key: cord-0705899-u0z8fnlj
authors: Wang, Haizhou; Zhang, Yongxi; Mo, Pingzheng; Liu, Jing; Wang, Hongling; Wang, Fan; Zhao, Qiu
title: Neutrophil to CD4+ lymphocyte ratio as a potential biomarker in predicting virus negative conversion time in COVID-19
date: 2020-06-06
journal: Int Immunopharmacol
DOI: 10.1016/j.intimp.2020.106683
sha: c76da8580ac833c752320eb8a8f234ab6e8c0c89
doc_id: 705899
cord_uid: u0z8fnlj

BACKGROUND: Since December 2019, novel coronavirus (SARS-CoV-2)-infected pneumonia (COVID-19) occurred in Wuhan, and rapidly spread throughout China. Our study aimed to evaluate the robustness of neutrophil to CD4+ lymphocyte ratio (NCD4LR) in predicting the negative conversion time (NCT) of SARS-CoV-2 in COVID-19 patients. METHODS: Univariate and multivariate analysis were conducted to evaluate the independency of NCD4LR in predicting NCT. Receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) were used to assess the diagnostic accuracy. RESULTS: Compared with low NCD4LR patients, patients with high NCD4LR had an older age; higher incidence of fever, fatigue, chest distress/breath shortness, severer disease assessment on admission; higher levels of inflammatory indicators; low levels of lymphocyte subsets, and a longer NCT. Multivariate analysis also identified NCD4LR as an independent risk factor for delayed NCT. ROC analysis showed that NCD4LR had a better performance than neutrophil to lymphocyte ratio in predicting the virus negative conversion within 2 weeks (AUC = 0.772), 3 weeks (AUC = 0.710), 4 weeks (AUC = 0.728), or 5 weeks (AUC = 0.815). CONCLUSION: This study suggests that NCD4LR is a potential and useful biomarker for predicting the virus negative conversion time in COVID-19 patients. Furthermore, due to the NCDLR value is easily calculated, it can be widely used as a clinical biomarker for disease progression and clinical outcomes in COVID-19 patients.

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Since December 2019, an outbreak of pneumonia of unknown cause occurred in Wuhan, and rapidly spread throughout China [1] . The pathogen was confirmed to be a distinct clade from the β-coronaviruses, which was officially named SARS-CoV-2, with the disease termed COVID-19. Currently, no antiviral drug demonstrated definite effects, and the main therapeutic strategy focused on symptomatic support.

During hospitalization, the negative conversion of SARS-CoV-2 was essential in the discharge criteria [2] . Therefore, it was necessary to identify factors associated with the negative conversion time (NCT) in COVID-19, which could contribute to the disease progression and clinical outcomes.

Several studies focused on the effects of impaired immunity in the deterioration of COVID-19. Our recent study found that total lymphocytes, CD4+ lymphocytes, CD8+ lymphocytes, B cells, and natural killer (NK) cells decreased in COVID-19 patients, and severe cases had a lower level than mild cases [3] . Qin et al also indicated the dysregulation of lymphocyte subsets might be highly associated with the development of COVID-19. Monitoring neutrophil to lymphocyte ratio (NLR) and lymphocyte subsets played a role in the diagnosis and treatment of COVID-19 [4] .

Importantly, CD4+ lymphocytes responded more significantly to virus surveillance than CD8+ lymphocytes [4] . However, it was still unknown on the relationship between NCT and neutrophil to CD4+ lymphocyte ratio (NCD4LR) in patients with . In this study, we aimed to clarify the characteristics of COVID-19 patients with higher NCD4LR and evaluate the robustness of NCD4LR in predicting NCT.

All consecutive patients with diagnosed COVID-19, who admitted to Zhongnan Hospital of Wuhan University from January 15 to March 2, were enrolled. Informed consent was obtained from each enrolled patient. This retrospective study was approved by the ethics committee of Zhongnan Hospital of Wuhan University (No. 2020011).

The virus nucleic acid detection kit was confirmed COVID-19 patients through detecting the RNA of SARS-CoV-2 in throat swab samples using based on the manufacturer's protocol (Shanghai BioGerm Medical Biotechnology Co.,Ltd). Then, all patients were admitted and isolated for treatment within one week after symptom onset. During the hospitalization, each patient had a swab virus test every other day.

NCT of SARS-CoV-2 was defined as the interval between symptom onset and the first of two consecutive negative virus tests.

In the severity assessment on admission, general illness was defined as mild clinical symptoms and there was no pneumonia phenotype on CT imaging. serious illness was defined if satisfying at least one of the following items: (i) breathing rate ≥30/min;

(ii) pulse oximeter oxygen saturation (SpO 2 ) ≤93% at rest; (iii) ration of partial pressure of arterial oxygen (PaO 2 ) to the fraction of inspired oxygen (FiO 2 ) ≤300mmHg (1mmHg=0.133kPa). Critical illness was defined if satisfying at least one of the following items: (i) respiratory failure occurred and received mechanical ventilation;

(ii) shock; (iii) combined with failure of other organs and received care in the intensive care unit (ICU) [2] .

Samples of EDTA anticoagulated peripheral blood (2 mL) were collected from patients with COVID-19 before initial treatment. All samples were tested within 6 hours of being obtained. Briefly, multiple-color flow cytometry was used to measure 

A COVID-19 case report form was designed to document primary data regarding demographic, clinical, and laboratory characteristics from electronic medical records.

The following information was extracted from each patient: gender, age, medical history, chief complaints and severity assessment on admission, laboratory findings, and NCT.

Categorical variables were presented as n (%). Continuous measurements were presented as mean (with standard deviation, SD) if they were normally distributed or median and interquartile range (IQR) if they were not. Nonparametric comparative test for continuous data and χ 2 test or Fisher's exact test for categorical data were used to compare variables between groups. P < 0.05 was considered statistically significant.

To identify the independent risk factors associated with NCT, univariate and multivariate logistic regression models were applied. The significant variables (P < 0.05) in the univariate analysis were selected and put into the multivariate logistic regression model by SPSS Statistics version 25.0 software. The "pROC" R package was used to conduct receiver operating characteristic (ROC) curve analysis to evaluate the diagnostic accuracy.

A total of 95 COVID-19 patients were included in this study ( Table 1 ). The mean age was 55 ± 16 years with 51 female patients (53.6%). The most common comorbidity was in the cardiovascular/cerebrovascular system (29.4%) and endocrine system (24.2%). The most common chief complaints were fever (67.4%), cough (37.8%), chest distress/breath shortness (37.8%), and fatigue (33.6%). On admission, 56 (58.9%), 15 (15.8%) , and 24 (25.2%) patients were classified into general, serious, and critical illness, respectively. During the hospitalization, 58 patients (61.1%) received corticosteroid, and 23 (24.2%) with mechanical ventilation. Additionally, the median NCT was 19 days (IQR, 11-27).

All patients were divided into two groups according to the median NCD4LR (0.012533). Compared with low NCD4LR patients, those with a higher NCD4LR had an older age (P = 0.006), higher incidence of fever (P = 0.02), fatigue (P < 0.001), chest distress/breath shortness (P < 0.001), and severer disease assessment on admission (P < 0.001). Moreover, higher NCD4LR patients were more likely to receive corticosteroid (P < 0.001) and mechanical ventilation (P < 0.001). Importantly, the higher NCD4LR group showed a relatively longer NCT (P < 0.001) ( Table 1 ).

In addition, laboratory findings showed that patients with high NCD4LR had higher levels of leukocytes (P < 0.001), neutrophils (P < 0.001), lymphocytes (P < 0.001), glutamyltranspetidase (GGT, P = 0.007), globulin (GLB, P < 0.001), creatinine kinase (P = 0.006), lactate dehydrogenase (LDH, P = 0.001), C-reactive protein (CRP, P < 0.001) and erythrocyte sedimentation rate (ESR, P < 0.001), and a lower level of albumin (ALB, P < 0.001). For lymphocyte subsets, lower levels of CD3+ (P < 0.001), CD3+CD4+ (P < 0.001), CD3+CD8+ (P < 0.001), CD19+ (P = 0.005) and CD16+CD56+ (P < 0.001) lymphocytes were observed in the higher NCR4LR group ( Table 2 ).

24 significant variables in the univariate analysis were selected to perform the multivariate analysis to identify independent risk factors associated with NCT. The results showed only chest distress/breath shortness (OR, 4.011; 95%CI, 1.333 to 9.455) and NCD4LR (OR, 2.575; 95%CI, 1.276 to 3.468) were positively correlated with NCT ( Table 3) .

To further evaluate the diagnostic accuracy of NCD4LR, ROC analysis was performed and NLR was selected as the control ratio. We found that NCD4LR had a better performance than NLR in predicting the negative conversion within 2 weeks (AUC=0.772), 3 weeks (AUC=0.710), 4 weeks (AUC = 0.728) and 5 weeks (AUC = 0.815) (Fig. 1) . Additionally, NK cells were reportedly decreased in COVID-19 patients [3, 5] .

Therefore, the CD4/CD56 ratio was used to compare with NCD4LR, and the results also found that NCD4LR had a better predictive effect on negative conversion (Fig.   S1 ). Moreover, we applied the stratified analysis for further data mining. For general patients, NCD4LR had a better performance in early (within 2 weeks) effective prediction of negative conversion (AUC = 0.774, Fig. 2a) . For critical patients, NCD4LR performed better in predicting the negative conversion within 5 weeks (AUC=0.833, Fig. 2b) . For severe patients, NCD4LR also showed a good power in predicting the negative conversion within 5 weeks (AUC=0.835), whereas the prediction performance was relatively poor within 3 (AUC=0.658) or 4 weeks (AUC=0.639) (Fig.   2c) . Thus, the predictive power of NCD4LR for negative conversion within 2 or 5 weeks was superior to that within 3 or 4 weeks.

In this study, we reported that NCD4LR played a valuable role in predicting NCT of patients with COVID-19. In addition, we observed that high NCD4LR patients were mostly elderly male with higher incidence of fever, fatigue, chest distress/breath shortness, severer disease assessment on admission and higher levels of inflammatory indicators. To the best of our knowledge, it is the first study to explore the relationship between NCD4LR and NCT in COVID-19 patients.

Currently, the therapeutic strategies of COVID-19 were mainly symptomatic and supportive treatment. The discharged criteria for COVID-19 patients were not only no abnormalities in clinical symptoms or computed tomography imaging, but also two consecutive negative results of nucleic acid test [2] . However, no published studies reported that any clinical indicators were highly associated with NCT in COVID-19 patients. Our data found that the high NCD4LR patients had a longer median NCT than that in the low NCD4LR group (24 vs. 13 days), indicating worse immune function and prolonged virus clearance. Therefore, the progression and prognosis of COVID-19 could be assessed by calculating NCD4LR value.

Moreover, recent studies reported that NLR was a promising biomarker to efficiently diagnose and predict the clinical outcomes of COVID-19 patients and was an independent risk factor for mortality in COVID-19 hospitalized patients [6, 7] . It is well-known that neutrophils and lymphocytes are important components of the innate immune system. Neutrophils secreted large amounts of cytokines and chemokines to regulate immune responses, such as antiviral defense, hematopoietic action, angiogenesis, or fibrogenesis [8] . In patients with severe viral infections, neutrophil levels were significantly elevated, inducing a cytokine/chemokine storm, which ultimately lead to lung injury and acute respiratory distress syndrome [9] .

Several studies even suggested that neutrophils should be used as a target for the treatment of severe influenza pneumonia [10] . In addition, approximately 80% of SARS patients had lymphopenia compared with healthy controls [11] . Patients with Middle East Respiratory Syndrome (MERS) also showed lymphopenia, albeit to a lesser extent than in patients with SARS [12] . Therefore, NLR was calculated as a useful indicator of inflammation during multiple diseases, such as viral infection, liver disease, and acute respiratory distress syndrome [13, 14] . However, we found that NCD4LR value was significantly more accurate than NLR value in the prediction of NCT in patients with COVID-19 ( Fig. 1 and Fig. 2 ). CD4+ lymphocytes, also known as helper T cells, played a crucial role in the detection and transmission of antigen information during viral infection. Channappanavar et al reported that approximately 90%~100% of SARS patients showed a marked decrease of CD4+ lymphocytes [11] .

Cui et al also found the incidence of CD4+ lymphocytes decreased in 100% of SARS patients, whereas CD8+ lymphocytes decreased in 87%, B cells decreased in 76%, and NK cells decrease in 55% [15] . Therefore, CD4+ lymphocytes may be the most affected cell subpopulation in lymphopenia, which also explains that NCD4LR has better predictive power than NLR.

In addition, little is known about the relationship between NCD4LR and clinical characteristics in patients with COVID-19. Thus, we divided patients into two groups based on the median NCD4LR (0.012533) as the cutoff point. Our data found that high NCD4LR patients were mostly elderly male, which was consistent with previously studies [16] . In clinical manifestations, fever was the most common symptoms, followed by fatigue, chest distress and shortness of breath and cough. The prevalence of fever (67.3%) in COVID-19 patients was relatively low in this study compared with SARS or MERS. Guan et al found that only 43.8% of patients had fever on admission, while the prevalence of fever in SARS or MERS reached almost 100% [12, 16, 17] .

Moreover, in the higher NCD4LR group, the incidence of fever was only 78.7%.

Similarly, the incidence of cough was also not high, only 37.8%. These data suggested that we should pay attention to those patients without fever and cough to avoid a missed diagnosis. In addition, the incidence of chest distress/breath shortness and fatigue and levels of inflammation indicators (e.g. CRP, ESR, and LDH) were increased significantly in the high NCD4LR group [18, 19] . This suggested that immune function of the high NCD4LR patients might be severely impacted. This view was supported by the significantly higher proportion of severe and critical patients on admission in the high NCD4LR group. Importantly, the CD4+ lymphocyte count was significantly decreased in the high NCD4LR patients than that in the low NCD4LR patients. This was consistent with the opinion of Qin et al, and further confirmed that CD4+ lymphocytes played an irreplaceable function in the immune regulation of COVID-19 patients.

There are several limitations in our research. First, this was a retrospective singlecenter study. A multi-center study may be better to test the accuracy of NCD4LR in predicting NCT. Second, only included inpatients for a certain period, the sample size is not large enough, and selection bias may occur. Third, NCD4LR value is collected and calculated on admission, not on the day of the onset of symptoms. Most patients took antipyretics before admission, which may affect the value of NCD4LR. Finally, we did not explore the dynamics of NCD4LR at different time points during the disease.

In conclusion, our study suggests that NCD4LR is a potential biomarker for predicting the virus negative conversion time in COVID-19 patients. A high NCD4LR value on admission indicates that patients are in poor conditions and are more likely to induce a longer NCT. Moreover, since NCD4LR are easily calculated from routine blood draws, it can be used widely as a simple and useful biomarker for disease progression and clinical outcomes in COVID-19 patients. NCD4LR, neutrophil to CD4+ lymphocyte ratio. COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval; NCD4LR, neutrophil to CD4+ lymphocyte ratio; AST, aspartate aminotransferase; ALT, alanine aminotransferase; ALB, albumin; GLB, globulin; GGT, glutamyltranspetidase; LDH, lactate dehydrogenase; CRP, C-reactive protein; ESR, erythrocyte sedimentation rate.

Cumulative number of reported cases of 2019 novel coronavirus pneumonia

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Lymphocyte Ratio and Mortality in Patients With Acute Respiratory Distress Syndrome: A Retrospective Cohort Study

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Author Contribution Haizhou Wang: Conceptualization; Writing -Original Draft Yongxi Zhang: Methodology; Writing -Original Draft Pingzheng Mo: Methodology; Validation Jing Liu: Writing -Original Draft; Validation Hongling Wang: Supervision Fan Wang: Writing -Review & Editing

Blood inflammatory indicators, median (IQR)

AST (15~40 U/L), median (IQR)

GLB (20~30 g/L), median (IQR)

GGT (8~57 U/L), median (IQR)

LDH (125-243 U/L), median (IQR)

Abbreviation: COVID-19

ESR, erythrocyte sedimentation rate

Highlights: 1. NCD4LR will contribute to the prediction of NCT in COVID-19 patients

Patients in the high NCD4LR group had a longer NCT

NCD4LR show better predictive value than NLR in predicting NCT

NCD4LR is a potential biomarker for clinical outcome in COVID-19 patients