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ORIGINAL ARTICLE  
Year : 2021  |  Volume : 64  |  Issue : 4  |  Page : 735-740
Evaluation of hematological, coagulation and inflammatory biomarker's role in predicting the severity of disease in patients with COVID-19, admitted in designated COVID-19 hospital of central India


1 Department of Pathology, NSCB Medical College, Jabalpur, Madhya Pradesh, India
2 Department of Pulmonary Medicine, NSCB Medical College, Jabalpur, Madhya Pradesh, India
3 Department of Community Medicine, NSCB Medical College, Jabalpur, Madhya Pradesh, India

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Date of Submission28-Nov-2020
Date of Decision13-Feb-2021
Date of Acceptance26-May-2021
Date of Web Publication20-Oct-2021
 

   Abstract 


Background: COVID-19 is a pandemic viral disease that has affected the Indian population very badly with more than 8.46 million cases and > 0.125 million deaths. Aim: Primary objective of the study is to establish the role of hematological, coagulation and inflammatory biomarkers in early identification of clinically severe covid-19 cases. Materials and Methods: This study was conducted from July 2020 to August 2020 at a dedicated COVID-19 referral hospital in central India. Only RT-PCR confirmed COVID-19 positive 300 cases admitted in the hospital were included in this study. Based on the clinical assessment, patients were categorised as mild, moderate, and severe groups as per ICMR guidelines. Blood samples of all cases were tested for haematological, coagulation and inflammatory biomarkers and mean values were compared among the three groups of patients. Results: 46% patients belonged to >60 years of age group. Hematological parameters like total leukocyte count, absolute neutrophil count, Neutrophil: Lymphocyte ratio, Platelet: Lymphocyte ratio significantly increased with lymphocytopenia (P=0.001). Coagulation profile(D-dimer and PT) and inflammatory biomarkers like CRP, LDH, ferritin, procalcitonin and NT- Pro BNP, all were significantly increased with severity of patients(p=0.001). ROC plotted for all the parameters between severe v/s non-severe cases showed that CRP, LDH and D-dimer had a good discriminative precision with AUC >0.8. Conclusion: We suggest that biochemical markers like CRP, LDH and D-dimer can be used as a screening tool to differentiate severe patients from non-severe patients of Covid-19 disease in order to identify severe disease at early stage for optimal utilization of resources & reducing further morbidity & mortality.

Keywords: Coagulation profile, COVID-19, disease severity, hematological parameter, inflammatory biomarker, prognosis

How to cite this article:
Lokwani D P, Yadav BS, Bharti S, Gupta V, Toppo N. Evaluation of hematological, coagulation and inflammatory biomarker's role in predicting the severity of disease in patients with COVID-19, admitted in designated COVID-19 hospital of central India. Indian J Pathol Microbiol 2021;64:735-40

How to cite this URL:
Lokwani D P, Yadav BS, Bharti S, Gupta V, Toppo N. Evaluation of hematological, coagulation and inflammatory biomarker's role in predicting the severity of disease in patients with COVID-19, admitted in designated COVID-19 hospital of central India. Indian J Pathol Microbiol [serial online] 2021 [cited 2021 Dec 7];64:735-40. Available from: https://www.ijpmonline.org/text.asp?2021/64/4/735/328521





   Introduction Top


The etiology of ongoing pandemic pneumonia outbreak as declared by the World Health Organization (WHO) is the novel coronavirus named severe acute respiratory syndrome corona virus-2 (SARS-CoV-2) responsible for coronavirus disease-2019 (COVID-19).[1]

As per COVID-19 data, shared by WHO on November 7, 2020, India had 8.46 million confirmed cases with 0.125 million deaths.[2] Identification of prognostic biomarkers for progression of disease toward clinical worsening and mortality are of paramount importance.[3] An early differentiation of mild, moderate, and severe cases is needed to optimize limited human and other technical resource usage, especially in developing countries like India.


   Material and Methods Top


Study oversight

This record-based cross-sectional study was conducted from July 2020 to August 2020 at a dedicated COVID-19 referral hospital of Central India. The study was approved by the Institutional Ethical Committee on 21-07-2020. In this study, the patient's identity was de-identified, so the requirement to take consent was waived off by the Institutional Ethical Committee. Only COVID-19-positive cases that were confirmed by RT-PCR (real-time polymerase chain reaction) test admitted in the hospital were included in this study. At the time of admission, three whole blood samples were collected and tested at the institutional laboratory: firstin ethylenediamine tetraacetic acid (EDTA) vial for hemogram, second in citrate vial for coagulation profile, and last one in the plain vial for biomarkers. All the EDTA samples were run on a fully automated hematology analyzer (Mindray BC3600) for hemogram. Total leukocyte count (TLC), absolute neutrophil count (ANC), absolute lymphocyte count (ALC), platelet count, and other parameters were documented in all cases. NLR (neutrophil-to -lymphocyte ratio) and PLR (platelet-to-lymphocyte ratio) were calculated. Prothrombin time (PT) and D-dimer tests were performed by coagulometer (STAGO-SATLLITE) on all samples and were collected in sodium citrate vial. Serum was separated from all the plain vial samples and was used to estimate C-reactive protein (CRP), lactate dehydrogenase (LDH), ferritin, procalcitonin, and N-terminal pro–b-type natriuretic peptide (NT-Pro BNP) on (Randox mola) clinical chemistry analyzer.

Data collection

Demographic, clinical, and laboratory investigation data were collected from patient's medical record from the medical record section. The severity of patients with COVID-19 was classified as mild, moderate, and severe at the time of admission as per Indian Council of Medical Research (ICMR) guideline version-3, published on date 13 June 2020 for patient with COVID-19.[4]

Statistical analysis

Data were entered in Microsoft Office 2007 Excel spreadsheet and analyzed by using the Statistical Package for the Social Sciences (SPSS) software program, version 26.0 (IBM, Armonk, New York). Chi-square test was used to analyze association between two variables. The quantitative variables such as hematological parameters, coagulation profile, and inflammatory biomarkers were expressed as mean ± standard deviation. One-way analysis of variance (ANOVA) was used to asses difference between two means (a value of P < 0.05 was considered statistically significant). Fisher's least significant difference (LSD) was also used to find out association within the group.

The diagnostic cutoff values of the parameters for differentiating severe cases of patients with COVID-19 from nonsevere were calculated by receiver-operating characteristic (ROC) and area under the ROC curve (AUC). The parameters with AUC >0.8 and with statistical significance (P < 0.05) were considered to have good discriminative precision. Best diagnostic cutoff was selected with values corresponding to maximum sensitivity and specificity.


   Results Top


In our study, clinical and laboratory investigation data of 300 patients were collected at the time of their admission. Of these, 134 (44.7%) cases were categorized as severe, 68 (22.7%) as moderate, and 98 (32.7%) as mild COVID-19 disease according to the ICMR guidelines for categorization. We observed that COVID-19 infection showed male predominance with 206 (68.7%) males and 94 (31.3%) female patients.

Age of the patients varied from 19 years to 99 years with maximum 137 (46%) patients belonged to >60 years of age group followed by 45–59 years age group (32.6%). Another important finding was that with increasing age, severity of illness increased significantly in all categories (P = 0.004) [Table 1].
Table 1: Age wise distribution of COVID-19 cases as per disease

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The hematological parameters according to the severity of patients as summarized in [Table 2] and [Table 3] show a clearcut difference in mean values. It reflected that TLC, ANC, NLR, and PLR significantly increased with severity of disease, while ALC significantly decreased in patients with severe disease (P = 0.001). As per Fisher's LSD analysis [Table 3] difference between mean value of ALC, PLR with severity (i.e. moderate and severe level of disease) was found to be insignificant. Hemoglobin, platelet count, mean platelet volume (MPV), and platelet distribution width (PDW) showed no significant differences among different severity groups.
Table 2: Mean Hematological parameters of COVID-19 positive patients according to disease severity

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Table 3: Association between haematological parameters with levels of disease severity (Fisher's Least significant difference (LSD) analysis)

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[Table 4] and [Table 5] show data of coagulation profile and inflammatory biomarkers. D-dimer significantly increased with severity of the disease, whereas PT/INR was significantly higher (P = 0.001) among severe patients as compared to the mild group of patients.
Table 4: Mean coagulation profile and inflammatory biomarkers of COVID-19 positive patients according to disease severity

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Table 5: Association between Coagulation profile and inflammatory biomarkers with levels of disease severity (Fisher's Least significant difference (LSD) analysis)

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Inflammatory biomarkers such as CRP, LDH, ferritin, procalcitonin, and NT-Pro BNP all increased significantly with severity of patients, whereas difference of mean procalcitonin and mean NT-Pro BNP was observed between the mild and moderate group of cases, which was not significant [Table 4] and [Table 5].

For discriminative precision and finding cutoff value for different parameters, ROC was plotted for all the hematological, coagulation, and inflammatory biomarkers between severe and nonsevere (mild and moderate) cases. As shown in [Table 6], CRP, LDH, and D-dimer has shown a good discriminative precision with AUC >0.8, whereas procalcitonin, ferritin, Pro-BNP, and ANC/ALP ratio has shown a fair (AUC = 0.7–0.8) discriminative precision between severe and nonsevere patients with COVID-19. Rest of the other markers evaluated were found to be poor in discriminative precision (AUC <0.7).
Table 6: The area under the receiver-operating characteristic (ROC) curve (AUC) for significant parameters of patients with COVID-19

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CRP had a significant (P = 0.001) discriminative value with AUC = 0.852 (95% confidence interval [CI] =0.794–0.911) and optimal threshold value was ≥48 mg/L, which was associated with a sensitivity of 82% and specificity of 81%. LDH levels had a significant (P = 0.001) discriminative value with AUC = 0.809 (95% CI = 0.745–0.873) and a cutoff value of ≥403 IU/L (sensitivity = 76%, specificity = 65%). D-dimer levels had a significant (P = 0.001) discriminative value with AUC = 0.803 (95% CI = 0.735–0.870) and a cutoff value of ≥461 ng/mL (sensitivity = 75%, specificity = 69%).


   Discussion Top


In the study, we included 300 COVID-19-positive cases confirmed by RT-PCR. Based on clinical assessment at the time of admission, patients with COVID-19 were categorized into mild, moderate, and severe groups according to ICMR guidelines. As this study was conducted at a COVID-19 referral tertiary care institute hospital, severe patients 143 (44.7%) were more as compared to mild and moderate patients.

We found comparatively more elderly patients with COVID-19 especially in the severe category (P = 0.004) [Table 1] with a higher proportion of men (68.2%) than women. Singh et al.[3] in India and Wang et al.[5] in China also found more elderly patients, severely affected with male predominance.

The primary focus of our study was to assess the prognostic significance of the laboratory investigations of patients with COVID-19, which included hematological, coagulation profile, and inflammatory biomarkers. In respect of hematological parameters, laboratory reports of severe patients showed higher level of TLC (12.67 vs. 8.24 × 103/μL; P = 0.001) and ANC (9.98 vs. 5.21 × 103/μL; P = 0.001), whereas ALC (1.51 vs. 2.18 × 103/μL; P = 0.001) were decreased. Similar to our study, Qin et al.,[6] Huang et al.,[7] and Zhang et al.[8] in China also found a higher level of TLC and ANC and decrease ALC (P < 0.001). Hu et al.[9] found that 85% of critical patients had neutrophilia. Lymphocytopenia was the most consistent and prominent finding, especially among severe patients. The cause of this lymphocytopenia is the affinity of coronavirus for lymphocytic ACE receptor leading to cytopathic effect and lymphocyte apoptosis due to neutrophilia as an exaggerated inflammatory response.

In our study, we observed an increase in ANC and a decrease in ALC and thus NLR (9.36 vs. 3.02; P = 0.0001) was significantly increased. Qin et al.,[6] Huang et al.,[7] and Zhang et al.[8] also reported similar findings. Platelet count did not show any significant difference between the groups but PLR (214.42 vs. 144.31 × 109/L; P = 0.0001) significantly increased in severe patients. Gong et al.[10] also found the same, which is due to lymphocytopenia.[11],[12] [Table 2] and [Table 3].

A significant increase was observed in coagulation profile tests (PT and D-dimer) of patients with COVID-19 with severe disease as compared to mild disease, where PT (14.48 vs. 12.7 s; P = 0.000) and D-dimer (2605.65 vs. 328.54 ng/ml; P = 0.000) were significantly increased. Huang et al.[7] also found that PT and D-dimer levels were higher in ICU patients with COVID-19 (P < 0.001). Tang et al.[13] reported that in nonsurvivors D-dimer and fibrinogen degradation product (FDP) levels were significantly high, and prolonged PT as compared to survivors, on admission. Patients presenting with viral infection may develop sepsis associated with organ dysfunction. Sepsis is well established as one of the most common causes of disseminated intravascular coagulation (DIC).DIC develops when monocytes and endothelial cells are activated to the point of cytokine release following injury, with expression of tissue factor and secretion of Von Willebrand factor. Levels of fibrin-related markers (D-dimer and FDP) are moderately or markedly elevated in all deaths due to COVID-19.[14] [Table 4] and [Table 5].

Cytokines play an important role in pathogenesis of COVID-19 and lead to increase levels of inflammatory biomarkers. The inflammatory biomarkers such as LDH (656.26 vs. 304.57 IU/L; P = 0.001), CRP (136.49 vs. 17.71 mg/L; P = 0.001), ferritin (875.5 vs. 207.32 ng/mL; P = 0.001), procalcitonin (2.09 vs. 0.17; P = 0.001), and NT Pro-BNP (3284.21 vs. 191.33 pg/mL; P = 0.001) were significantly high in severe patients' group compared to mild and moderate groups [Table 4] and [Table 5].

Guan et al.[15] from China found that CRP was elevated in 60.7% of patients. The elevated level of procalcitonin indicates a secondary bacterial infection, complicating the clinical course of COVID-19 disease, which was found elevated in 5.5% cases, whereas elevated LDH in 41% of patients. More severe cases show a marked increase compared with the nonsevere ones (81.5% vs. 56.4% for CRP, 13.7% vs. 3.7% for procalcitonin and 58.1% vs. 37.2% for LDH).

Zhou et al.[16] included 191 patients with COVID-19 in their study in China, and reported that nonsurvivors, as compared with survivors, had high level of LDH (P < 0.001), procalcitonin (P < .001), serum ferritin levels (P < .001), and IL-6 (P < .001). Another researcher also found a positive correlation between CRP concentration with the lung lesion, acute kidney injury, and extent of the cardiac injury.[17]

Some researchers also reported increase LDH associated with a higher risk of ARDS, ICU support, and death. Higher CRP has been linked to unfavorable aspects of COVID-19 disease, such as ARDS development, higher troponin-T levels, myocardial injury, and death.[18] A meta-analysis of four published studies shows that increased procalcitonin values are associated with a nearly five-fold higher risk of severe infection (OR = 4.76; 95% CI: 2.74–8.29, I2 = 34%).[19]

Sun et al.[20] found that serum ferritin levels were significantly high in the severe group compared to the mild group (P < 0.000). Ferritin level can be affected by serum iron status in body and may indicate hyperimmune state. It is a marker for hemophagocytic lymphohistiocytosis, which is a known complication of viral infection.[21],[22] In a meta-analysis, Pranata et al.[23] revealed that elevated NT-proBNP levels are associated with increased mortality in COVID-19 pneumonia.

ROC was plotted to analyze the discriminative precision of hematological, coagulation, and inflammatory biomarkers for severe cases v/s nonsevere cases and we observed that CRP, LDH, and D-dimer has a good discriminative precision with AUC >0.8, while procalcitonin, ferritin, Pro-BNP, and ANC/ALP ratio has shown a fair discriminative precision (AUC = 0.7–0.8) [Figure 1] and [Table 6].
Figure 1: ROC for significant parameters to discriminate severs cases from non-severe cases

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We also found that the best threshold value of CRP to differentiate severe patients from nonsevere patients was ≥4 8 mg/L with a sensitivity of 82% and specificity of 81%. Similarly, LDH also has a very good discriminative power with a cutoff value of ≥403 IU/L, with a sensitivity 76% and specificity 65%. D-dimer was the third parameter that was found very useful for discriminative precision for severe cases v/s non-severe cases with an optimal cutoff value of ≥461 ng/mL, with sensitivity 75% and specificity 69%.


   Conclusion Top


We conclude that hemocytometric changes (such as TLC, ANC, and NLR) in patients with COVID-19 are elevated and lymphocytopenia is also seen. Among the severe category of patients, significant elevation of coagulation profile tests (D-dimer and PT) is observed. Inflammatory biomarkers such as CRP, LDH, ferritin, procalcitonin, and NT-Pro BNP are significantly raised among severe patients of COVID-19. On the basis of our findings, we suggest that CRP, LDH, and D-dimer can be used as a screening tool to differentiate severe patients from nonsevere patients of COVID-19 in order to identify at early stage, those who will require ICU and proper monitoring to reduce unnecessary burden on tertiary care hospital (dedicated COVID Hospitals) in terms of human resource, oxygen beds, and other logistics. This can also help in timely identification of severe cases which can be provided ICU care, further reducing morbidity and mortality due to COVID-19 infection.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
   References Top

1.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A Novel corona virus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727-33.  Back to cited text no. 1
    
2.
WHO Corona virus Disease (COVID-19) Dashboard. Geneva: World Health Organization; c2020. [Last accessed 2021 Nov 26]. Available from: https://covid19.who.int.  Back to cited text no. 2
    
3.
Singh P, Kumar A, Singh S, Kelkar A, Doshi P, Nimbargi RC, et al. Utility of routine haematological parameters and infectious biomarkers to assess the disease severity in COVID-19 positive patients, analysis and early trend from India. 10.21203/rs. 3.rs-40378/v1 [Preprint]. 2020. [Last accessed 2020 Nov 26]. Available from: https://www.researchsquare.com/article/rs-40378/v1.  Back to cited text no. 3
    
4.
Clinical management protocol: Covid 19. Delhi: Govt. of India, Ministry of family welfare. 2020. [Last accessed 2021 Mar 21]. Available from: https://www.mohfw.gov.in/pdf/UpdatedClinicalManagement ProtocolforCOVID19dated03072020.pdf.  Back to cited text no. 4
    
5.
Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 Novel Coronavirus-Infected pneumonia in Wuhan, China. JAMA 2020;323:1061-9.  Back to cited text no. 5
    
6.
Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, et al. Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin Infect Dis 2020;71:762-8.  Back to cited text no. 6
    
7.
Huang J, Cheng A, Lin S, Jhu Y, Chen G. Individualized prediction nomograms for disease progression in mild COVID-19. J Med Virol 2020;92:2074-80.  Back to cited text no. 7
    
8.
Zhang G, Hu C, Luo L, Fang F, Chen Y, Li J, et al. Clinical features and outcomes of 221 patients with COVID-19 in Wuhan, China. J Clin Virol 2020;127:104364.  Back to cited text no. 8
    
9.
Hu L, Chen S, Fu Y, Gao Z, Long H, Ren HW, et al. Risk factors associated with clinical outcomes in 323 COVID-19 patients in Wuhan, China. Clin Infect Dis 2020;71:2089-98.  Back to cited text no. 9
    
10.
Gong J, Ou J, Qiu X, Jie Y, Chen Y, Yuan L, et al. A Tool to early predict severe 2019-novel coronavirus pneumonia (COVID-19): A multicenter study using the risk nomograms in Wuhan and Guangdong, China. Clin Infect Dis 2020;71:833-40.  Back to cited text no. 10
    
11.
Xu H, Zhong L, Deng J, Peng J, Dan H, Zeng X, et al. High expression of ACE2 receptor of 2019-nCoV on the epithelial cells of oral mucosa. Int J Oral Sci 2020;12:8.  Back to cited text no. 11
    
12.
Tan L, Wang Q, Zhang D, Ding J, Huang Q, Tang Y-Q, et al. Correction: Lymphopenia predicts disease severity of COVID–19: A descriptive and predictive study. Signal Transduct Target Ther 2020;5:61.  Back to cited text no. 12
    
13.
Tang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel corona virus pneumonia. J Thromb Haemost 2020;18:844-7.  Back to cited text no. 13
    
14.
Kitchens CS. Thrombocytopenia and thrombosis in Disseminated intravascular coagulation (DIC). Hematology Am Soc Hematol Educ Program 2009:240-6. doi: 10.1182/asheducation-2009.1.240.  Back to cited text no. 14
    
15.
Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of corona virus disease 2019 in China. N Engl J Med 2020;382:1708-20.  Back to cited text no. 15
    
16.
Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult in patients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020;395:1054-62.  Back to cited text no. 16
    
17.
Sahu BR, Kampa RK, Padhi A, Panda AK. C-reactive protein: A promising biomarker for poor prognosis in COVID-19 infection. Clinica Chimica Acta 2020;509:91-4.  Back to cited text no. 17
    
18.
Terpos E, Ntanasis-Stathopoulos I, Elalamy I, Kastritis E, Sergentanis TN, Politou M, et al. Hematological findings and complications of COVID-19. Am J Hematol 2020;95:834-47.  Back to cited text no. 18
    
19.
Lippi G, Plebani M. Procalcitonin in patients with severe corona virus disease 2019 (COVID-19): A meta-analysis. Clin Chim Acta 2020;505:190-1.  Back to cited text no. 19
    
20.
Sun Y, Dong Y, Wang L, Xie H, Li B, Chang C, et al. Characteristics and prognostic factors of disease severity in patients with COVID-19: The Beijing experience. J Autoimmun 2020;112:102473.  Back to cited text no. 20
    
21.
Grangé S, Buchonnet G, Besnier E, Artaud-Macari E, Beduneau G, Carpentier D, et al. The use of ferritin to identify critically ill patients with secondary hemophagocytic lymphohistiocytosis. Crit Care Med 2016;44:e1045-53.  Back to cited text no. 21
    
22.
Lin TF, Ferlic-Stark LL, Allen CE, Kozinetz CA, McClain KL. Rate of decline of ferritin in patients with hemophagocytic lymphohistiocytosis as a prognostic variable for mortality. Pediatr Blood Cancer 2011;56:154-5.  Back to cited text no. 22
    
23.
Pranata R, Huang I, Lukito AA, Raharjo SB. Elevated N-terminal pro-brain natriuretic peptide is associated with increased mortality in patients with COVID-19: Systematic review and meta-analysis. Postgrad Med J 2020;96:387-91.  Back to cited text no. 23
    

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Correspondence Address:
Bhagwan S Yadav
Department of Pathology, NSCB Medical College, Jabalpur, Madhya Pradesh
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/IJPM.IJPM_1350_20

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