Neutrophil-to-lymphocyte ratio on admission is an independent risk factor for the severity and mortality in patients with coronavirus disease 2019

Abstract

•The level of NLR on admission could be an independent risk factor for the severe disease and the mortality of COVID-19.•The predictive value of NLR for poor prognosis was more significant in patients without other potential risk factors.•NLR could help physicians rapidly identify high-risk patients and adopt timely intervention. The study by Liu et al. had been published in your journal, and reported that the neutrophil-to-lymphocyte ratio (NLR) was an independent risk factor for the mortality of the COVID-19 patients.1Liu Y. Du X. Chen J. et al.Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality inhospitalized patients with COVID-19.J Infect. 2020; 81: e6-e12Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar Based on it, we reported the association between levels of NLR at admission and the disease severity in COVID-19 and further explored the predictive role of NLR for mortality of the COVID-19 patients in more subgroups. Key epidemiological, clinical, laboratory, radiological and outcomes data were obtained through a detailed medical chart review from January 1st to February 10th, 2020 at the Renmin Hospital of Wuhan University. All the peripheral venous blood samples were collected on admission and were examined at the laboratory following standard procedures. Multivariable logistic regression analyses with the stepwise procedure were used to estimate odds ratios (OR) and 95% confidence intervals (CI). Then, the subgroup and interaction analyses for NLR were conducted according to statistically significant variables in former logistic regression analyses. A cohort of 140 patients with the confirmed disease was identified. 52 patients had severe diseases and 32 patients eventually died. Compared to the lower NLR group, patients with higher NLR in this study were 29 years older, more likely to have current smoking, had more comorbidities such as diabetes, hypertension, cardiovascular and chronic obstructive pulmonary disease (COPD), and had various symptoms, especially sputum production, headache, upper airway symptoms, and dyspnea (Table 1). It was consistent with the baseline characteristic of the study by Liu et al.1Liu Y. Du X. Chen J. et al.Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality inhospitalized patients with COVID-19.J Infect. 2020; 81: e6-e12Abstract Full Text Full Text PDF PubMed Scopus (9) Google Scholar Table 2 shows the correlation of NLR with severe disease and death in the final analysis. Upon multivariate adjustment, most of the estimated correlations were attenuated. Increased NLR (severity: OR, 8.56, 95% CI, 1.39 - 52.61, p = 0.021; mortality: OR, 1.30, 95% CI, 1.14 - 1.49, p < 0.001) was an independent risk factor for both severity and mortality. Adjusting interacted variables for NLR did not eliminate its significant correlation with the severity risk and mortality risk. Liu et al. reported that NLR exhibited an increase in the risk of mortality for the third tertile (NLR ≧ 4.85). And we further found that the risk of severity and mortality for patients with NLR ≧ 2.14 were significantly higher than those with NLR ≦ 0.48. It suggested that the cut-off point of the NLR could be lower down. For disease severity, age group (≤60, >60; p = 0.053), cancer (p = 0.037) had interactions with NLR. For mortality, age group (p = 0.059), hypertension (p = 0.005), dyspnea (p = 0.006) had interactions with NLR. The correlations of NLR with severity and mortality were statistically significant in subgroups of patients with the age of ≤60 years old, without diabetes, cancer, hypertension, and symptom of dyspnea.Table 1The baseline characteristics of patients with COVID-19 by the level of NLR.CharacteristicsAll casesNLR(n = 140)Group 1 (< 2.14, n = 93)Group 2 (≧2.14, n = 47)Demographics Age, median (IQR)48.00 (29.75)37.00 (21.00)66.00 (19.00) Age range, years ≤3025 (17.9%)22 (23.7%)3 (6.4%) 30–6079 (56.4%)62 (66.7%)17 (36.2%) >6036 (25.7%)9 (9.7%)27 (57.4%) Sex male51 (36.4%)35 (37.6%)16 (34.0%) female89 (63.6%)58 (62.4%)31 (66.0%) BMI, median (IQR)23.45 (2.88)23.20 (3.30)23.80 (2.30) Overweight46 (38.3%)33 (35.5%)13 (48.1%) Exposure history (yes)4 (3%)2 (2.2%)2 (4.3%) Current smoking (yes)8 (6%)2 (2.2%)6 (12.8%)Comorbidity3 Diabetes (yes)15 (11%)3 (3.2%)12 (25.5%) Hypertension (yes)32 (23%)6 (18.8%)26 (55.3%) Cardiovascular disease (yes)16 (11%)1 (1.1%)15 (31.9%) COPD (yes)6 (4%)1 (1.1%)5 (10.6%) Cancer (yes)10 (7%)6 (6.5%)4 (8.5%) Chronic liver disease (yes)2 (1%)1 (1.1%)1 (2.1%) Other disease (yes)14 (10%)4 (4.3%)10 (21.3%)Clinical symptoms Fever (yes)96 (68.6%)59 (63.4%)37 (78.7%) Cough (yes)84 (60.0%)54 (58.1%)30 (63.8%) Sputum (yes)13 (9.3%)1 (1.1%)12 (25.5%) Myalgia (yes)59 (42.1%)38 (40.9%)21 (44.7%) Headache (yes)28 (20.0%)10 (10.8%)18 (38.3%) Dyspnoea (yes)45 (32.1%)21 (22.6%)24 (51.1%) UAS (yes)34 (24.3%)16 (17.2%)18 (38.3%) GIS (yes)11 (7.9%)6 (6.5%)5 (10.6%)Laboratory findings2On admission, liver and renal function tests were all found to be within normal range, and thus excluded from the data collection. WBC, median (IQR), 109/L4.66 (2.37)4.34 (2.00)5.61 (4.00) N, median (IQR), 109/L1.63 (2.30)1.14 (0.80)4.39 (3.37) L, median (IQR)), 109/L1.87 (2.05)2.60 (1.71)0.66 (0.42) NLR LDH, median (IQR), U/L214.5 (113.50)197.00 (62.00)293.00 (173.00) LDH > 250 U/L43 (30.7%)16 (17.2%)27 (57.4%) CRPR, median (IQR)0.99 (2.78)0.48 (1.41)2.78 (5.56)Total severity score, median (IQR)2.00 (3.00)2.00 (2.00)7.00 (11.0)Disease severity Common type86 (61.4%)79 (84.9%)7 (14.9%) Severe type54 (38.6%)14 (15.1%)40 (85.1%)Survival status Alive108 (77.1%)87 (93.5%)21 (44.7%) Dead32 (22.9%)6 (6.5%)26 (55.3%)Abbreviation: COVID-19, coronavirus disease 2019; n, number of cases; BMI, body mass index; IQR, interquartile range; COPD, chronic obstructive pulmonary disease; UAS, upper airways symptoms (sore throat, sneeze, and rhinorrhea); GIS, gastrointestinal symptoms (diarrhea, gastrointestinal discomfort, and loss of appetite); WBC, white blood cell; N, neutrophil; L, lymphocyte; NLR, neutrophil-to-lymphocyte ratio; LDH, lactate dehydrogenase; CRPR, ratio of C-reactive protein (the ratio of CRP value/ upper limit of the CRP value). Exposure history meant Huanan seafood market exposure history..1For categorical variables, P values were derived from χ2-test or Fisher's exact test. For continuous variables, P values were derived from Student-t-test or Mann-Whitney U test.2 On admission, liver and renal function tests were all found to be within normal range, and thus excluded from the data collection. Open table in a new tab Table 2Final multivariable analyses of the correlation of neutrophil, lymphocyte, and NLR with the severe disease and death of COVID-19.CharacteristicsSeverityMortalityOR (95% CI)P value1Derived from multivariate stepwise analysis of logistic regression model.OR (95% CI)P value1Derived from multivariate stepwise analysis of logistic regression model.Final Model 12Final model 1: for disease severity, retained in this model after the stepwise selection was age (as a continuous variable), fever (yes, no), dyspnea (yes, no), neutrophil (109/L), lymphocyte (109/L), C-reactive protein ration (CRPR); for mortality, retained in this model after the stepwise selection was age (as a continuous variable), neutrophil (109/L), lymphocyte (109/L), CRPR.N (109/L)2.27 (1.04–4.93)0.0391.06 (0.82–1.36)0.674L (109/L)0.64 (0.25–1.18)0.1550.78 (0.56–1.09)0.146Final Model 23Final model 2: for disease severity, retained in the final model was fever (yes, no), dyspnea (yes, no), NLR (as a continuous variable), and CRPR (as a continuous variable); for mortality, retained in the final model was hypertension (yes, no), cancer (yes, no), NLR (as a continuous variable), and CRPR (as a continuous variable).NLR8.56 (1.39 - 52.61)0.0211.30 (1.14 - 1.49)< 0.001Final Model 34Final model 3: for disease severity, retained in the final model was age group (<60, ≧60), COPD (yes, no), cancer (yes, no), fever (yes, no), dyspnea (yes, no), and NLR (as a categorical variable); for mortality, retained in the final model was age group (<60, ≧60), hypertension (yes, no), dyspnea (yes, no), CRPR, NLR (as a categorical variable). 5NLR was used as a continuous variable in the subgroup analysis.NLR1.87 (1.42–2.46)<0.0011.24 (1.08–1.41)0.002 Tertile 1 (≦0.48, as ref.)1.001.00 Tertile 2 (0.49- 2.13)0.74 (0.18–3.05)0.3821.15 (0.12–11.05)0.902 Tertile 3 (≧2.14)20.48 (5.87–71.46)<0.00111.79 (2.05–67.94)0.006Subgroup analyses for NLR5Age ≤ 602.73 (1.28–5.84)0.0101.36 (1.10–1.68)0.005 >601.92 (1.00–3.69)0.0491.16 (0.99–1.35)0.067Fever No1.69 (0.92–3.10)0.0885.06 (0.16–155.78)0.354 yes2.98 (1.52–5.87)0.0021.11 (0.96–1.30)0.171dyspnea No2.77 (1.42–5.41)0.0301.80 (1.10–2.94)0.020 Yes2.09 (0.86–5.08)0.1051.11 (0.96–1.28)0.160Hypertension No2.34 (1.06–5.16)0.0351.53 (1.22–1.92)<0.001 Yes2.17 (1.00–4.73)0.0501.05 (0.92–1.19)0.487Diabetes No1.88 (1.18–7.00)0.0201.16 (1.00–1.34)0.050 Yes//1.34 (0.70–2.58)0.383Cancer No2.54 (1.43–4.51)0.0011.18 (1.02–1.37)0.030 Yes//1.51 (0.58–3.92)0.396Abbreviation: COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval; N, neutrophil; L, lymphocyte; NLR, neutrophil-to-lymphocyte ratio.“/” means that the number of cases in the subgroup is not sufficient for analysis.1 Derived from multivariate stepwise analysis of logistic regression model.2 Final model 1: for disease severity, retained in this model after the stepwise selection was age (as a continuous variable), fever (yes, no), dyspnea (yes, no), neutrophil (109/L), lymphocyte (109/L), C-reactive protein ration (CRPR); for mortality, retained in this model after the stepwise selection was age (as a continuous variable), neutrophil (109/L), lymphocyte (109/L), CRPR.3 Final model 2: for disease severity, retained in the final model was fever (yes, no), dyspnea (yes, no), NLR (as a continuous variable), and CRPR (as a continuous variable); for mortality, retained in the final model was hypertension (yes, no), cancer (yes, no), NLR (as a continuous variable), and CRPR (as a continuous variable).4 Final model 3: for disease severity, retained in the final model was age group (<60, ≧60), COPD (yes, no), cancer (yes, no), fever (yes, no), dyspnea (yes, no), and NLR (as a categorical variable); for mortality, retained in the final model was age group (<60, ≧60), hypertension (yes, no), dyspnea (yes, no), CRPR, NLR (as a categorical variable). 5NLR was used as a continuous variable in the subgroup analysis. Open table in a new tab Abbreviation: COVID-19, coronavirus disease 2019; n, number of cases; BMI, body mass index; IQR, interquartile range; COPD, chronic obstructive pulmonary disease; UAS, upper airways symptoms (sore throat, sneeze, and rhinorrhea); GIS, gastrointestinal symptoms (diarrhea, gastrointestinal discomfort, and loss of appetite); WBC, white blood cell; N, neutrophil; L, lymphocyte; NLR, neutrophil-to-lymphocyte ratio; LDH, lactate dehydrogenase; CRPR, ratio of C-reactive protein (the ratio of CRP value/ upper limit of the CRP value). Exposure history meant Huanan seafood market exposure history. .1For categorical variables, P values were derived from χ2-test or Fisher's exact test. For continuous variables, P values were derived from Student-t-test or Mann-Whitney U test. Abbreviation: COVID-19, coronavirus disease 2019; OR, odds ratio; CI, confidence interval; N, neutrophil; L, lymphocyte; NLR, neutrophil-to-lymphocyte ratio. “/” means that the number of cases in the subgroup is not sufficient for analysis. For COVID-19, the increased neutrophils indicate the degree of the inflammatory response, and the decreased lymphocytes indicate the degree of immune imbalance.2Liu J. Li S. Liu J. et al.Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients.EBioMedicine. 2020; 102763Abstract Full Text Full Text PDF PubMed Scopus (977) Google Scholar These associations are amplified by the concept of NLR. In severe diseases, the rapid replication of coronavirus induces the delayed IFN response, which sensitizes the T cells to apoptosis. Thus, the virus cannot be cleared in time. A large number of neutrophils and monocyte/macrophages are recruited to the infectious sites, and infiltrate into the lungs.3Channappanavar R. Perlman S Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology.Semin Immunopathol. 2017; 39: 529-539Crossref PubMed Scopus (1601) Google Scholar Previous studies of coronavirus suggested that the lymphocyte loss might be associated with the immune-escape mechanism of the virus.3Channappanavar R. Perlman S Pathogenic human coronavirus infections: causes and consequences of cytokine storm and immunopathology.Semin Immunopathol. 2017; 39: 529-539Crossref PubMed Scopus (1601) Google Scholar Nowadays, it has also been suggested that lymphocyte loss might be associated with the direct infection of lymphocytes by virus or the myelosuppression by antiviral responses.4Oberfeld B. Achanta A. Carpenter K. et al.SnapShot: COVID-19.Cell. 2020; 181 (954.e1)Abstract Full Text PDF PubMed Scopus (85) Google Scholar The proliferation of the virus results in the toxic effect on lymphocytes, and the decrease of lymphocytes further weakened the immune response to the virus, forming a vicious circle. Uncontrolled and overreacted immune responses lead to the cytokine storm, causing diffuse alveolar damage or multi-organ failure,5Wang J. Jiang M. Chen X. Montaner L.J Cytokine storm and leukocyte changes in mild versus severe SARS-CoV-2 infection: review of 3939 COVID-19 patients in China and emerging pathogenesis and therapy concepts.J. Leukoc. Biol. 2020; 108: 17-41Crossref PubMed Scopus (390) Google Scholar finally resulting in death from COVID-19.6Yang X. Yu Y. Xu J. et al.Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study.Lancet Respir Med. 2020; 8: 475-481Abstract Full Text Full Text PDF PubMed Scopus (5895) Google Scholar The depletion of hematopoietic stem cell bank or immune cell function, which were caused by the aging of the body or a long time of chronic inflammation, were more likely to lead to the cytokine storm when responding to the severe infections.7Bagatini M.D. Cardoso A.M. Dos Santos A.A. Carvalho F.B Immune system and chronic diseases.J Immunol Res. 2017; 4284327PubMed Google Scholar Thus, patients with these risk factors had a higher level of NLR. Liu et al. conducted subgroup analyses by gender, female, body mass index, and the presence of hypertension. They only found that the male had a more significant association with the risk of mortality than the female. Interestingly, we further found that NLR was of greater value in predicting severity and mortality for patients with no other clinical risk factors (i.e., those with a theoretically better prognosis), such as patients with younger age, or without comorbidities. In conclusion, we found that the level of NLR on admission could be an independent risk factor for the prognosis of COVID-19, not only for the mortality but also for the disease severity. Also, the predictive value was more significant in patients without other potential risk factors. NLR could help physicians rapidly identify high-risk patients and adopt timely intervention, to reduce the rates of severe disease and mortality. The authors state that they have no conflicts of interest to disclose.