Biomarkers for unfavourable outcomes prediction in COVID-19 patients: a narrative review

Introduction

Since SARS-CoV-2 was first identified, it has rapidly spread around the world, causing a pandemic (1). As of 22 November 2023, WHO reported over 772 million confirmed cases of coronavirus disease 2019 (COVID-19) and almost 7 million deaths worldwide (2). Also, COVID-19 significantly impacts the social, economic, and psychological spheres of human life (3). COVID-19 may be asymptomatic or variable symptomatic from mild symptoms such as cough, sore throat, high temperature, diarrhoea, headache, muscle or joint pain, fatigue, and loss of sense of smell and taste (4) to severe acute respiratory syndrome and multiorgan failure (5,6).

Multiple biomarkers for the prediction of severe COVID-19 and mortality have been studied. Biomarkers are important for early suspicion of unfavourable outcomes, rationalization of patient management, and assessment of response to treatment. Knowledge about biomarkers of unfavourable outcome for COVID-19 is very important for any doctor treating patients with COVID-19. We present this article in accordance with the Narrative Review reporting checklist (available at https://jeccm.amegroups.com/article/view/10.21037/jeccm-24-58/rc).

Methods

This review is aimed to summarize available data about biomarkers of unfavourable outcomes in COVID-19 patients and classify them. Literature search was performed through the scientific database PubMed and assessed literature from 2019 to March 2024. The most relevant studies and meta-analyses about biomarkers predicting COVID-19 severity and mortality were reviewed. Also, these biomarkers were classified. For further details about search method see Table 1.

Laboratory parameters predicting unfavourable outcome in COVID-19

Hematological parameters

Haemoglobin level tends to be lower in patients with severe disease (7,8). Anemia is associated with about 70% higher risk of short-term mortality in COVID-19 patients (9). Higher white blood cell count at hospital admission is associated with higher risk of death in COVID-19 (10). The immunological phenotype of severe COVID-19 is characterized by elevated neutrophil count and reduced lymphocyte count (11). Lymphopenia is associated with the disease severity and mortality (12,13). As there is reduced lymphocyte count and elevated neutrophil count in COVID-19 patients, the neutrophil-lymphocyte ratio (NLR) increases with the severity of the disease. It was found that the NLR of 9.47 is the optimal cut-off value for predicting mortality and the NLR of 5.86 is the optimal cut-off value for predicting severity (14). Thrombocytopenia is another important marker of disease severity and mortality (15). Patients with thrombocytopenia have 7-fold higher odds of mortality from COVID-19 (16). There are following proposed mechanisms of thrombocytopenia in COVID-19 patients: (I) inhibition of platelet production in bone marrow by direct injury of hematopoietic and bone marrow stromal cells or mediated by cytokine storm; (II) platelet destruction caused by increase of autoantibodies and immune complexes; (III) decrease in circulating platelet due to platelet activation, aggregation and wrapping into microthrombus (17). Also, absolute eosinopenia is found to be a predictor of severe COVID-19 and death (18). Systemic immune-inflammation index (SII) calculated based on the complete blood parameters (neutrophils × platelets/lymphocytes) is an important proinflammatory marker of systemic inflammation that can be effectively used as an independent prediction of mortality in COVID-19 patients with an optimal cut-off value of 618.8 (19). Platelet-lymphocyte ratio (PLR) is another reliable marker of severity and mortality among patients with COVID-19 (20). Mean platelet volume (MPV) and platelet distribution width (PDW) are elevated in COVID-19 patients compared to non-COVID individuals (21) and may be used as predictors of mortality (22,23). High platelet-large cell ratio is associated with mortality (24).

Inflammatory markers

COVID-19 may lead to hyperinflammatory response and ‘cytokine storm’ and tissue damage via apoptosis and pyroptosis (25). So, inflammatory markers may reflect the severity of the disease. It’s known that IL-6 is elevated in COVID-19 patients (26) and may be used as a predictor of severe COVID-19 (27) and in-hospital mortality (28). Higher C-reactive protein (CRP) levels are associated with disease progression and mortality (29). The optimal cut-off value of CRP for prediction of severe complications is 64.75 mg/dL (30). Patients with high tumour necrosis factor (TNF) and IL-23 on admission are more likely to experience a severe form of COVID-19 (31). Serum amyloid A levels are positively associated with the severe disease and mortality (32). Procalcitonin is another marker reflecting an inflammatory state that has good discriminative power for predicting mortality and disease severity in COVID-19 patients (33). Elevated procalcitonin may reflect hyperinflammatory condition (34). Erythrocyte sedimentation rate is found to be higher among those with pneumonia, requiring oxygen, and non-survivors, but its prognostic value is poor (35). Also, elevated lactate dehydrogenase is associated with a poor outcome in COVID-19 (36,37). Granulocyte-macrophage colony-stimulating factor, C-X-C motif chemokine ligand 10 (CXCL10), IL-1β, IL-8, IL-15, resistin, macrophage inflammatory protein-1α (MIP-1α) and intracellular adhesion molecule 1 (ICAM-1), monocyte chemoattractant protein 1 (MCP-1) were associated with adverse outcomes (38-43). IL-10 is an anti-inflammatory cytokine that is a reliable predictor of severity and mortality in COVID-19 patients (44). Also, a low level of amino-terminal propeptide of C-type natriuretic peptide (NT-proCNP) on hospital admission is associated with severe COVID-19 (45) and predicts the severe disease (46).

Elevated soluble IL-2 receptor (sIL-2R) level suggests a hyper-inflammatory state reflecting the severity of COVID-19 and may be used as a predictor of severity and mortality (47-49). sIL-2R are secreted by activated T-cells and their elevated levels are a marker for T-cell activity (50,51).

Transforming growth factor-β1, an important immunomodulatory and pro-fibrotic cytokine is found to be an efficient biomarker for predicting COVID-19 severity and adverse outcomes in patients with non-alcoholic fatty liver disease (52). Patients who died of severe COVID-19 have significantly higher levels of transforming growth factor-β at the disease onset and this biomarker may be used as a predictor of fatal outcomes [area under the curve (AUC), 0.75] (53).

Ferritin is one of the most important biomarkers used as a predictor of unfavourable outcomes in COVID-19 patients. According to the FerVid study, a ferritin level of >500 ng/mL is found in more than 50% of COVID-19 patients (54). Ferritin values >3,000 ng/mL are referred to hyperferritinemic syndrome and have high specificity (96%) for unfavourable outcomes (54). Ferritin levels at admission may serve as a predictor of ICU admission, the need for mechanical ventilation and in-hospital mortality (55,56). However, as ferritin level is lower in the female than in male patients with COVID-19, the optimal cut-off values are different too (57). The optimal ferritin cut-off values for mortality were 433 ng/mL in women and 740 ng/mL in men (58). To improve predictive abilities of ferritin, ferritin-hemoglobin ratio (59), ferritin-albumin ratio (60), and ferritin-lymphocyte ratio (61) were studied.

Iron metabolism

Hepcidin is an important iron-regulating protein (62) that was found to be a good biomarker in predicting the severity and mortality of COVID-19 in hospitalized (63) and ICU patients (64). Hepcidin blocks iron export from cells through ferroportin, a transmembrane protein that exports iron from duodenal enterocytes absorbing dietary iron, from iron-recycling macrophages in the spleen and the liver, and from iron-storing hepatocytes (65). Patients with COVID-19 present with lower serum iron levels that may be explained by increased iron internalization due to reduced iron export from cells via ferroportin (66). Serum iron level is an accurate predictor of hospitalization (optimal cut-off value of 6.0 µmol/L with a sensitivity of 94.7% and a specificity of 67.9%; AUC, 0.894) (67). Also, serum iron showed good predictive abilities for COVID-19 severity (optimal cut-off value, 5.26 µmol/L; sensitivity, 58.1%; specificity, 89.5%; AUC, 0.696) and mortality (optimal cut-off value, 12.54 µmol/L; sensitivity, 100.0%; specificity, 77.8%; AUC, 0.929) (68). Reduced serum transferrin levels reflect heightened inflammation in COVID-19 patients and are an important predictor of the severity and progression of the disease (69). So, COVID-19 patients present with low levels of transferrin, iron, and haemoglobin, as well as high ferritin and hepcidin levels.

Lipid and glucose profile

Low total cholesterol, high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein cholesterol levels and high triglycerides are associated with severe COVID-19 patients and mortality (70-72). To improve the predictive abilities of the lipid spectrum, triglyceride-HDL ratio (73), and monocyte-HDL ratio (74) were studied and had predictive abilities.

It’s known that both diabetes mellitus, hyperglycaemia, and elevated haemoglobin A1c levels are independently associated with adverse prognosis of COVID-19 (75-77).

Coagulation status

Often coagulation abnormalities are seen in COVID-19 patients. Causal factors of COVID-19-associated coagulopathy include inflammation, endothelial dysfunction, platelet and complement activation, renin-angiotensin-aldosterone system derangement, and hypoxemia (78). Patients with COVID-19 have higher values of thrombin-antithrombin complex, α2-plasmin inhibitor-plasmin complex, thrombomodulin, t-PA/PAI-1 complex, prothrombin time, international normalized ratio, fibrinogen, thrombin time, and D-dimer (79). Prothrombin time is found to be a predictor of the disease severity and mortality, an increase in prothrombin time is associated with worsened prognosis (80). An optimal cut-off value of prothrombin time was 16.25 seconds for severe COVID-19 (80). Also, γ′ fibrinogen is a useful inflammatory marker of COVID-19 respiratory disease severity (81). Activated partial thromboplastin time >27.1 seconds may be used as a predictor of mortality in COVID-19 patients (82). Elevated levels of Willebrand factor antigen and soluble thrombomodulin representing endotheliopathy are associated with mortality (83). Patients with a D-dimer level greater than 0.5 µg/mL have 5.78 times higher odds of severe COVID-19 (84). 1.5 µg/mL is the optimal cut-off value of D-dimer for predicting mortality in COVID-19 patients (sensitivity, 70.6%; specificity, 78.4%) (5).

Markers of organ dysfunction

In addition to pulmonary involvement, COVID-19 may impair cardiac, liver and kidney function (85). N-terminal pro-brain natriuretic peptide (NT-proBNP), the most studied marker of heart failure, is found to be an independent risk factor for in-hospital death in patients with severe COVID-19; its optimal cut-off value is 88.64 pg/mL (86). High levels of mid-regional pro-atrial natriuretic peptide (MR-proANP) at admission are associated with COVID-19 severity and appeared to be an independent prognostic marker of 28-day mortality (AUC, 0.832) (87). Patients with elevated troponin I levels have 7.92 higher odds of poor outcomes compared to patients with normal troponin levels (88). Soluble suppression of tumorigenesis-2 (sST2), a biomarker of heart failure, is a useful biomarker to predict ICU admission, ventilator use, extracorporeal membrane oxygenation use, and 30-day mortality in hospitalized COVID-19 patients (89).

Elevated creatine kinase level is found to be associated with severity of disease, even when adjusting for CRP (90). Myoglobin predicts mortality in severe/critical COVID-19 patients and is found to be superior to troponin for predictive value (91).

Elevated alanine aminotransferase, aspartate aminotransferase, alkaline phosphatase, and total bilirubin levels, as well as decreased albumin levels, are associated with unfavourable outcomes in COVID-19 patients (92).

Elevated creatinine, blood urea nitrogen, and blood urea nitrogen/creatinine ratio are associated with COVID-19 severity and lethal outcomes (93,94). Severity of COVID-19 may be predicted by blood urea nitrogen/albumin ratio (cut-off value, 6.23 mg/g; sensitivity, 79%; specificity, 54%, AUC, 0.695) (95). Serum cystatin C is a predictor of severe COVID-19; the cut-off value is 1.245 mg/L (sensitivity, 79.1%; specificity, 60.7%) (96).

Krebs von den Lungen-6 (KL-6) glycoprotein expressed on type II alveolar epithelium is found to be higher in patients with severe COVID-19 and may be used as a predictor of the severe disease representing lung injury (97,98).

Biomarkers of unfavourable outcomes in COVID-19 in clinical practice

Summarizing the data of these studies, published studies showed that COVID-19 may be accompanied by pulmonary, cardiovascular, hepatic, and renal involvement that is associated with unfavourable outcomes. Also, plenty of biomarkers representing inflammation and coagulation states, iron, lipid, and glucose metabolism, as well as haematological changes may be used as predictors of unfavourable outcomes in COVID-19 patients (Figure 1).

Figure 1 Biomarkers for unfavourable outcomes prediction in COVID-19 patients. COVID-19, coronavirus disease 2019; NLR, neutrophil-lymphocyte ratio; SII, systemic immune-inflammation index; PLR, platelet-lymphocyte ratio; MPV, mean platelet volume; PDW, platelet distribution width; PLCR, platelet-large cell ratio; CRP, C-reactive protein; sIL-2R, soluble interleukin-2 receptors; ESR, erythrocyte sedimentation rate; TNF, tumor necrosis factor; SAA, serum amyloid A; LDH, lactate dehydrogenase; GMCSF, granulocyte-macrophage colony-stimulating factor; CXCL10, C-X-C motif chemokine ligand 10; IL-1β, interleukin-1β; IL-6, interleukin-6; IL-8, interleukin-8; IL-10, interleukin-10; IL-15, interleukin-15; MIP-1α, macrophage inflammatory protein-1α; ICAM-1, intracellular adhesion molecule 1; MCP-1, monocyte chemoattractant protein 1; TGF-β1, transforming growth factor-β1; NT-proCNP, N-terminal propeptide of C-type natriuretic peptide; HDL, high-density lipoprotein; LDL, low-density lipoprotein; T-HDL ratio, triglyceride-high-density lipoprotein ratio; M-HDL ratio, monocyte-high-density lipoprotein ratio; PT, prothrombin time; INR, international normalized ratio; TATC, thrombin-antithrombin complex; APTT, activated partial thromboplastin time; α2-PIPC, α2-plasmininhibitor-plasmin complex; t-PA/PAI-1 complex, tissue plasminogen activator/plasminogen activator inhibitor-1; NT-proBNP, N-terminal propeptide of B-type natriuretic peptide; MR‐proANP, midregional pro-atrial natriuretic peptide; sST2, soluble suppression of tumorigenesis-2; ALAT, alanine aminotransferase; ASAT, aspartate aminotransferase; AP, alkaline phosphatase; TB, total bilirubin; CK, creatine kinase; BUN, blood urea nitrogen; BUN-C ratio, blood urea nitrogen/creatinine ratio; BUN-A ratio, blood urea nitrogen/albumin ratio; KL-6, Krebs von den Lungen-6 glycoprotein.

Despite the fact that multiple biomarkers of unfavourable outcomes in COVID-19 have been studied, plenty of them are expensive or unavailable in clinics. Also, predictive abilities of some biomarkers are not high enough. These factors make some laboratory parameters to be secondary for unfavourable outcomes prediction.

Considering availability, cost and predictive ability, the most relevant biomarkers in real clinical practice include CRP, ferritin, IL-6, procalcitonin, and coagulation status that should be performed in addition to routine laboratory tests. If there are symptoms, signs or any other evidence of organ dysfunction specific laboratory tests and investigations should be performed.

Conclusions

Thus, biomarkers predicting unfavourable outcomes in COVID-19 patients may be classified as haematological parameters, inflammatory markers, markers of iron metabolism, lipid and glucose profile, coagulation status, and markers of organ dysfunction. As each biomarker reflects a specific aspect of COVID-19 pathology, laboratory parameters may be used to guide the selection of an appropriate method of therapeutic intervention.

Acknowledgments

Funding: None.

Footnote

Reporting Checklist: The authors have completed the Narrative Review reporting checklist. Available at https://jeccm.amegroups.com/article/view/10.21037/jeccm-24-58/rc

Peer Review File: Available at https://jeccm.amegroups.com/article/view/10.21037/jeccm-24-58/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jeccm.amegroups.com/article/view/10.21037/jeccm-24-58/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

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