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ORIGINAL ARTICLE Table of Contents  
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Association of inflammatory markers, neutrophil-lymphocyte ratio, and D-Dimer with mortality in COVID-19 infection: A hospital-based retrospective analysis


1 Department of Pulmonary Medicine, AIIMS, Patna, Bihar, India
2 Department of CFM, AIIMS, Patna, Bihar, India
3 Department of PMR, AIIMS, Patna, Bihar, India
4 Department of Nephrology, PMCH, Patna, Bihar, India

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Date of Submission03-Jan-2022
Date of Decision13-Feb-2022
Date of Acceptance15-Feb-2022
Date of Web Publication27-Oct-2022
 

  Abstract 


Introduction: To assess the association of blood biomarkers such as C-reactive protein (CRP), serum ferritin, lactate dehydrogenase (LDH), neutrophil-lymphocyte ratio, and D-dimer at admission with in-hospital mortality in COVID-19 and to determine best predictive cut-offs for them. Materials and Methods: This cross-sectional study included 984 confirmed cases of COVID-19 admitted in months of July and August 2020. The optimal biomarker cut-off points for mortality were defined by a receiver operating characteristic curve. Survival probabilities were estimated by the Kaplan–Meier method and compared with the log-rank test. Results: The overall mortality rate among the hospitalized cases was 254 (25.81%). All the markers were found to be significantly higher (P < 0.001) in nonsurvivor group as compared to the survivors at the time of admission. Serum CRP, ferritin, D-dimer and LDH were found to be elevated, i.e., higher than the upper limit of normal range in 426 (83%), 469 (68.37%), 449 (67.9%), and 380 (93.1%) respectively overall. However, these markers were significantly more elevated in nonsurvivor compared to survivors. A significant increasing trend of elevated level of all biomarkers was observed with increase of severity level (P < 0.0001). It was found that CRP ≥82 mg/L had sensitivity of 63.58% and specificity of 68.38% for predicting the mortality. Similarly, serum ferritin ≥475.6 mg/ml had sensitivity of 68.09% and specificity of 65.26%, D-dimer ≥0.65 had sensitivity of 90.71% and specificity of 55.45%, and LDH ≥915 U/L had sensitivity of 69.34% and specificity of 73.8% to predict the mortality. Furthermore, neutrophil and lymphocyte count ratio (NLR) ≥8.86 had sensitivity of 65.61% and specificity of 79.7% to predict the mortality. Conclusion: Levels of the blood biomarker such as CRP, serum ferritin, LDH, NLR, and D-dimer at admission can predict mortality in COVID-19 infection.

Keywords: COVID-19, D-dimer, inflammatory marker, mortality, neutrophil and lymphocyte count ratio


How to cite this URL:
Rai DK, Ranjan A, Pandey SK, Vardhan H. Association of inflammatory markers, neutrophil-lymphocyte ratio, and D-Dimer with mortality in COVID-19 infection: A hospital-based retrospective analysis. J Appl Sci Clin Pract [Epub ahead of print] [cited 2023 Feb 4]. Available from: http://www.jascp.org/preprintarticle.asp?id=358992





  Introduction Top


The novel coronavirus (SARS-cov2) or COVID-19 has spread as pandemic worldwide from its place of origin in Wuhan City of Hubei Province of China. Many of the countries have faced more than one waves of epidemic since December 2019 till date. On March 11, 2020, the World Health Organization (WHO) has declared COVID-19 as a global pandemic and most of the countries worldwide have registered COVID-19 cases and mortality. As of till May 18, 2021, a total 16.4 crore cases, and 34.1 lakh deaths have been reported at the global level.[1]

In India, the first case of COVID-19 was reported on January 30, 2020, and almost for 1 month there was no incidence until March 3, 2020. From March 3rd onward, there has been regular incidence of COVID-19 reported from all the states and UTs except few. Till May 18, 2021, a total of 2.55 crore cases and 2.83 lakh deaths have been reported from almost all the states and UTs of India. The first case of COVID-19 was reported on March 20, 2020 in Bihar. The total cases and deaths reported from various districts of Bihar till May 18, 2021, was 6.64 lakhs and 4039 deaths, respectively.[2]

Characterization of COVID-19 infection in hospitalized patients is urgently needed to support the clinical decision-making and the appropriate allocation of resources. Retrospective analysis of patient characteristics and laboratory findings including neutrophil and lymphocyte count ratio (NLR) and several inflammatory markers including lactate dehydrogenase (LDH), C-reactive protein (CRP), ferritin, and interleukin-6 (IL-6) can be helpful in assessing the severity and predicting the mortality. Some studies have reported high level of several inflammatory markers correlating with disease severity for predicting the disease outcome.[3],[4] However, the prognostic value of these markers needs to be established for taking clinical decisions and management of COVID-19 cases admitted to hospitals.

This study was carried out to assess the relationship of serum CRP, ferritin, D-dimer, and LDH levels and NLR level of the patients at the time of admission with the outcome such as death/discharge and also in relation to the severity levels with-in hospital among patients with COVID-19 infection and to determine cut-off values of these biomarkers and NLR for predicting the mortality.


  Materials and Methods Top


This cross-sectional study was carried out at the Department of Pulmonary Medicine, All India Institute of Medical Sciences, Patna, Bihar, India. Records of all the patients of COVID-19 admitted in wards and intensive care units of hospital from July to August 2020 were retrieved from the Medical Record Department using the patients ID. A patient record form was developed to capture important variables such as sociodemographic, date of admission and discharge, clinical signs and symptoms, comorbidities, severity score, biomarkers and laboratory parameters at the time of admission, and outcome at the time of discharge. Disease severity was assessed using WHO guidelines.[5]

Out of total 984 records, data of biomarkers at admission were not available for all the patients. Data of CRP, ferritin, D-dimer, LDH, and NLR were available for 513, 686, 661, 408, and 972 patients respectively. Hence, separate analysis was done for each of the biomarkers and NLR with respect to disease severity and outcomes.

Ethical approval for the secondary data analysis was taken from the Ethical Review Committee of the institute. Consent of patients was not required because no personal identifiers was used for the study.

Statistical Analysis: Data were analyzed using Stata, version 10 (Stata Corp, Texas, USA). Shapiro–Wilk test was performed to test the normality of continuous variables. Nonparametric tests such as Mann–Whitney Wilcoxon rank sum test was used to compare the equality of distribution of variables between two groups. Kruskal–Wallis test was performed to compare the average level of biomarkers in more than two groups. Chi-square test was performed to assess the association between two binary variables. A P < 0.05 was taken as statistical significance.

Receiver operating characteristics (ROC) curves was used to determine the area under curve (AUC) with 95% confidence intervals of continuous markers taking mortality and survival of the patients as binary outcome, i.e., classification value. The cut-off value of each markers was determined using Youden Index, the closest to (0, 1) criteria (ER) and concordance probability method (CZ). The cut-off values were used to determine the sensitivity and specificity of all these markers for predicting mortality.

Kaplan–Meier survival analysis was performed taking the cut-off values of each markers and the duration of hospital stay of each patient as survival period to determine the probability of getting discharged from hospital as predicted by different biomarkers at these thresholds. Log-rank test was used to test the survival probabilities. The individual biomarkers were categorized into two groups: ≥cut-off values and <cut-off values to estimate the survival probabilities.


  Results Top


During the study, 984 patients with COVID-19 infection were admitted to the hospital. The overall mortality rate among the hospitalized cases was 254 (25.81%). We analyzed the data of all the biomarkers as well as NLR of the patients available in the database. Patients with missing values of these variables were excluded from the analysis.

[Table 1] presents the comparison of absolute values of these markers. All the markers were found to be significantly higher (P < 0.001) in nonsurvivor group as compared to the survivors at the time of admission. These markers were categorized as high and normal categories based on the normal range of biomarkers (NLR >3.3, CRP >5 mg/L, serum ferritin >322 ng/ml, LDH >460 U/L and D-dimer >0.5 mg/L considered as high). NLR was also significantly higher in nonsurvivor compared to survivors (P < 0.001).
Table 1: Comparison of inflammatory markers between survivor and nonsurvivor Groups

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[Figure 1] presents the comparison of elevated markers between nonsurvivors and survivors' group of patients. Serum CRP, ferritin, D-dimer, and LDH were found to be elevated, i.e., higher than the upper limit of normal range in 426 (83%), 469 (68.37%), 449 (67.9%), and 380 (93.1%) respectively overall. However, these markers were significantly more elevated in nonsurvivor compared to survivors.
Figure 1: Comparison of proportions of patients with high inflammatory markers based on outcome

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[Figure 2] presents the comparison of biomarkers among three categories of severity, i.e., mild, moderate and severe as per the COVID-19 severity classification of WHO. A significant increasing trend of elevated level of all biomarkers and NLR was observed with increase of severity level (P < 0.0001) [Table 2].
Figure 2: Comparison of proportions of patients with high inflammatory markers based on severity

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Table 2: Comparison of inflammatory markers among severity levels

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[Table 3] presents the AUC with 95% confidence interval, sensitivity, specificity, positive and negative likelihood ratio of each biomarkers and NLR. [Figure 3] presents the combined ROC of all biomarkers and NLR. It was found that CRP ≥82 mg/L had sensitivity of 63.58% and specificity of 68.38% for predicting the mortality. Similarly, serum ferritin ≥475.6 mg/ml had sensitivity of 68.09% and specificity of 65.26%, D-dimer ≥0.65 had sensitivity of 90.71% and specificity of 55.45%, and LDH ≥915 U/L had sensitivity of 69.34% and specificity of 73.8% to predict the mortality. Furthermore, NLR ≥8.86 had sensitivity of 65.61% and specificity of 79.7% to predict the mortality.
Table 3: Area under the receiver operating characteristic curves and optimal cut-off values of biomarkers

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Figure 3: Receiver operating characteristic curves for different inflammatory markers and neutrophil and lymphocyte count ratio

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[Figure 4] presents the Kaplan–Meier survival curves to compare the survival probabilities of COVID-19 patients based on the cut-off values of all biomarkers and NLR. The occurrence of death was taken as failure with respect to the duration of hospital stay as time. Survival probabilities were significantly higher among those with lower cut-off values of biomarkers such as CRP (log-rank Chi-square = 27.86, P = 0.0001), ferritin (log-rank Chi-square = 33.06, P = 0.0001), D-dimer (log-rank Chi-square = 71.93, P = 0.0001), LDH (log-rank Chi-square = 30.62, P = 0.001), and also NLR (log-rank Chi-square = 123.89, P = 0.0001).
Figure 4: KaplanMeier survival curves according to levels of inflammatory markers and Neutrophil and lymphocyte count ratio at admission

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  Discussion Top


In developing country like India, there is limited availability of medical resources especially for critically ill patients who require intensive care unit. If we identified patients with high risk of mortality as soon as possible, risk stratification can help in better utilization of insufficient medical resources and might reduce mortality. There is limited data in the literature on predictors of mortality in COVID-19 infection at the time of admission to the hospital. This study designed to provide sensitivity and specificity of various inflammatory marker, NLR, and D-dimer in predicting mortality in these patients. This study found significantly higher NLR, CRP, LDH, ferritin, and D-dimer in severe COVID-19 infection in compare to mild disease (P < 0.05). Several other studies supported our finding and showed higher level of marker in severe group.[6],[7],[8] All these markers were also significantly higher in severe group compare to moderate group supported by other study[9] while in contrary study by Arshad et al.[3] showed no significant difference. SARS-CoV-2 infection triggers both innate and adaptive immune response.[10] Disturbance of the immune system in patients has been considered as one of the hallmarks for COVID-19, especially cytokine release syndrome and lymphopenia.[11],[12] A meta-analysis performed by Ji et al. concluded that severe COVID-19 is associated with higher levels of inflammatory markers than a mild disease, so tracking these markers may allow early identification or even prediction of disease progression.[13] Among all the inflammatory markers, serum LDH were found in highest proportion of severe COVID patients followed by CRP and ferritin.

We found all the measured biomarker such as NLR, D-dimer, CRP, serum ferritin, and LDH were significantly higher in nonsurvivor compares to survivor.

Among all biomarker, NLR come out as best predictor of mortality. NLR basically reflects the balance of the body's neutrophil and lymphocyte count levels and the degree of systemic inflammation. It more reflects the balance between the severity of the inflammation and the body's immunity status, and is so considered an important marker of systemic inflammatory response.[14] NLR is more important marker practically as it is easily obtained in routine blood tests. NLR remains a simple, accessible, near real-time, and cost-effective biomarker, especially for healthcare facilities with limited medical resources. We also found that mean NLR as well as proportion of patient with elevated NLR increases with severity of COVID-19 infection. Our finding supported by other study showed NLR as independent risk factor for severe disease.[15] A systematic review of 38 studies showed that higher NLR values on admission were associated with higher risks of severity and mortality in COVID-19 patients.[16] ROC analysis performed to determine the optimal cut-off value found as 8.86 with an AUC value of 0.78, a sensitivity of 65.61%, and a specificity of 79.7%. To date, no optimal cut-off value for NLR has been validated across different populations and it varies across study. Yan et al.[17] showed cut-off value of 11.75 with an AUC value of 0.945 while Zhou et al.[18] found value of 7.945 with an AUC value of 0.827.

CRP, an acute phase reactant that is increased in a wide range of inflammation condition, has been found to be increased in 75%-93% of patients with COVID-19 infection, especially in severe disease.[19] CRP was significantly found higher in nonsurvivor and patients with severe disease. The area under ROC curve was largest for CRP at values >82 with higher sensitivity and specificity in predicting mortality. A meta-analysis[20] showed nearly three times increased risk of mortality amongst patients with cut off ≥10 mg/L. Another study[21] showed CRP >41.4 mg/L associated with sensitive of 90.5% and 77.6% specificity for mortality among hospitalized patients.

Serum ferritin has been recognized as a representative of total body iron stores, its prognostic utility is linked with inflammatory processes and is nonspecifically raised in a variety of conditions such as chronic kidney disease, rheumatoid arthritis, and various autoimmune disorders.[22] It is believed that the high ferritin levels in COVID-19 infection are driven by increased production driven by proinflammatory cytokines such as IL-6 and tumor necrosis factor-α or release from damaged cells. ROC analysis found Serum ferritin value off >475.6 with AUC of 0.77 associated with highest sensitivity and specificity in predicting mortality. In a study done by Feld et al.[23] showed cut-off 799 ng/ml with an AUC of 0.677.15 as best predictor of mortality. Another study supported our finding showed that elevated serum ferritin associated with 2 times increased risk of mortality.[24]

Several studies during the early phase of pandemic reported the elevated LDH in severe or deceased cases of COVID-19 infection.[25],[26] LDH is a cytoplasmic enzyme which is widely expressed in tissues and increased LDH was observed in different conditions such as tissue injury, necrosis, hypoxia, hemolysis, or malignancies.[27] Patients with LDH levels ≥1200 U/L in an American study were eight times more likely to die. ROC analysis found optimal cut off 915 for LDH with best sensitivity and specificity.

D-dimer elevation has been reported to be one of the commonest laboratory findings noted in COVID-19 infection. It originates from the formation and lysis of cross-linked fibrin and reflects activation of coagulation and fibrinolysis.[28] Our study showed nearly 4 times elevation of D-dimer in nonsurvivor and in patient with severe COVID-19 infection. We found that when using the cut-off value of 0.56, D-dimer levels upon admission for in-hospital mortality has an AUC of 0.65. The sensitivity and specificity are 88.2% and 55.45%, respectively. Zhou et al.[29] reported that D-dimer >1 μg/ml is a risk for mortality. Another study showed that D-dimer >2.14 mg/L associated with highest risk of in hospital mortality.[30] Guan et al.,[31] analyzed 1099 COVID-19 patients found that nonsurvivors had a significantly higher D-dimer (median: 2.12 μg/ml) than that of survivors (median: 0.61 μg/ml) which is similar to our finding of 1.96 in nonsurvivor to 0.56 in survivor. A recently Loomba et al.[32] performed a systemic review supported our finding, showed significantly higher value of CRP, neutrophil, D-dimer and LDH among nonsurvivor.

Limitation of study

First, it is a retrospective study and many biomarkers were not performed at time of admission, rather dynamic although we had excluded them. The factors affecting these parameters are not assessed like history of obesity, smoking, etc., from the hemogram are also affected by conditions such as obesity and long-term smoking.


  Conclusion Top


Biomarker such as NLR, CRP, Ferritin, LDH, and D-dimer are associated with COVID-19 mortality and can be used to predict disease progression and mortality. Among all NLR was found as best for predicting mortality.

Highlight of the study

This is one of the largest cohorts of hospitalized COVID-19 patients analyzed for association between various blood biomarker and mortality. This study showed among all blood biomarker NLR as best predictor for mortality.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
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Correspondence Address:
Deependra Kumar Rai,
Department of Pulmonary Medicine, AIIMS, Patna
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jascp.jascp_4_22



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    -  Ranjan A
    -  Pandey SK
    -  Vardhan H


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