Characteristics of Peripheral Blood Cells in COVID-19 Patients Revealed by a Retrospective Cohort Study

Background Peripheral hematological changes in severe COVID-19 patients may reect the immune reaction during SARS-CoV-2 infection. Characteristics of peripheral blood cells as early signals were needed to be investigated for clarifying its associations with the fatal outcomes in COVID-19 patients. Methods A retrospective cohort study was performed and the hospitalized COVID-19 patients were recruited in Characteristics of peripheral blood cells in survivors and non-survivors were analyzed. Also the comparison among patients with different level of eosinophils was performed. Results

However, in severe cases, uncontrolled in ammation and the microcirculation dysfunctions together lead to viral sepsis with immunologic impairment [4]. The severity of disease was associated with immunological impairment. Especially, in some life-threaten cases, SARS-CoV-2 could trigger catastrophic damage to the human immune system resulting in death at their worst.
Unfortunately, our understanding of immune response to SARS-CoV-2 is extremely limited until now.
Many scholars speculated that the interaction of SARS-CoV-2 and host could be referring to the other coronavirus because of the highly similarity in the sequence homology in coronavirus family [5]. Previous study mainly focused on the immune dysfunction caused by severe acute respiratory syndrome coronavirus (SARS-CoV) and middle east respiratory syndrome coronavirus (MERS-CoV), respectively. Coronavirus infections (SARS and MERS) are confirmed to activate both innate and adaptive immune responses, which included that lymphopenia and thrombocytopenia caused by SARS-CoV due to immune complexes and T cells' apoptosis through extrinsic and intrinsic pathways triggered by MERS-CoV [6,7].
In simply means that the changes of peripheral blood cells could re ect the immune damage caused by virus infection.
Lymphocytes play a crucial role in maintaining immune homeostasis during virus infection, especially SARS-CoV-2 [8]. Several cohort studies have reported lymphopenia can predict prognosis in COVID-19 patients [9,10]. In addition, a few studies found that the eosinopenia was associated with poor prognostic features. Thus, the differentiation of peripheral blood cells may indicate the immunologic impairment at the early stage of the disease. However, the risk factors for the changes of peripheral blood cells in the prognosis are not well addressed yet. A retrospective cohort study predicted the value of peripheral blood cells in COVID-19 patients was performed for further investigation. The clinical data, including demographics information; clinical symptoms and signs; underlying diseases; laboratory results; the most intense level of oxygen support; treatment and clinical outcomes, were extracted from electronic medical records. The whole laboratory evaluation was consisted of complete blood cell counts, biochemical and coagulation indices and so forth. The differential peripheral blood indices were detailed recorded. The baseline data were recorded in the rst 24 hours after admission. The end point was written of discharging from hospital or death. The differences in clinical characteristics and laboratory findings in patients with different outcome would be addressed. Longitudinal tracing of laboratory indices during the hospitalization was performed. Furthermore, independent predicting factors associated with the fatal outcome would also be investigated. All the data were entered into a computerized database and checked by two experienced physicians independently.

Statistical analysis
Continuous variables were described using median and interquartile range (IQR). Categorical variables were described as number (%). Non-normal distributed continuous data were compared using Mann-Whitney-Wilcoxon test. Categorical data were compared using X 2 test or the Fisher exact test. Correlations between variables were analyzed using the Spearman's rank correlation. Correlation strength was selected by an absolute correlation |r| > 0.2 and the selected correlation were plotted as an undirected network graph. All tests were 2-sides, and a P value <0.05 was considered statistically signi cant. Data was analyzed using IBM SPSS Statistics software (version 19.0).

Demographic information of survivors and non-survivors
A total of 198 patients con rmed severe COVID-19 were enrolled in this study. The median age of patients and the gender distribution between two groups (survivor group and non-survivor group) was basically the same. Majority of the included patients in both two groups were with comorbidity and more than half of the patients had at least one underlying disease. The ranking of the underlying disease was hypertension (40.0%), diabetes (16.7%), chronic respiratory disease (5.7%), cardiovascular disease (5.2%) and so on. Among the underlying disease, the percentage of malignant disease of patients in the nonsurvivor group is higher than it in the other group. The most common symptoms on admission were fever and cough, followed by fatigue and sputum production in both two groups. During the clinical treatment, the most intense level of oxygen support was recorded. Patients in survivor group were mostly under oxygen therapy by nasal cannula in survivors compared to patients in non-survivor group (47% vs 0, P <0.05). The proportion of patients under invasive ventilation (IMV) in non-survivors was signi cantly higher than that in the other group (53.8% vs 2.2%, P <0.05). More than 70% of the patients received antivirals, and Lopinavir/Ritonavir use differed signi cantly between non-survivors and survivors (6.7% vs 100.0%, P <0.05). According to the CURB-65 score, the proportion of patients with different grade showed signi cant differences between two groups. Systematic glucocorticoids use differed signi cantly between non-survivors and survivors (66.7% vs 22.5%, P=0.002). At the end of the observing period, 185 (93.4%) patients had been discharged and 13 (6.6%) patients had died. Demographic information showed in Table 1.
Regarding the coagulation parameters, the prolonging of PT and increased levels of D-dimer were significantly higher in non-survivors compared to survivors (Table 2; Figure 1).

Effects on clinical characteristics of different EOS levels in COVID-19 patients
According to the level of circulating EOS counts, COVID-19 patients were divided into two groups: low EOS group (< 0.02×10 9 /L) and normal EOS group (≥ 0.02×10 9 /L). The media age and gender distribution between the two groups without signi cant differences  Patients who received glucocorticoids therapy showed a negative correlation between the counts of WBC and LYM (r =-0.265), but a positive correlation between WBC and LYM was observed in patients without glucocorticoids therapy (r =0.531). After glucocorticoids treatment, the counts of EOS negatively correlated with NEU (r =-0.288), but no correlation was observed before the treatment (r = 0.058). A similar correlation was observed between the counts of LYM and EOS in patients received glucocorticoids therapy (r =0.454), but no correlation was found before the treatment (r =0.020) (Figure 3).

Discussion
As the classi cation of survivors and non-survivors was observed in this cohort study, the differential features of peripheral hematologic cells were analyzed. Previous study demonstrated that severe patients tend to have lower lymphocytes counts, higher leukocytes counts and neutrophil-lymphocyte-ratio (NLR), as well as lymphopenia has been reported as a predictor of prognosis in COVID-19 patients [9,11,12].
Our data also revealed that the initial counts of lymphocytes, eosinophils, and basophils of COVID-19 patients were much more decreased in non-survivors compared with the counts of above indices in survivors, which with the consistent conclusion with other studies.
Eosinophils are linked to immune response conferring host protection against viruses and eosinopenia has been observed in different acute in ammation situation as pneumonia [13][14][15]. A recent report by Xie et al proved that COVID-19 patients with low EOS counts were likely to have more severe symptoms such as fever, fatigue, shortness of breath, more lesions in chest CT, radiographic aggravation, longer length of hospital stay and course of disease [16]. Our study also indicated that patients with low EOS on admission showed a signi cantly higher fever. Eosinopenia may be the result of rapid sequestration of circulating eosinophils mediated by the overwhelming release of in ammatory cytokines, including thermogenic ones (such as IL-1, IL-6) [17]. In addition, effects of glucocorticoids on hematological and immunological indicators were signi cant especially the decrease in counts of eosinophils.
Although our understanding of the speci c innate and adaptive immune response to SARS-CoV-2 is relatively limited, the hematological changes may re ect a homeostatic mechanism to prevent systemic over-activation of in ammation. SARS-CoV-2 RNA and proteins interact with various pattern recognition receptors can initiate antiviral immune responses which characterized by differentiation and proliferation of various immune cells with immune mediator production and release, especially lymphocytopenia and elevated level of IL-1β, IFN-γ, IP-10 and IL-17, regulating viral replication and spreading within the host [18,19]. SARS-CoV-2 has been proven to induce remodeling of peripheral lymphocytes, and a more robust humoral immune response occurs in severe infection [20]. The decreased production, apoptosis and redistribution of lymphocytes may together lead to circulating lymphopenia [21]. In addition, eosinophils are recruited from the blood circulation into the in ammatory focus, modulating immune responses through releasing a serious of cytokines and other mediators, as well as by a broad spectrum of immune mechanisms [22]. In short, uncontrolled SARS-CoV-2 infection and the immune response may cause a systemic destruction, while the changes of peripheral blood cells can serve as early signals of immune impairment in COVID-19 patients [23].
Glucocorticoids can avoid excessive in ammation by inhibiting immune response to SARS-Cov-2 infection, while the suppression of immunity may lead to an increase in viral load [24]. Besides, glucocorticoids can suppress the release of EOS in bone marrow and promote eosinophil clearance by directly inducing apoptosis [25,26]. The panel of WHO made a strong recommendation for use of glucocorticoids in severe and critical COVID-19 patients, and in a real-life clinical setting, physicians tend to use glucocorticoids in most critically patients [27]. In this cohort, we proved that the use of glucocorticoids altered the immunological characteristics of peripheral blood cells and glucocorticoidrelated EOS decreased, which was considered as a risk factor for fatal outcomes. Due to the role of glucocorticoids in treating severe COVID-19 patients is still controversial, blood immunological marker which could be used as an index to guide the strategy of glucocorticoids therapy in COVID-19 patients is needed and may improve the prognosis in the clinical practice.
Early identi cation of risk factors for critical illness can facilitate appropriate provision of supportive care and help reduce mortality. Blood routine seems like a convenient and effective indicator which can help to identify the entities involved in immune dysregulation. Lymphopenia and eosinopenia on admission may be particularly important to indicate the poor prognosis of COVID-19 patients, and counts of eosinophils are of guiding signi cance for the use of glucocorticoids. In conclusion, peripheral blood cells may serve as early signals of disease progression, which can be chosen as effective monitor parameters during the treatment of COVID-19.

Consent for publication
Not applicable.

Availability of data and materials
All the data from electronic medical records in Tongji Hospital were reviewed by experienced physicians separately and checked by 2 physicians independently.

Competing interests
The authors declare that they have no competing interests.     A similar correlation was observed between the counts of LYM and EOS in patients received glucocorticoids therapy (r =0.454), but no correlation was found before the treatment (r =0.020) ( Figure  3).