Clinical Characteristics and Predictive Value of low CD4+T Count in Patients with Moderate and Severe COVID-19: A Multicenter Retrospective Study

procalcitonin.


Background
In December 2019, an outbreak of coronavirus disease 2019 (COVID-19), an acute respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in mainland China. Although the overall case fatality rate of patients with COVID-19 is relatively low [1], the number of deaths related to COVID-19 has already exceeded the sum of SARS and MERS, which has brought great harm to human beings. Moreover, the fatality rate of patients with severe COVID-19 is higher and the harm is bound to be greater [2]. Describe the patient's clinical symptoms in detail, nding markers that predict the prognosis of patients with COVID-19 are of great value.
The decline of T-lymphocytes in peripheral blood is a typical laboratory characteristic of patients with COVID-19, especially in severe patients [3,4]. A recent study recruited 21 patients with COVID-19 including 11 severe patients and 10 moderate patients. The study showed absolute number of T-lymphocytes, CD4 + T and CD8 + T cells decreased in almost all the patients, and signi cantly lower in severe patients (294.0, 177.5 and 89.0 × 10 6 /L) than moderate patients (640.5, 381.5 and 254.0 × 10 6 /L). Meanwhile, most patients did not show a decrease in B-lymphocytes count, but showed a tendency to an increased Blymphocytes count. This phenomenon suggested that SARS-CoV-2 infection may primarily affect Tlymphocytes particularly CD4 + T and CD8 + T cells [4]. T-lymphocytes play a critical role in antiviral immunity. CD4 + T lymphocyte subsets secretes high level of effector cytokines, especially interferon-γ (IFN-γ), which are essential for virus clearance [5,6]. Previous study also showed that the drastic reduction in total lymphocytes indicated the consumed immune cells and the destructed cellular immune function by coronavirus [7]. However, there are not enough studies on whether CD4 + T predicts the prognosis of COVID-19 patients.

Subjects
Medical records from 476 patients with con rmed COVID-19 were collected in Hubei General Hospital and Chongqing Three Gorges Central Hospital. Missing CD4 + T or CD + 8T data (n = 58), malignant tumor (n = 8), younger than 18 years (n = 11), eGFR ≤ 30 ml/min (n = 3), and pregnant (n = 1) were excluded. Finally, 395 patients were analyzed in this study (Fig. 1). The positive infected cases were con rmed by testing new coronavirus nucleic acid by real-time uorescent Polymerase Chain Reaction (RT-PCR). Patients with severe COVID-19 were de ned according to the New Coronavirus Pneumonia Prevention and Control Program issued by the National health commission of the People's Republic of China (5th edition).
Patients with respiratory distress (respiratory rates ≥ 30 per/min or resting oxygen saturation ≤ 93% or partial pressure of arterial oxygen (PaO2)/inspired oxygen fraction (FiO2) ≤ 300 mmHg or respiratory failure requiring mechanical ventilation, were de ned as severe COVID-19, and the remaining patients were de ned as moderate patients. CD4 + T count, CD8 + T count and lymphocyte count were divided into lower group and higher group according to the low value of laboratory reference values. The study was a multicenter, retrospective, observational registry with clinicaltrials.gov identi er NCT04292964. All study procedures were approved by the local ethics committee (approval NO. 20200701). All data were collected by experienced researchers using blinded methods.

Baseline Data And Follow-up
Demographic and clinical characteristics were collected from the electronic medical record system. Data collection of laboratory results were de ned by the results of the rst test after admission. All patients in the study were followed up from admission till death or discharge. The outcome was de ned as the inhospital death rate.

Statistical Analysis
Continuous data were expressed as mean ± standard deviation (SD) or median (interquartile range) according to the distribution. Categorical variables were presented as frequency rates with percentages.
Continuous variables with normal distribution were compared using independent group T-test; otherwise, the Mann-Whitney U test. Categorical data were tested using the Chi-square test and Fisher's exact Chisquare test. Cox proportional-hazards models were used to perform univariate analyses and multivariate analyses to identify the association between CD4 + T count and in-hospital death. Kaplan-Meier survival analysis with log-rank test was performed to estimate the cumulative survival rate of groups with higher or lower CD4 + T count. Statistical analyses were performed by the IBM SPSS Statistics 26.0 software. P (two-sided) value less than 0.05 was considered statistical signi cance.
The most frequent comorbidities were hypertension (102, 25.8%) and diabetes (47, 11.3%). The proportion of coronary heart disease, hepatitis B infection, and chronic obstructive pulmonary disease was 6.4% (25/392), 2.3% (9/392), and 1.5% (6/392), respectively.     In terms of laboratory ndings, compared with patients in higher CD4 + T group, patients in the lower CD4 + T group showed lower median lymphocyte count (0.8 (0.6-1.0) vs 1. and CD8 + T were more commonly reduced in severe patients. There was no signi cant change in the proportion of CD4 + T lower than the lower limit of normal in moderate and severe patients, but the proportion of CD4 + T lower than the lower limit of normal in moderate and severe patients accounted for 48.2% (95/197) and 50.5% (100/198), respectively. (Fig. 2A). The analysis also found that it is the CD8 + T count that re ects the severity of the patient's condition, not the CD4 + T count. (Fig. 2B).
In terms of computed tomography ndings, in moderate patients, compared with patients in the higher group, patients in the lower group more often represented as local patchy shadowing (45 [47.4%] vs 33 [32.4%], P = 0.031). Ground-glass opacity and local patchy shadowing did not differ between the two groups in the entire patient population. (Table 1).

Treatment And Clinical Outcome
In all cases, the proportion of use of oxygen inhalation, and mechanical ventilation were 84.3% (328/389), and 7.7% (30/388), respectively. The most common therapy is treatment with antiviral treatment (

Survival Curves Of In-hospital Death
Kaplan-Meier survival curves of the COVID-19 patients grouped by CD4 + T count are shown in Fig. 3. The low CD4 + T group had a higher in-hospital death rate than the high CD4 + T group during the follow-up period (log rank < 0.001). The same trend was also found in severe patients (log rank < 0.001 presenting with lower CD4 + T count was an independent risk factor for in-hospital death. Variables like age, white blood cell count and shortness of breath also showed signi cance for independently predicting in-hospital death in this study ( Table 2, Fig. 4). Similarly, Cox proportional hazards analyses was also performed on severe patients, and the results also suggested that lower CD4 + T count was an independent risk factor for in-hospital death (Supplementary table4, Supplementary table5, Supplementary Fig. 1).

Discussion
This study showed the relationship between CD4 + T count and in-hospital death in COVID-19 patients. The dominant symptoms observed in the study included fever on admission, cough, fatigue and shortness of breath. The most frequent comorbidities were hypertension and diabetes. Compared with patients with higher CD4 + T level, patients with lower CD4 + T level were older and were more frequently male. In terms of laboratory ndings, lymphocyte count, CD4 + T count, CD8 + T count were signi cantly lower in lower group.
The case in-hospital death rate was signi cant higher in patients with lower CD4 + T level than in those with higher CD4 + T level. After adjustment for potential confounding factors, the lower group remained a signi cant predictor for in-hospital death.
Previous studies have shown that CD4 + T count was reduced signi cantly in COVID-19 patients [4]. It is suggested that CD4 + T count and CD8 + T count were reduced below the lower limit of normal in the vast majority of patients with either severe or moderate, and both of them were reduced profoundly in severe patients than in moderate patients [4]. In the present study, among 395 patients with COVID-19, 49.4% patients (195/395) showed decreased CD4 + T count and the in-hospital death was markedly higher in patients with decreased CD4 + T count than in patients with normal CD4 + T count (12.8% vs 1.0%, P < 0.001). In addition, our study found that increased age and increased white blood cell count were associated with in-hospital death, which were similar with several studies. Verity, et al. estimated that the total case fatality rate increased with age, with the case fatality rate of patients < 60 years old being 0.32% (95% CI: 0.27-0.38) and the case fatality rate of patients ≥ 60 years old being 6.4% (95% CI: 5.7-7.2), possibly because they often had other chronic diseases [8]. Wang, et al. suggested that white blood cell count and neutrophil count of dead patients were higher than those of surviving patients, which may be related to cytokine storm caused by the invasion of SARS-Cov-2 [9].
Several recent studies indicated that the absolute value of lymphocytes [1,10] and T-lymphocytes [3,11] were reduced in most patients with COVID-19. It was believed that SARS-CoV-2 may act mainly on lymphocytes, especially T-lymphocytes [4,7]. At present, the potential mechanisms undergoing CD4 + T count decrease induced by SARS-CoV-2 infection is still unknown. Researchers analyzed the clinical characteristics of patients with COVID-19, consistently found that patients with COVID-19, especially those with severe COVID-19, had signi cantly higher concentrations of Interleukin-10 (IL-10), interferoninducible protein 10 (IP10), monocyte chemo-attractant protein 1 (MCP-1/CCL2), macrophage in ammatory protein-1α (MIP1A/CCL3), tumor necrosis factor alpha (TNF-α) [2]. Meanwhile, it is reported that the concentration of IL-10, Interleukin-6 (IL-6), and TNF-α were negatively correlated with total T-cell counts, CD4 + T count, and CD8 + T count, respectively; Compared with patients in the illness period, levels of IL-10, IL-6, and TNF-α in the patients in the decline stage decreased signi cantly, while the total T-cell counts, CD4 + T count, and CD8 + T count were recovered [11]. The phenomena suggested the decrease in the number of T-cells in patients with COVID-19 may be due to the negative effects of high concentrations of TNF-α, IL-6, IL-10 in serum on the survival or proliferation of T-cells [11]. In addition, Previous studies have shown that, in SARS patients, the formation of autoimmune antibodies or immune complexes induced by viral infection and the use of steroids may play an important role in lymphocytic decline [12].
This study was limited by sample size and lack of dynamic detection of CD4 + T count and CD8 + T count.
First, our study only analyzed 395 patients with COVID-19, the relatively small sample sizes may affect the statistical power. Secondly, the patients included in this study lacked dynamic measurements of CD4 + T count and CD8 + T count, which made the evaluation of the relationship between CD4 + T levels and disease changes in patients with COVID-19 incomplete.

Conclusions
In conclusion, the main ndings of the study were that it is the CD8 + T count, not the CD4 + T count, that re ected the severity of the patient's disease; And, the high prognostic value of decreased CD4 + T count in patients with COVID-19. Lower CD + 4T count is independently associated with increased in-hospital death.
Thus, in this acute-care setting, CD + 4T count can provide early prognostic information in patients with COVID-19.

Declarations
Ethics approval and consent to participate: All study procedures were approved by the local ethics committee (approval NO. 20200701). All subjects were well informed.
Consent for publication: All authors have read and approved the nal manuscript.
Availability of data and materials: The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.   Forest plots of multivariate Cox proportional-hazards regression analyzing the effect of baseline variables on in-hospital death. Mode1: adjusted sex, age and temperature; Mode2: adjusted hypertension, diabetes and shortness of breath; Mode3: adjusted white blood cell count, platelet count and Creatinine; Mode4: adjusted hypersensitive C-reactive protein, procalcitonin and D-dimer; Mode5: adjusted CD8+T group, CD4/CD8 ratio and lymphocyte count group; Mode6: adjusted age, hypertension, shortness of breath, white blood cell count, platelet count, D-dimer and CD4/CD8 ratio.