COVID-19 is a novel infectious disease that has led to a worldwide pandemic. According to the report from the Chinese Centers for Disease Control and Prevention, the mortality rate of COVID-19 is 2.3%; however, this figure increased to 49.0% among critical cases. Thus, it is of great significance to study the laboratory data and clinical development of the disease to guide management.
In this study, the clinical manifestations and laboratory data of the ICU and non-ICU patients with COVID-19 were compared. In addition, the characteristics of lymphocyte subsets and cytokine profiles of peripheral blood in the enrolled patients were analyzed. It was found that most of the ICU patients were older than the non-ICU patients. In addition, the ICU group had more patients with basic diseases than the non-ICU group; this indicates that older patients, in particular those with basic diseases, such as hypertension and diabetes mellitus, may be more likely to develop severe COVID-19. These findings are consistent with several previous studies [12, 18, 19]. Fever, cough, and expectoration were found to be the most common symptoms. However, the above symptoms did not appear in some patients. In addition, some patients only had symptoms in the digestive system or nervous system.
Cellular immunity is an important part of the human immune system in a viral infection. Increasing evidence suggests that lymphocytes play a crucial role in airway diseases [20, 21]. Marked lymphocytopenia occurred in most patients during the acute phase of SARS and Middle East respiratory syndrome (MERS), with CD4+ and CD8+ T cells particularly affected. In addition, the degree of decrease in the T lymphocytes was associated with disease severity [22–24]. However, the mechanisms by which the viruses cause lymphocyte changes are different. In COVID-19, a growing number of studies have found that lymphocytopenia, particularly in T lymphocyte subsets, is common, especially in severe/critical cases [16, 18, 25–27], while results concerning CD19+ B and NK cells are inconsistent . In this study, lymphocytopenia occurred in 96.2% of the ICU patients and in 84.5% of the non-ICU patients. Specifically, the number of CD3+ T cells, CD4+ T cells, and CD8+ T cells was significantly lower in the ICU group than the non-ICU group. While CD8+ T cells are vital for the elimination of virus-infected cells as a result of the secretion of perforins, granzymes, and interferons, CD4+ T cells participate via co-stimulating CD8+ T cells and CD19+ B cells . CD4+ T and CD8+ T cells have been reported as powerful predictors of COVID-19 severity and clinical outcome in different studies, respectively [13, 15, 29]; however, there were no significant differences between the two T lymphocyte subsets in our study. The CD4+/CD8+ T cell ratio in the non-ICU group and the ICU group were similar, which may indicate that CD4+ T and CD8+ T cells were equally reduced in both groups . CD3+ T cells are composed of CD4 + and CD8+ T cells, and CD3+ T cells may be a more reasonable and valuable parameter for severe disease and death. Differences in immune profiles can help better understand the pathogenesis and clinical expression of COVID-19 . Currently, the pathophysiological mechanism of lymphocyte reduction in patients with COVID-19 remains unclear and further investigations are required.
Early studies have documented that cytokine storms, also known as inflammatory storms, have occurred in a large number of patients with COVID-19. In patients with SARS, an increased number of proinflammatory cytokines in the serum, such as IL-1β, IL-6, IL-12, IFN-γ, IFN-γ-inducible protein-10, and C-C motif chemokine ligand 2, was observed and was considered to be related to pulmonary inflammation, extensive lung damage, and even multiple organ failure . A previous study showed that patients with MERS also had increased concentrations of proinflammatory cytokines (IFN-γ, TNF-α, IL-15, and IL-17) . Recent data have indicated that patients with COVID-19 also had high concentrations of serum cytokine profiles, such as TNF-α, IL-1, IL-6, and IFN-γ[12, 18]. In clinical work, it was found that the course of disease and lung lesions progressed rapidly, and that multiple organ failure developed over a short time in some patients with a high concentration of cytokines. In this study, it was noted that patients typically had increased concentrations of serum IL-6. Moreover, the serum IL-6 concentration was significantly higher in the ICU patients than in the non-ICU patients, which is in agreement with the concept of a cytokine storm . However, IL-4, IL-10, IL-17, TNF-α, and IFN-γ were all nearly in the normal range. Although the exact mechanism of changes in cytokines remains to be elucidated, a higher concentration of serum cytokines seems to be associated with poor outcomes. Therefore, monitoring the changes in cytokines is of a certain significance for the early detection and management of critically ill patients.
For patients with COVID-19, it is important to determine who has inherent susceptibility to develop severe or even critical disease. Monitoring COVID-19 severity is helpful in clinical decision making . Early screening of critically ill patients may improve clinical outcomes. Searching for potential predictors of the severity of disease and disease outcome could help us to identify patients requiring special care, i.e., early ICU admission, intense monitoring, and more aggressive therapy .
In this study, the clinical and laboratory features of patients with COVID-19 were explored. The enrolled patients were divided into two cohorts based on disease severity. Baseline characteristics, clinical presentation, and laboratory data were compared between the ICU and non-ICU groups. Multivariate logistic regression analysis and ROC curve analysis were further performed. In addition, AUC and cutoff values were calculated. It was found that age, diabetes mellitus, CD3+ T cells < 510.5 × 106/L at hospital admission, and IL-6 > 6.58 pg/mL at hospital admission were the predictive factors for the development of severe disease. ROC curve analysis showed that the AUC of CD3+ T cells and that of IL-6 were 0.806 and 0.785, respectively, and the AUC of combined predictor (combining age, diabetes mellitus, CD3+ T cell count reduction, and IL-6 elevation) was 0.887.
Among the 53 patients in the ICU group, 33 patients were admitted straight to the ICU due to the severity of their condition, while the remaining 20 patients were admitted to general isolation ward and then transferred to the ICU following deterioration of the disease. The value of lymphocyte subsets and cytokines in predicting severe conditions is in the identification of patients with less severe disease at hospital admission. We found that there was no significant difference in any of the indicators of lymphocyte subsets and cytokines between the direct-ICU group and the late-ICU group at hospital admission. For the late-ICU group, there was no significant difference in the lymphocyte subsets and cytokines from hospital admission to ICU admission, but the lymphocyte subsets showed a downward trend with disease progression. This finding also confirmed the value of lymphocyte subsets and cytokines in predicting severe illness at hospital admission. We also compared the changes in lymphocyte subsets and cytokines at hospital admission and ICU admission between severe and critical patients, and found no significant difference in all indicators.
In summary, the characteristics of lymphocyte subsets and cytokine profiles between ICU and non-ICU patients with COVID-19 were compared in this study. As a result, predictive factors for patients developing a severe condition were identified. This is helpful to identify high-risk patients as early as possible, which allows intensive monitoring and treatment to be provided at an early stage, and ultimately reduces the mortality associated with COVID-19.
This study has several potential limitations. First, the retrospective single-center design leads to missing data and unavoidable biases. However, the researchers responsible for data collection were trained before the study began so that they could correctly fill out the case report forms and reduce errors. In addition, two researchers collected data independently and checked each other’s forms for mistakes so as to minimize the bias as much as possible. Second, data were not collected continuously during the patients’ hospitalization, and, consequently, the trend of these clinical and laboratory indicators could not be described. Fortunately, all of the data were recorded in our electronic medical record system, and we plan to extract and collect parameters required for further study in the future.