysis, bivariate analysis, and network analysis, to establish potential associations between exposures (e.g., patient characteristics) and outcomes (e.g., mortality or survival). However, this meta-analysis has several limitations. We did not perform sensitivity and subgroup analyses, despite the inclusion of studies with patients at various stages of COVID-19. Moreover, the data were obtained from a variety of countries, including developed and developing nations, with varying levels of medical facilities, suggesting different management guidelines for related medical comorbidities.
In conclusion, some pre-existing conditions and biochemical/hematological indices were associated with a higher risk of death in COVID-19 patients. Also, the data showed that complications, such as heart failure and septic shock, were more common in COVID-19 non-survivors, which could be attributed to patient characteristics, emphasizing the importance of pre-screening at triage.148