Do the Kinetics of Antibody Responses Predict Clinical Outcome in Hospitalized Patients With Moderate-to-Severe COVID-19?

Abstract

Background/Aim: The relationship between the kinetics of antibody responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and the severity of Coronavirus Disease 2019 (COVID-19) is poorly understood. The aim of the present study was to investigate whether serum SARS-CoV-2 antibody kinetics serve as an early predictor of clinical deterioration or recovery in hospitalized patients with COVID-19.

Patients and Methods: In this prospective observational study, 102 consecutive patients (median age: 60 years, 58% males) with symptomatic COVID-19 infection diagnosed by real-time polymerase chain reaction assay, hospitalized in two tertiary hospitals, were included. Rapid test for qualitative detection of immunoglobulin M (IgM) and immunoglobulin G (IgG) SARS-CoV-2 antibodies was performed at pre-defined time intervals during hospitalization (days: 0, 3, 7, 10, 14, 21 and 28).

Results: During a 3-month follow-up period after COVID-19 disease onset, a total of 87 patients were discharged, 12 patients were intubated and entered the Intensive Care Unit, and three patients died. The median time for seroconversion was 10 days for IgM and 12 days for IgG post onset of symptoms. Univariate logistic regression analysis found no associations between IgM or IgG positivity and clinical outcomes or complications during hospitalization for COVID-19 infection. Diabetes and dyslipidemia were the only clinical risk factors predictive of COVID-19-related complications during hospitalization.

Conclusion: SARS-CoV-2 antibody responses do not predict clinical outcome in hospitalized patients with moderate-to-severe COVID-19 infection.

Coronavirus Disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major health problem with global dimensions. At the clinical level, SARS-CoV-2 infection can cause variable clinical syndromes ranging from asymptomatic or mild flu-like symptoms to severe acute respiratory distress syndrome (ARDS) and multiple organ failure (1). The maturation of the immune response to the virus typically requires 40 days, with variations in the dynamics of antibody production, which depend on the severity of disease and other factors that are still under investigation (2). Seroconversion is typically observed within the first 3 weeks post onset of symptoms, with a median time of 10 days for total antibodies, 10-12 days for immunoglobulin M (IgM) antibodies and 12-14 days for immunoglobulin G (IgG) (3-6). Whether the existence of IgM and IgG antibodies represents protective immunity in patients with COVID-19 is still unclear. According to some researchers, antibodies may enhance infectivity as higher antibody titers have been observed in patients with severe COVID-19 rather than in patients with non-severe disease (4,7-9). Therefore, the role of the immune response in both the pathogenesis and the course of COVID-19 infection needs further studies as it remains unclear.

Thus, the aim of the present study was to investigate whether serum SARS-CoV-2 antibody kinetics might serve as an early predictor of clinical deterioration or recovery in hospitalized patients with moderate-to-severe COVID-19 infection.

Patients and Methods

In this prospective observational study, 102 consecutive patients with symptomatic COVID-19 infection diagnosed by nucleic acid real-time polymerase chain reaction (RT-PCR) assay, hospitalized in two Greek tertiary hospitals were included. Recruitment took place between November 2, 2020, and April 20, 2021. Each patient was subsequently followed-up for at least 3 months from COVID-19 onset or until death for non-survivors. All patients fulfilled one or more criteria for hospitalization, namely respiratory failure requiring oxygen therapy, unilaterally extensive or multiple or bilateral pulmonary infiltrates on x-ray imaging/chest computed tomography, and single or multiple organ failure. RT-PCR test in oro- or naso-pharyngeal specimens (GeneXpert assay, Cepheid, Sunnyvale, CA USA) and rapid test for qualitative detection of IgM/IgG SARS-CoV-2 antibodies (BioMedomics, Inc., Morrisville, NC, USA) (10) was performed for each patient at predefined time intervals during hospitalization (days: 0, 3, 7, 10, 14, 21 and 28). During a 3-month follow-up, data regarding clinical outcome (defined as discharge, intubation, or death), and significant alterations in laboratory findings were also collected. Exclusion criteria were pre-existing end-stage failure in one or more organs, hematological malignancies, advanced solid malignancies and receiving immunosuppressive therapy (corticosteroids, chemotherapy, or biological agents).

The study protocol was approved by the two Institutional Ethics Committees (approval numbers: 17941 and 55944, respectively) and was performed in accordance with the ethical standards of the World Medical Association Declaration of Helsinki. All participants or their legal representatives gave their written informed consent prior to participation.

The analyses were performed using the Statistical Package for Social Sciences 22.0 for Windows (IBM, Armonk, NY, USA). Data are presented as median with interquartile range (first quartile-third quartile). Logistic regression analysis was used to investigate the associations of IgM and IgG SARS-CoV-2 antibodies and co-morbidities with clinical outcomes (discharge, intubation, and death) and complications during hospitalization and their corresponding odds ratios and 95% confidence intervals were calculated. A p-value less than 0.05 was considered to indicate statistical significance.

Results

Table I summarizes the demographic and clinical characteristics of the COVID-19 study population. A total of 102 hospitalized patients were recruited, of whom 59 (58%) were males. The patients had a median age of 60 years [interquartile range (IQR)=48-70 years]. One or more co-morbidities were recorded in 79 (78%) patients, whereas 38 (37%) patients had three or more co-morbidities with hypertension (40%) and dyslipidemia (33%) being the most frequent. The median time from the onset of clinical symptoms to hospital admission was 8 days (IQR=6-10 days). The median duration of hospitalization was 9 days (IQR=6-11) days, whereas the median time from symptom onset to a negative RT-PCR result for the naso-pharyngeal swab was 17.5 days (IQR=15-19 days). During hospital stay, the most common complications were pneumonia (90%) and acute respiratory distress syndrome (12%). In regard to clinical outcomes, 87 patients were discharged, 12 patients were intubated and entered the Intensive Care Unit (ICU), and three patients died (Table I).

Table I. Demographic and clinical characteristics of the COVID-19 study population (n=102).

ACEi: Angiotensin-converting enzyme inhibitors; AKI: acute kidney injury; ARB: angiotensin receptor blockers; ARDS: acute respiratory distress syndrome; CAD: coronary artery disease; CCB: calcium channel blockers; CKD: chronic kidney disease; COPD: chronic obstructive pulmonary disease; IQR: interquartile range.

A total of 54 (53%) and 88 (86%) patients had detectable levels of IgM and IgG antibodies, respectively, in their in-hospital sample. The median time for seroconversion was 10 days (IQR=8-13 days) for IgM and 12 days (IQR=10-14 days) for IgG post onset of clinical symptoms. Using the abovementioned median times for seroconversion as cutoffs, IgM and IgG positivity was not correlated with clinical outcome (discharge, intubation, or death) or any complication, including pneumonia, acute respiratory distress syndrome, acute kidney injury and cardiovascular or neurological complications, in hospitalized patients with moderate-to-severe COVID-19 infection (Table II). On the other hand, among clinical risk factors, diabetes and dyslipidemia were predictors of experiencing a complication during hospitalization (odds ratio=3.600, 95% confidence interval=1.226-10.567, p=0.02 and odds ratio=2.714, 95% confidence interval=1.157-6.368, p=0.022, respectively; Table II).

Table II. Univariate logistic regression analysis demonstrating the associations between worse clinical outcome (intubation or death), any complication, IgM and IgG SARS-CoV-2 antibodies and co-morbidities.

CAD: Coronary artery disease; CKD: chronic kidney disease; CI: confidence interval; COPD: chronic obstructive pulmonary disease. *Using a cutoff of 10 days for IgM and 12 days for IgG. Statistically significant p-values are shown in bold.

Discussion

The present study demonstrated that positive IgM and IgG SARS-CoV-2 antibodies do not predict clinical deterioration or recovery in hospitalized patients with moderate-to-severe COVID-19 infection. Furthermore, diabetes and dyslipidemia were associated with an increased incidence of COVID-19-related complications during the disease course, suggesting the detrimental impact of metabolic syndrome on the prognosis of COVID-19.

Several studies have pointed to the alleged association of SARS-CoV-2 neutralizing antibodies and COVID-19 severity (11-14). In addition, Kurano et al. suggest the possible usefulness of SARS-CoV-2 antibody testing in the early phase of disease to identify non-vaccinated patients with COVID-19 who would require high-flow oxygen therapy or mechanical ventilation (15). Interestingly, in a recent study, high anti-receptor-binding domain IgG neutralization potency was shown to be a predictor of survival in patients with severe COVID-19 infection (16). Moreover, data indicate that COVID-19 mortality is not associated with the cross-sectional SARS-CoV-2 antibody titers per se but rather, with the delayed kinetics of neutralizing antibody production (17). However, the abovementioned studies present significant heterogeneity in their categorization of disease severity, the timing of serum collection and methods for the detection and quantitation SARS-CoV-2 antibodies. On the other hand, Gozalbo-Rovira et al. failed to find differences in SARS-CoV-2 antibody titers within the first month after the onset of clinical symptoms between ICU and non-ICU patients who were matched for age, sex, and co-morbidities (18). In addition, they observed weak or very weak associations between antibody levels and inflammatory biomarkers such as C-reactive protein and interleukin-6. In line with the above data, the current study did not demonstrate association between IgM and IgG SARS-CoV-2 antibodies and clinical outcomes of patients with COVID-19.

Many studies have showed that diabetes is one of the most important underlying co-morbidities in patients with COVID-19 and is linked to severity and mortality in these patients (19-22). Consistent with this, the data of the current study demonstrated a significant statistical association between diabetes in patients with COVID-19 and a higher incidence of complications. Moreover, in a meta-analysis, dyslipidemia was correlated with increased severity and mortality of COVID-19 infection (23). Indeed, in the present study, dyslipidemia was associated with the presence of complications during hospitalization. Overall, metabolic syndrome seems to be a prognostic indicator for severe disease outcomes in patients with COVID-19, since mortality and ICU admissions are significantly increased in patients with metabolic syndrome compared with those without it (24).

In conclusion, in the present study SARS-CoV-2 antibody responses did not predict clinical outcome in hospitalized patients with moderate-to-severe COVID-19 infection. Additionally, diabetes and dyslipidemia were associated with the presence of COVID-19-related complications during hospitalization. Further large-scale and well-powered studies are required to answer the question about the role of antibodies in patient survival.

Conflicts of Interest

The Authors report no conflicts of interest.

Authors’ Contributions

Conceptualization, study design, data collection and analysis, writing manuscript: GP, CFK and IP. Study enrollment and data collection: GP, AP, CM, EK, HK, AK, EP and SS. Article review and editing, supervision: MP, DV and KG. All Authors critically revised and approved the final version of the article.