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Table of Contents
ORIGINAL ARTICLE
Year : 2021  |  Volume : 9  |  Issue : 4  |  Page : 215-220

Association of neutrophil-lymphocyte ratio with clinical outcome of COVID-19 patients: A prospective study


Department of General Medicine, Bangalore Medical College, Bengaluru, Karnataka, India

Date of Submission04-Apr-2021
Date of Decision24-May-2021
Date of Acceptance31-May-2021
Date of Web Publication20-Oct-2021

Correspondence Address:
Dr. Avinash Hanbe Rajanna
Department of General Medicine, Bangalore Medical College, Bengaluru, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ajim.ajim_43_21

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  Abstract 


Aim: This study aims to find the association of neutrophil-lymphocyte ratio (N-L ratio) of COVID-19 patients admitted in an Indian setting with clinical profile and disease outcomes. Background: The COVID-19 pandemic hit in early 2020 with the presentation of varied severity of acute respiratory illness. This study tries to use N-L ratio as a predictor of adverse outcome. Methodology: The prospective single-center study considered adults patients of both the gender, diagnosed with COVID-19 infection by reverse transcription-polymerase chain reaction technique. Necessary demographic and clinical data were collected, and selected subjects were followed up until discharge or death. Individuals were classified as those who survived and those who succumbed to death. t-test was used for comparing continuous variables and Chi-square test for categorical data for comparing different parameters between the groups. Results: The study included 1977 patients with a male:female ratio of 1:0.62. Fever, dyspnea, and cough were noted as the major symptoms prevalent among patients who succumbed to death when compared to those who survived (P < 0.00001). Statistically significant variables noted between the groups were age, total leukocytes count (TLC), neutrophil, lymphocytes, all the comorbidity variables, and the asymptomatic status. Variables identified as significant predictors of disease outcomes were TLC, neutrophils, lymphocytes, and N-L ratio. Most of the subjects belonging to the mortality group required oxygen and other intensive care unit facilities when compared to the survival group (P < 0.00001). Conclusion: TLC, neutrophils, lymphocytes, and N-L ratio are noted as significant predictors of COVID-19 outcome. The mean days of viral clearance noted in COVID subjects is around 8.98 ± 3.54 days.

Keywords: COVID-19, India, infection, neutrophil-lymphocyte ratio


How to cite this article:
Shetty B A, Shilpa T A, Rajanna AH, Ravi K, Rao M, Bhat B. Association of neutrophil-lymphocyte ratio with clinical outcome of COVID-19 patients: A prospective study. APIK J Int Med 2021;9:215-20

How to cite this URL:
Shetty B A, Shilpa T A, Rajanna AH, Ravi K, Rao M, Bhat B. Association of neutrophil-lymphocyte ratio with clinical outcome of COVID-19 patients: A prospective study. APIK J Int Med [serial online] 2021 [cited 2021 Nov 29];9:215-20. Available from: https://www.ajim.in/text.asp?2021/9/4/215/328675




  Introduction Top


COVID-19 infection, which was first reported as a cluster of pneumonia from Wuhan, China, in December 2019, has rapidly emerged as a global pandemic.[1] During the early course of the pandemic, Italy had the highest infection burden, and India remained much less affected with corresponding mortality rates of 14.24% and 3.03%.[2] However, the recent trends from the country show an exponential increase in daily spike, and the total cases has crossed 75 lakh mark, according to the Health Ministry data published on October 20, 2020.[3] The officially confirmed deaths from the disease are around 114,646.

Understanding and evaluating the demographic data pertaining to the disease is paramount to develop customized approaches to reduce the disease risk and public health policies, which may also help us deal with future outbreaks, which are bound to occur. A study by Huang et al. studied the clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The researchers found that 2019-nCoV infection caused clusters of severe respiratory illness similar to severe acute respiratory syndrome coronavirus and was associated with intensive care unit (ICU) admission and high mortality.[4] A study conducted by Safdarjung Hospital COVID 2019 working group, during the early phase of the pandemic, has noted that the first 21 patients diagnosed with COVID-19 had the clinical presentation of mild upper respiratory tract infection, which self-resolved with preserved vitals and organ functions. All the subjects recovered with no residual symptoms.[5]

Laskowski et al. have reported that understanding the demographic characteristics of the population at risk is paramount to understand the pattern of epidemic spread and to determine the public health intervention measures to be adopted for effective disease management.[6]

A study conducted by Basbus et al., in early 2020 on 131 patients of COVID-19 with varying severity of disease in Buenos Aires identified neutrophil-lymphocyte ratio (N-L ratio) as a significant prognostic marker in early infection.[7]

Although the global COVID cases surpassed 28 million with mortality exceeding 909000, the risk factors for mortality and the detailed clinical course of disease have not yet been established. The present study is intended to analyze N-L ratio of COVID-19 patients admitted in an Indian setting and to find the relationship of the same with clinical profile and disease outcomes. N-L ratio if found to be have a significant relationship with outcome can be used as an early and economically feasible predictor of severity of illness.


  Methodology Top


The prospective study was carried out between March and May 2020 at a Bengaluru-based hospital setting. Approval and clearance were obtained from the Institutional Ethics Committee. The study included patients aged ≥18 years of both the gender, diagnosed with COVID-19 infection by reverse transcription-polymerase chain reaction (RT-PCR) technique. The study excluded patients <18 years and those not willing to provide signed informed consent prior to the study. Case record form with a follow-up chart was used to record the demographic data and duration and clinical features of the disease.

Sample size estimation

N = Za2σ2/d2

N = 1.922 × 4002/4% of mean = 1676.07

The demographic and clinical data collected were age, clinical symptoms, and incidence of comorbidities such as hypertension, diabetes, and metabolic renal cardiac and respiratory disorders. All the selected participants were followed up until discharge or death. As per the first discharge policy released by the state government, the patients were discharged after 14 days if 2 consecutive throat/nasopharyngeal swabs taken 24 h apart were negative for SARS-CoV-2 RNA done using RT-PCR technique. If positive, the test was repeated after 72 h. As per the revised discharge policy, all mild and asymptomatic patients were discharged only after a repeat RT-PCR technique for SARS-CoV-2 RNA was negative, conducted 7 days after the first test. If positive, test was repeated after 72 h. As per the third discharge policy, patients who had mild and moderate symptoms were discharged after 10 days without throat/nasopharyngeal swab test for COVID-19, and for severe patients, 14th day discharge policy based on negative swab test was adopted and those who were positive, the tests were repeated every 3rd day till obtaining a negative result. The demographics and clinical outcome were further correlated.

Statistical analyses were carried out using R software (version 3.6.0, 2019) Vienna, Austria. Continuous variables were expressed as means and standard deviation, and categorical variables were presented as counts and percentages. Patients were grouped as survival and death. Different parameters were compared between the groups using t-test for continuous and Chi-square test for categorical data. The optimal cut points were estimated for significant continuous variables using receiver operating characteristic curve (ROC) analysis. Multiple regression analysis was carried out, and odds ratio with confidence interval (CI) were estimated to determine the effect of significant factors on outcome death and survival. For evaluating the mean days of viral clearance, many mild and moderate cases were not considered due to the implementation of the revised third discharge policy. P < 0.05 was considered as statistically significant.


  Results Top


The study considered 2000 patients admitted to our hospital and were diagnosed positive for COVID-19. Thirty-three patients were referred to different hospitals due to various reasons. The remaining 1977 patients were included in the study with a male:female ratio of 1:0.62. Among 1977 patients, 1419 (71.78%), 128 (6.48%), and 428 (21.65%) were under 10 days asymptomatic policy, 2 swab discharge policy and 7th day swab policy, respectively. All the patients were categorized as survived (1839%–93.02%) or succumbed to death (138%–6.98%) based on the outcome observed. The demographic and clinical characteristics considered for the analysis are shown in [Table 1]. The average age of the patients was 43.89 ± 15.58 years, and the mean age of survival and death noted were 42.74 ± 15.15 years and 59.12 ± 12.95 years, respectively.
Table 1: Baseline and clinical characteristics of the participants

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Between the two groups, the statistically significant variables noted were age, total leukocytes count (TLC) [Figure 1], neutrophil, lymphocytes, N-L ratio, all the comorbidity variables, and the asymptomatic status of the subjects [Table 2]. These significant variables, except neutrophils and lymphocytes, were further considered for multivariate logistic regression. N-L ratio, being a ratio of neutrophils and lymphocytes, was considered for the regression analysis. Odds ratio (OR) with CI for the variables are tabulated in [Table 3]. Variables such as comorbidities and asymptomatic nature of patients were found to be statistically significant. The risk of mortality was more in subjects with comorbidities and those having chronic kidney disease. A direct positive association was noted between asymptomatic status and increase chances for survival (OR 0.30, 0.09–0.78).
Figure 1: Comparison of neutrophil-lymphocyte ratio and total leukocytes count in patients who survived and those who succumbed to death

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Table 2: Comparison of neutrophil-lymphocyte ratio in various groups are 123

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Table 3: Multivariate logistic regression of the selected variables

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For continuous variables such as age, TLC, N, L, and N-L ratio cut-off points were determined through ROC analysis. Predicted cut off points, area under the ROC curve (AUC), specificity, sensitivity, and mean values noted for each variable are listed in [Table 4]. All the variables were found to be potential predictors as the AUCs were more than 60%. Highest AUC was found for TLC (67.01%) with cut-off point of 9800 along with the specificity and sensitivity of 73.97% and 83.12%, respectively. AUC noted for the variables are graphically shown in [Figure 3].
Table 4: Cut off points, area under receiver operating characteristic curve, specificity and sensitivity noted for potential predictors

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Figure 2: Odds ratio of comorbidities

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Figure 3: Receiver operating characteristic curve for variables showing area under curve

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Based on the number of days required for viral clearance, the subjects were classified as Group 1: ≤14 days, Group 2: 15–28 days, and Group 3: >28 days. Out of 536 patients who had viral clearance information, 449 (83.77%), 121 (22.58%), and 6 (1.12%) patients were categorized into Group 1, 2, and 3, respectively. Among these patients, 76 (14.18%), 122 (22.76%), and 378 (70.52%) were under 10 days asymptomatic policy, 2 swab discharge policy, and 7th day swab policy respectively with corresponding mean viral clearance time of 12.09 ± 4.86, 18.12 ± 5.06, and 10.56 ± 5.72 days. The overall mean viral clearance time for 536 patients was found to be 8.98 ± 3.54 days. Comparison of different variables across the different groups is shown in [Table 5]. Significant difference was noted between three groups with respect to the comorbidity status (P < 0.0001). In the Group 3, around 33% of the subjects had diabetes as opposed to only around 5% in Group 1 and 2. 50% of l the subjects belonging to the Group 3 required oxygen and other ICU facilities when compared to the other two groups (P < 0.0016). In all the three groups categorized based on viral clearance, more than half of the subjects were asymptomatic (>50%). The COVID-related symptoms dyspnea and cough were more prominent in Group 3 (P < 0.05), and the other symptoms such as fever, myalgia, sore throat, and headache were not significantly differed between the groups (P > 0.05). The corresponding number of subjects who succumbed to death in Group 1, 2, and 3 were 42 (9.35%), 0 (0%), and 1 (17.63%), respectively (P 0.0187).
Table 5: Comparison of the different variables across the three groups

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  Discussion Top


Through the present study, it was noticed that poor outcomes occur at higher ages. There is substantial literature evidence to validate the association between age-related COVID19 severity and mortality. A meta-analysis and rapid review by Romero Starke et al. have also reiterated the positive associated between increased age-related risk of COVID-19 disease severity, admission to ICU, and mortality. The increased risk per age year noted for disease severity was 2.7%.[8]

The current study has noted fever, dyspnea, and cough as the major symptoms prevalent among patients who died when compared to those who survived (P < 0.00001). Zhang et al. have also evaluated the clinical characteristics of 82 deaths cases, laboratory-confirmed as SARS-CoV-2 infection. The researchers have reported fever (78.0%), cough (64.6%), and shortness of breath (63.4%) as the prominent symptoms reported in the succumbed victims.[9]

The statistically significant variables noted between the survived and mortality groups were age, TLC, neutrophil, lymphocytes, NLR, all the comorbidity variables, and the asymptomatic status of the subjects. In concurrence with these findings, a study conducted by Saluja et al. in an Indian setting has also observed that hypertension was the most common associated comorbidity reported followed by diabetes.[10]

Hb, TLC, neutrophils, lymphocytes, NLR, LDH, and ferritin were identified as significant predictors of disease outcome. Among these variables, the highest specificity (73.97%) and sensitivity (83.12%) were noted for TLC. A study by Singh et al. has assessed the potential of routine hematological parameters and infectious biomarkers in evaluating the disease severity in 100 adult COVID-positive patients. The researchers have suggested that TLC, absolute neutrophil count, and NLR may assist in triaging patients requiring ICU care and deciding on the interventions.[11]

In the current mortality group, around 53% of the subjects had diabetes/hypertension with and around 6% of the subjects demonstrated chronic kidney disease as opposed to 0.92% in the survived group. In concurrence with these findings data from Mexico has identified CKD, hypertension, chronic obstructive pulmonary disease, obesity, and diabetes are associated with elevated mortality risk in COVID patients. A review focusing on developing countries, including India, has reported that the presence of comorbidities is linked to poor outcomes in COVID subjects. The study has also found that the majority of the COVID subjects are asymptomatic with incidence ranging between 26% and 76%.[12] The present study has also noted more than half of the subjects belonging to the survived group being asymptomatic (58.48%). The COVID-related symptoms were more prominent in group that adopted the 10-day asymptomatic policy, and the major symptoms were fever (49%), dyspnea (62%), cough (30%), and myalgia (13%).

Zhang et al. studied the clinical characteristics of 82 cases of death due to COVID, and most of the findings are in line with the present results. The most common comorbidity noted in patients who died were hypertension (56.1%), followed by heart disease (20.7%), diabetes (18.3%), cerebrovascular disease (12.2%), and cancer (7.3%). Lymphopenia, neutrophilia, and thrombocytopenia were the common clinical finding observed on admission. In addition, elevated NLR of >5, systemic immune-inflammation index of >500. Respiratory failure was identified as the main cause of COVID-19, and high level of interleukin-6 (>10 pg/ml) was indicative of cytokine release syndrome-mediated damage to other vital organs.[9]

The present study holds significant relevance, as there is very limited literature evidence from the subcontinent correlating demographic data of COVID-19 patients with clinical profile and disease outcomes. Moreover, it sheds light on several significant findings, which would assist clinicians in screening, treatment decision, and estimating the disease prognosis. Another strength of the study is good sample size, but the generalization of the findings is limited, as the study was carried out in a single center. The study has not evaluated the outcomes from treatment interventions. This was not considered, as no specific standard protocol was available at that point of a pandemic for managing COVID patients.


  Conclusion Top


The present study has underscored the clinical utility of TLC, neutrophils, lymphocytes, and N-L ratio, as significant predictors of COVID-19 outcome. Maximum of around 8.98 ± 3.54 days has been concluded as mean days of viral clearance required in most of the COVID positive patients.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
WHO | Pneumonia of Unknown Cause – China World Health Organization; 2020. Available from: http://www.who.int/csr/don/05-january-2020-pneumonia-of-unkown-cause-china/en/. [Last accessed on 2020 Nov 04].  Back to cited text no. 1
    
2.
John TJ, Seshadri MS. COVID-19 mortality trends and reporting. Econ Polit Wkly 2015;55:7-8.  Back to cited text no. 2
    
3.
PTI. COVID-19 Caseload in India Crosses 75-Lakh Mark. National Herald; 2020. Available from: https://www.nationalheraldindia.com/national/covid-19-caseload-in-india-crosses-75-lakh-mark. [Last accessed on 2020 Nov 04].  Back to cited text no. 3
    
4.
Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506.  Back to cited text no. 4
    
5.
Gupta N, Agrawal S, Ish P, Mishra S, Gaind R, Usha G, et al. Clinical and epidemiologic profile of the initial COVID-19 patients at a tertiary care centre in India. Monaldi Arch Chest Dis. 2020;90. doi: 10.4081/monaldi.2020.1294. PMID: 32290644.  Back to cited text no. 5
    
6.
Laskowski M, Mostaço-Guidolin LC, Greer AL, Wu J, Moghadas SM. The impact of demographic variables on disease spread: Influenza in remote communities. Sci Rep 2011;1:105.  Back to cited text no. 6
    
7.
Basbus L, Lapidus MI, Martingano I, Puga MC, Pollán J. Neutrophil to lymphocyte ratio as a prognostic marker in COVID-19. Medicina (B Aires) 2020;80 Suppl 3:31-6.  Back to cited text no. 7
    
8.
Romero Starke K, Petereit-Haack G, Schubert M, Kämpf D, Schliebner A, Hegewald J, et al. The age-related risk of severe outcomes due to COVID-19 infection: A rapid review, meta-analysis, and meta-regression. Int J Environ Res Public Health 2020;17:E5974.  Back to cited text no. 8
    
9.
Zhang B, Zhou X, Qiu Y, Song Y, Feng F, Feng J, et al. Clinical characteristics of 82 cases of death from COVID-19. PLoS One 2020;15:e0235458.  Back to cited text no. 9
    
10.
Saluja M, Pillai D, Jeliya S, Bauddh N, Chandel R. COVID 19- clinical profile, radiological presentation, prognostic predictors, complications and outcome: A perspective from the Indian subcontinent. J Assoc Physicians India 2020;68:13-8.  Back to cited text no. 10
    
11.
Marimuthu AK, Anandhan M, Sundararajan L, Chandrasekaran J, Ramakrishnan B. Utility of various inflammatory markers in predicting outcomes of hospitalized patients with COVID-19 pneumonia, Lung India: September–October 2021;38:448-53 doi: 10.4103/lungindia.lungindia_935_20.  Back to cited text no. 11
    
12.
Singh AK, Misra A. Impact of COVID-19 and comorbidities on health and economics: Focus on developing countries and India. Diabetes Metab Syndr 2020;14:1625-30.  Back to cited text no. 12
    


    Figures

  [Figure 1], [Figure 2], [Figure 3]
 
 
    Tables

  [Table 1], [Table 2], [Table 3], [Table 4], [Table 5]



 

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