Characteristics of patients with non-severe infections of different SARS-CoV-2 omicron subvariants in China

Abstract

Objective: The aim of this study was to explore the clinical characteristics of patients infected with different Omicron subvariants presenting non-severe disease, evaluate the safety and efficacy of Azvudine for treatment of COVID-19, in order to broaden understanding of Omicron subvariant infections.

Method: A total of 244 individuals with Omicron subvariant (BA.2.76, n = 158; BA.5.1, n = 86) were included in the study. Demographic, clinical, and laboratory data of the study participants were collected and analyzed.

Result: Patients infected with BA.5.1 exhibited a higher incidence of clinical symptoms like fatigue (25.58% vs. 2.53%, p < 0.001), headache/dizziness (12.79% vs. 4.43%, p = 0.017), nausea/vomiting (10.47% vs. 1.27%, p = 0.002), viral loads and inflammatory factors, and shorter virus shedding time than those with BA.2.76. There are 28.1% patients reporting mild adverse events following Azvudine administration. After treatment, the levels of anti-SARS-CoV-2 IgG/IgM, white blood cell, and lymphocyte obviously increased, while C-reactive protein, procalcitonin, and D-dimer reduced. Azvudine speeded up the time for virus clearance compared to control treatment (10 vs. 11 days, p = 0.032). Low lymphocyte counts (odd ratio (OR) = 0.607, p = 0.001) and anti-SARS-CoV-2 IgG titer (OR = 0.990, p = 0.028) were the independent risk factors for long nucleic acid negativization duration after infection. Patients with pneumonia were often accompanied by dyspnea, fatigue and high level of D-dimer. Dyspnea (OR = 10.176, p = 0.019) could be used to identify the occurrence of pneumonia in patients infected with Omicron.

Conclusion: The study demonstrated the difference in clinical and laboratory parameters between patients infected with Omicron BA.2.76 and BA.5.1, as well as the safety and efficacy of Azvudine therapy. Our study linked patient manifestations to Omicron subvariant, treatment, and clinical outcomes, which is conducive to healthcare providers/policymakers to revise and implement appropriate countermeasures, facilitating appropriately advise for individuals with Omicron subvariant infections.

Keywords: Azvudine; BA.2.76; BA.5.1; clinical features; nucleic acid negativization; omicron subvariant; pneumonia.

Figure 1

Azvudine improved the immune and inflamatory status of patients infected with Omicron variant. (A) The time of viral clearance was shorter in Azvudine group than control group. (B,C) Azvudine treatment significantly enhanced the titers of anti-SARS-CoV-2 IgG (B) and IgM (C) compared to control treatment. (D–F) The reduction of C-reactive protein (D), procalcitonin (E), and D-dimer (F) in azvudine group was greater than that in control group. G-H. After treatment, immune cells including white blood cell counts (G), lymphocyte counts (H), and platelet (I) of patients receiving azvudine increased more than those in control group. Statistical analysis was performed by Wilcoxon test (A) and paired Wilcoxon test (B–I). FC, fold change.

Figure 2

Factor associated with virus clearance in patients infected with Omicron subvariants. (A) The heatmap showed the factors correlated with the days for nucleic acid to turn negative after infection. (B) Box plot showed the difference of virul clearancr time between Omicron infected patients with or without fever symptom. (C,D) The association between virul clearance time (days) and lymphocytes counts (C) as well as anti-SARS-CoV-2 IgG (D). (E,F) Risk factors associated with long days of nucleic acid to turn negative in model 1 (E) and model 2 (F). Lymphocytes counts and anti-SARS-CoV-2 IgG titers were evaluated before treatment.

Figure 3

Factor associated with pneumonia in patients infected with Omicron subvariants. (A,B) Proportion (orange) of fatigue (A) and dyspnea (B) symptoms in Omicron infected patients with or without pneumonia. (C) Levels of D-dimer in patients with or without pneumonia before treatment. (D,E) Risk factors related to pneumonia using univariate (D) and multivariate logistic regression (E).