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ORIGINAL RESEARCH Table of Contents  
Ahead of print publication
Utility of hematological and biochemical parameters as a screening tool for assessing coronavirus disease 2019 infection and its severity


1 Department of Biochemistry, Hamdard Institute of Medical Science and Research, Jamia Hamdard, New Delhi, India
2 Department of Pathology, Hamdard Institute of Medical Science and Research, Jamia Hamdard, New Delhi, India
3 Department of Medicine, Hamdard Institute of Medical Science and Research, Jamia Hamdard, New Delhi, India
4 Department of Community Medicine, Hamdard Institute of Medical Science and Research, Jamia Hamdard, New Delhi, India

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Date of Submission02-Jul-2022
Date of Decision17-Sep-2022
Date of Acceptance30-Sep-2022
Date of Web Publication19-Jan-2023
 

  Abstract 


Background: The rapidly evolving pandemic of Coronavirus disease 2019 (COVID-19) has presented with clinical severity, which varies from asymptomatic cases to being fatal in others. The need of the hour is to find meaningful and cost-effective COVID-19 biomarkers out of conventional hematological and biochemical parameters, which will help in the early identification of patients with a poor prognosis, leading to timely intervention. Aim: The aim was to analyze different biochemical and hematological parameters in COVID-19 patients and also to study the association of these parameters with disease severity. Materials and Methods: Cross-sectional observational study was carried out on 100 COVID-19 patients from a hospital from July to October 2020. Based on saturation of oxygen (SpO2), admitted patients were grouped into mild–moderate (SpO2 ≥90%) and severe groups (SpO2 <90%). Hematological and biochemical parameters were studied in both groups, and association with disease severity was analyzed. Results: Out of 100 patients, 57 patients were seen in the mild–moderate group (SpO2 ≥90%), while 43 patients (SpO2 <90%) belonged to the severe category. Males were predominant in both mild–moderate and severe groups. Among the hematological parameters, statistically significant higher values of absolute neutrophil count (P = 0.046) and significantly lower absolute lymphocyte count (P = 0.003) values were observed. With regard to biochemical parameters, increased urea and decreased total protein were found in the severe category and this association was statistically significant. Conclusion: To conclude, early identification and monitoring of hematological and biochemical parameters, especially those associated with higher disease severity, may contribute toward improving disease outcomes.

Keywords: Coronavirus disease 2019, disease severity, laboratory parameters


How to cite this URL:
Alam S, Khan S, Jain V, Kashyap V, Kapur P. Utility of hematological and biochemical parameters as a screening tool for assessing coronavirus disease 2019 infection and its severity. J Microsc Ultrastruct [Epub ahead of print] [cited 2023 Feb 8]. Available from: https://www.jmau.org/preprintarticle.asp?id=368034





  Introduction Top


Novel coronavirus disease originated in 2019 which was caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).[1],[2] It was named as Coronavirus Disease 2019 (COVID-19) by the WHO on February 11, 2020. On March 11, 2020, it was declared a global pandemic. By May 19, 2021, there were 164,901,667 cases of COVID-19, including 3,418,730 deaths, as reported globally by the WHO.[3]

The exact etiopathogenesis of this disease is not known. Studies have shown that COVID-19 could trigger more secretion of T-helper-2 cytokines that decrease inflammation.[4] Furthermore, SARS-CoV-2 is supposed to infect cells via the receptors of angiotensin-converting enzyme 2 (ACE-2) and transmembrane serine protease 2. These trigger activation of monocytes and macrophages, T-cells, and antibody production (B-cell mediated). Finally, it leads to the death of host cells.[5]

The clinical features of COVID-19 are very diverse which range from mild symptoms to rapidly developing acute respiratory distress syndrome to even death. In majority of cases, COVID-19 had a good prognosis. However, the requirement of mechanical ventilation or multiple organ failure was seen in 5% of the infected patients, depending on age and comorbidities.[6],[7] Hence, the rapidly evolving pandemic of COVID-19 presented with clinical severity, causing death in some cases while no symptoms in others.[1],[8]

Most of the diagnostic strategies for COVID-19 rely on clinical signs and imaging techniques or more sophisticated inflammatory markers that are costly and not easily available, especially in low-resource settings. Few studies have been done on the laboratory abnormalities in these patients presenting with variable severity.[9],[10] However, the results of routine parameters (hematological and biochemical) in our study patients have been very conflicting, with few studies showing a strong association with disease severity while few completely refuting it.[11]

To the best of our knowledge, very little Indian data are available linking routine hematological and biochemical parameters with disease severity and prognosis. Therefore, with this background in mind, we plan to investigate patients with the confirmed diagnosis who were admitted to our hospital. The purpose was to explore or identify different biochemical and hematological parameters which may aid in assessing the severity of COVID-19 infection so as to provide new insights for improving disease outcome and its prognosis.


  Material and Methods Top


Study design

Cross-sectional observational study.

Study group

Hospitalized patients in the COVID ward or intensive care unit of a tertiary care center in New Delhi.

Duration of study

Four months (from July to October 2020).

Sample size

One hundred patients.

Operational definitions

COVID-19 diagnosis was made by WHO-approved kits based on real-time reverse transcription polymerase chain reaction. Admitted patients were categorized into mild–moderate (SpO2 ≥90%) and severe cases (SpO2 <90%) based on oxygen (SpO2) saturation according to the Ministry of Health and Family Welfare Government of India Revised Guidelines on clinical management of COVID-19.[12]

Consent (informed) was taken from the patients. Our study was approved by the institutional ethics committee. The identity of the subject was not revealed as data has been used in anonymized form.

Baseline data collection

For each subject, demographic data were taken. Furthermore, the clinical findings of the patients during hospitalization and routine investigations (hematological and biochemical) were gathered from electronic medical records. A history of comorbid conditions (hypertension, diabetes mellitus (DM), cerebrovascular disease, chronic obstructive pulmonary disease, cancer, etc.) was taken. The presence of symptoms and its duration was noted. Hematological and biochemical variables were critically analyzed in all hospitalized patients of COVID-19 infection when admitted. Blood samples were drawn before starting the treatment. The samples were tested for complete blood count (CBC) on six-part hematology analyzer (Sysmex XN-1000). Biochemical investigations (liver function tests [LFT] and kidney function test [KFT]) were done on Beckman AU480 Chemistry Analyzer. All data were recorded in a predesigned proforma. Patients with incomplete information on medical records and those who sought transfer to other medical facilities were excluded from our study.

Statistical analysis

Data were systematically collected and compiled. Mean values of variables were compared against normal ranges, and observations were tabulated and expressed as mean ± standard deviation Independent t-test was applied to. P < 0.05 was considered statistically significant. We calculated the standard error of the mean also. Data were analyzed using IBM SPSS Statistics for Windows, version 26 (IBM Corp, Armonk, N.Y., USA).


  Results Top


One hundred patients with confirmed infection from SARS-CoV2 were taken in our study.

Demographic characteristics of the study population

Fifty-seven patients were seen in mild–moderate group (SpO2 ≥90%), while 43 patients (SpO2 <90%) belonged to the severe category. The patients'age in the mild group was 46.91 ± 16.759, whereas in the severe group, it was 57.74 ± 16.125. Patients in the severe group had significantly higher mean age than that in the mild category (P < 0.05). There were 35 males (61.4%) and 22 females (38.6%) in the mild group, whereas in the severe group, there were 33 (76.7%) males and 10 (23.3%) females.

Clinical profile of study population

Patients' symptoms varied from fever, cough, diarrhea, and breathlessness to severe symptoms such as multi-organ failure. At the time of admission in the hospital and during the course of the study, the most common symptoms noted in mild cases were fever (70.1%), loss of appetite (49.1%), loss of taste, cough (42.1%), chills, dyspnea (26.3%), and body ache (21%). The most prevalent symptoms in severe cases were dyspnea which was seen in 86%, followed by fever in 76.7% of patients. However, there was no case of diarrhea in the severe category. Furthermore, diarrhea and loss of taste were statistically significant (P < 0.05) in the mild category. Among all symptoms, dyspnea was most commonly reported in the severe category and it was statistically significant (P < 0.05) [Table 1].
Table 1: Demographics and baseline characteristics of patients with COVID-19 patients

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The most prevalent comorbidity in both mild and severe cases was DM (52.6% in mild cases, whereas 46.5% in severe cases), followed by hypertension (29.8% in mild cases and 41.8% in severe cases) [Table 1].

Laboratory profile of study population

Hematological parameters

The hematological profile [Table 2] revealed a higher mean total leukocyte count in severe cases, but it was not significant on the comparison (P = 0.158) with mild cases. In our study, it was seen that Absolute neutrophil count (ANC) was higher in severe cases as compared to milder ones. This difference was statistically significant. It reflected in the percentage of polymorphs which was higher in severe cases of differential leukocyte count, and the difference was also statistically significant (P < 0.05). Furthermore, patients having severe COVID-19 had significantly lower Absolute lymphocyte count (ALC) (P = 0.003). The mean value of platelet count was slightly less in the severe category as compared to the mild category. However, both were within the normal ranges. Furthermore, the percentage of lymphocytes on differential leukocyte count was decreased in the severe group in contrast to mild cases (P < 0.05). In addition, the percentage of monocytes was increased in severe cases and the difference was found to be statistically significant (P = 0.017). Although eosinopenia was seen in both categories, the difference was not statistically significant. The mean value of Neutrophil-to-Lymphocyte ratio (NLR) was 5.08 ± 3.46 in mild–moderate group, while the mean was 12.78 ± 9.34 in the severe group. It was found to be statistically significant. The mean value of platelet-to-lymphocyte ratio (PLR) was 11.75 ± 9.84 in mild–moderate group, while the mean was 29.73 ± 19.10 in the severe group. It was also found to be statistically significant. The mean value of monocyte-to-lymphocyte ratio (MLR) was 0.56 ± 0.34 in the mild–moderate group, while the mean was 0.86 ± 0.56 in the severe group. It was not found to be statistically significant in our study.
Table 2: Comparison of hematological parameters among COVID-19 patients

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Biochemical parameters

Amongt the biochemical parameters, urea in severe cases was significantly higher as compared to the milder group (P < 0.05). It was seen in our study that serum creatinine was raised in the severe group as compared to the mild group, but it was not found to be statistically significant. Total protein was also slightly lower in the severe category and this association was seen to be statistically significant. Furthermore, our findings revealed that uric acid, albumin, and globulin were in the normal range in both categories. Our study also reiterated that aspartate aminotransferase (AST) and aminotransferase (ALT) were elevated in severe cases. However, the difference was not statistically significant [Table 3].
Table 3: Comparison of biochemical parameters among COVID-19 patients

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  Discussion Top


As the coronavirus pandemic progresses, a need was felt for assessing laboratory markers to analyze the progression of disease.[13]

This study was conducted in a hospital in Delhi, which primarily caters to the lower socioeconomic population located in urban slums around the hospital. In India and many developing countries around the world, where there are financial limitations as well adequate facilities are not available, it is very difficult for a physician to decide about the prognosis of such an unpredictable disease like COVID-19. This study analyzed clinical history, CBC, KFT, and LFT, which are readily available investigations even in peripheral parts of India.

In our study, we have categorized 100 patients into mild–moderate and severe categories and described and attempted to correlate the clinical findings, hematological and biochemical profile of COVID-19 disease. It was seen that the age of patients in the severe category was more as compared to the mild category. This was in concordance with other studies which suggested that age may be a risk factor and could be responsible for poor outcomes.[14],[15]

In our study, male predominance was seen. These findings were comparable with other studies.[16],[17],[18] Several factors, including sex hormones, higher incidence of smoking, and raised ACE-2 expression, may be responsible for the higher number of cases in males.

With regard to clinical characteristics of COVID-19, fever was not present in 30% of cases. Although fever being the most common symptom, it was not the hallmark feature of COVID-19 in our study. Other studies also showed that fever was present in 91.7% of cases.[6],[19] Furthermore, in our study, dyspnea was the presenting complaint in 86% of cases in the severe category, which can be attested by the fact that the lung is the primary target organ of SARS-CoV-2 and the virus gains entry through ACE-2 receptors.[20] In addition, loss of taste, loss of smell, and diarrhea were good prognostic indicators in our study. Studies have suggested that mucosal inflammation is the possible reason behind anosmia, as seen in our patients.[21]

The hematological profile revealed a higher mean white blood cell count in severe cases, but it was not significant. According to the results of meta-analysis done, WBC count was significantly more in nonsurvivors. It was also seen that leucocyte count elevated mildly in severe COVID-19 patients, while those patients with a significant rise in WBC count predicted a poorer outcome.[22] The mechanisms which contribute to increased WBC count in severe COVID-19 remain unclear. It should be kept in mind that a high WBC count could be due to rampant usage of steroids in severe diseases or might be a superadded bacterial infection.

In addition, ANC was higher in severe cases as compared to milder ones. Furthermore, patients having severe COVID-19 had reduced ALC, which was consistent with the findings of a study done by Terpos.[23] In another study done by Yuan et al., it was seen that most patients had reduced lymphocyte counts in severe/critical patients (P < 0.01).[24] The virus attaches to ACE-2 receptors on lymphocytes and results in depleted lymphocyte count. It could also be due to immune response to SARS-CoV-2 infection. It may also be due to a direct attack of coronavirus on lymphocytes.[25]

In our study, the percentage of polymorphs on differential lymphocyte count was more in severe cases as compared to the milder group. This difference was found to be statistically significant (P < 0.05). Furthermore, our study revealed a significant decrease in the percentage of lymphocytes in the severe group in contrast to mild cases (P < 0.05). Our results were supported by an earlier study done by Lombardi et al., which also showed lymphopenia in 80.9% of patients. Lymphopenia could be the consequence of an ongoing infection by virus. It was seen more in those cases with a severe outcome. In our study, monocytes were increased in severe cases, and the difference was found to be statistically significant as compared to mild cases (P < 0.05).[26] Our results were consistent with an earlier study which showed that monocyte count increases in patients with COVID-19 in contrast to influenza patients. Moreover, the mechanism which could lead to monocytes alteration is not clear.[27],[28] However, significant eosinopenia was not seen in our study, which was in contrast with another study done by Zhang et al.[29]

Thrombocytopenia is a very common manifestation of COVID-19 and is reported in 5%–40% of cases. Studies have revealed that platelet count was normal in many patients at the time of admission to the hospital, which is concordant with our study. Furthermore, thrombocytopenia was present and associated with an increased risk of mortality in other studies.[30],[31] However, in our study, thrombocytopenia was not a prominent feature, even in severe cases. The reason behind variable findings in other studies could be due to the duration of illness and different timings at which these tests are done.

Moreover, it was seen that in severe COVID-19 patients, parameters such as NLR and PLR MLR showed the hematological profile in a much better way when we compared these inflammatory indices to cell counts. Our study reiterated that NLR was increased in patients with severe disease, as seen in other studies also.[32],[33],[34],[35] Qu et al.[36] implicated that PLR correlated with cytokine storm. It may serve as a newer inflammatory marker for assessing the severity of COVID-19 patients. Furthermore, MLR also showed significant differences, as seen in other studies.[33],[35],[37]

Amongst the biochemical parameters, it was seen that urea in severe cases was significantly more in comparison to the milder group. Serum creatinine was also raised in the severe group as compared to the mild group, but it was not found to be statistically significant. Our result was supported by another study, in which Li et al. showed that 31% of patients had increased blood urea nitrogen and 22% showed raised serum creatinine.[28] The exact mechanism behind this is not clear and could be due to SARS-CoV-2 binding in nephrons through ACE-2 receptors.[38],[39] Moreover, normal kidneys have higher ACE-2 expression than lung tissue. Earlier studies also revealed changes in kidney alterations as increased serum creatinine was seen in our patients.[40] Many studies have described hypoalbuminemia in patients with COVID-19.[41] In our study, total protein was decreased in severe cases as compared to the mild category and it was found to be statistically significant. Although albumin and globulin were slightly decreased in the severe category as compared to the mild, it was not statistically significant. Several studies have suggested that hypoproteinemia in COVID-19 is associated with markedly elevated inflammatory cytokines and coagulation profiles.[42]

The changes in values of liver biomarkers, such as aspartate AST, ALT, and bilirubin are quite common in affected patients. However, liver function parameters (ALP, total bilirubin, including direct and indirect bilirubin) in our study were within the normal range in both categories and did not show any significant difference among the mild and severe groups. In a study by Cai et al., total bilirubin was increased, and no increase in ALP was found.[43] Our study also showed that AST and ALT were elevated in severe cases compared to milder cases, but it was not statistically significant in both parameters. This was discordant with the results of other studies in which significant elevation in liver enzymes (ALT and AST) was seen.[6] However, the mechanism is not clear and it was seen that hepatocytes express ACE-2 receptors. However, some studies have suggested that cytokine storm related to pneumonia could cause liver injury, leading to hepatic insufficiency.[44]

On extensive review of literature, we came across very few Indian studies on the association of laboratory parameters, particularly hematological findings, with COVID-19 infection.[45],[46] Our study was done on 100 patients of COVID-19 infection with an aim to establish the association between routinely employed laboratory markers and the severity of COVID-19 infection, which was similar to the study by Pujani et al.[35]

Limitations of the study

The sample size could have been larger; however, this study can pave the way for large-scale studies with a larger sample size. Furthermore, the correlation of these basic parameters with inflammatory parameters such as C-reactive protein, lactate dehydrogenase, ferritin, and interleukin 6 can be done in further studies.


  Conclusion Top


To conclude, this study explored different biochemical and hematological parameters for predicting an adverse outcome in COVID-19 patients. It helped us in identifying few cost-effective conventional laboratory parameters, such as ANC, ALC, urea, and total protein, which were found to be significantly associated with the severity of the disease. Thus, using these routine tests at the time of admission can help in risk stratification and better management to timely identify the complications and improve the disease outcome. Thus, early identification of these parameters can help in monitoring the disease and predicting severity. The need of the hour is to find meaningful and cost-effective COVID-19 biomarkers out of conventional biochemical and hematological tests for a better understanding of the disease.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
  References Top

1.
Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020;395:507-13.  Back to cited text no. 1
    
2.
Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, 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;8:475-81.  Back to cited text no. 2
    
3.
Worldometers. COVID-19 Coronavirus Pandemic. Worldometers. Available from: https://www.worldometers.info/coronavirus/. [Last updated on 2021 May 19].  Back to cited text no. 3
    
4.
Mahallawi WH, Khabour OF, Zhang Q, Makhdoum HM, Suliman BA. MERS-CoV infection in humans is associated with a pro-inflammatory Th1 and Th17 cytokine profile. Cytokine 2018;104:8-13.  Back to cited text no. 4
    
5.
Tay MZ, Poh CM, Rénia L, MacAry PA, Ng LF. The trinity of COVID-19: Immunity, inflammation and intervention. Nat Rev Immunol 2020;20:363-74.  Back to cited text no. 5
    
6.
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. 6
    
7.
Wang C, Horby PW, Hayden FG, Gao GF. A novel coronavirus outbreak of global health concern. Lancet 2020;395:470-3.  Back to cited text no. 7
    
8.
Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: A model-based analysis. Lancet Infect Dis 2020;20:669-77.  Back to cited text no. 8
    
9.
Zhao K, Li R, Wu X, Zhao Y, Wang T, Zheng Z, et al. Clinical features in 52 patients with COVID-19 who have increased leukocyte count: A retrospective analysis. Eur J Clin Microbiol Infect Dis 2020;39:2279-87.  Back to cited text no. 9
    
10.
Bennouar S, Bachir Cherif A, Kessira A, Hamel H, Boudahdir A, Bouamra A, et al. Usefulness of biological markers in the early prediction of corona virus disease-2019 severity. Scand J Clin Lab Invest 2020;80:611-8.  Back to cited text no. 10
    
11.
Zhang C, Shi L, Wang FS. Liver injury in COVID-19: Management and challenges. Lancet Gastroenterol Hepatol 2020;5:428-30.  Back to cited text no. 11
    
12.
Ministry of Health and Family Welfare, Government of India. Guidelines on the Clinical Management of COVID-19; 2020. Available from: https://www.mohfw.gov.in. [Last accessed on 2021 Jul 08].  Back to cited text no. 12
    
13.
Ksiazek TG, Erdman D, Goldsmith CS, Zaki SR, Peret T, Emery S, et al. A novel coronavirus associated with severe acute respiratory syndrome. N Engl J Med 2003;348:1953-66.  Back to cited text no. 13
    
14.
Wu Z, McGoogan JM. Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: Summary of a report of 72 314 cases from the Chinese Center for Disease Control and Prevention. JAMA 2020;323:1239-42.  Back to cited text no. 14
    
15.
Lu J, Hu S, Fan R, Liu Z, Yin X, Wang Q, et al. ACP Risk Grade: A Simple Mortality Index for Patients with Confirmed or Suspected Severe Acute Respiratory Syndrome Coronavirus 2 Disease (COVID-19) during the Early Stage of Outbreak in Wuhan, China; 2020.  Back to cited text no. 15
    
16.
Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20.  Back to cited text no. 16
    
17.
Li Q, Guan X, Wu P, Wang X, Zhou L, Tong Y, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020;382:1199-207.  Back to cited text no. 17
    
18.
Xu XW, Wu XX, Jiang XG, Xu KJ, Ying LJ, Ma CL, et al. Clinical findings in a group of patients infected with the 2019 novel coronavirus (SARS-Cov-2) outside of Wuhan, China: Retrospective case series. BMJ 2020;368:m606.  Back to cited text no. 18
    
19.
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. 19
    
20.
Lu R, Zhao X, Li J, Niu P, Yang B, Wu H, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: Implications for virus origins and receptor binding. Lancet 2020;395:565-74.  Back to cited text no. 20
    
21.
Klopfenstein T, Zahra H, Kadiane-Oussou NJ, Lepiller Q, Royer PY, Tok L, et al. New loss of smell and taste: Uncommon symptoms in COVID-19 patients on Nord Franche-Comte cluster, France. Int J Infect Dis 2020;100:117-22.  Back to cited text no. 21
    
22.
Henry BM. COVID-19, ECMO, and lymphopenia: Word of caution. Lancet Respair Med 2020;42:e266-9.  Back to cited text no. 22
    
23.
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. 23
    
24.
Yuan X, Huang W, Ye B, Chen C, Huang R, Wu F, et al. Changes of hematological and immunological parameters in COVID-19 patients. Int J Hematol 2020;112:553-9.  Back to cited text no. 24
    
25.
Chu H, Zhou J, Wong BH, Li C, Chan JF, Cheng ZS, et al. Middle east respiratory syndrome coronavirus efficiently infects human primary T lymphocytes and activates the extrinsic and intrinsic apoptosis pathways. J Infect Dis 2016;213:904-14.  Back to cited text no. 25
    
26.
Lombardi A, Trombetta E, Cattaneo A, Castelli V, Palomba E, Tirone M, et al. Early phases of COVID-19 are characterized by a reduction in lymphocyte populations and the presence of atypical monocytes. Front Immunol 2020;11:560330.  Back to cited text no. 26
    
27.
Yun H, Sun Z, Wu J, Tang A, Hu M, Xiang Z. Laboratory data analysis of novel coronavirus (COVID-19) screening in 2510 patients. Clin Chim Acta 2020;507:94-7.  Back to cited text no. 27
    
28.
Rajamanickam A, Kumar NP, Pandiarajan AN, Selvaraj N, Munisankar S, Renji RM, et al. Dynamic alterations in monocyte numbers, subset frequencies and activation markers in acute and convalescent COVID-19 individuals. Scientific reports 2021;11:1-9.  Back to cited text no. 28
    
29.
Zhang JJ, Dong X, Cao YY, Yuan YD, Yang YB, Yan YQ, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy 2020;75:1730-41.  Back to cited text no. 29
    
30.
Fan BE, Chong VC, Chan SS, Lim GH, Lim KG, Tan GB, et al. Hematologic parameters in patients with COVID-19 infection. Am J Hematol 2020;95:E131-4.  Back to cited text no. 30
    
31.
Liu Y, Sun W, Guo Y, Chen L, Zhang L, Zhao S, et al. Association between platelet parameters and mortality in coronavirus disease 2019: Retrospective cohort study. Platelets 2020;31:490-6.  Back to cited text no. 31
    
32.
Yang AP, Liu JP, Tao WQ, Li HM. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol 2020;84:106504.  Back to cited text no. 32
    
33.
Sun S, Cai X, Wang H, He G, Lin Y, Lu B, et al. Abnormalities of peripheral blood system in patients with COVID-19 in Wenzhou, China. Clin Chim Acta 2020;507:174-80.  Back to cited text no. 33
    
34.
Ding X, Yu Y, Lu B, Huo J, Chen M, Kang Y, et al. Dynamic profile and clinical implications of hematological parameters in hospitalized patients with coronavirus disease 2019. Clin Chem Lab Med 2020;58:1365-71.  Back to cited text no. 34
    
35.
Pujani M, Raychaudhuri S, Verma N, Kaur H, Agarwal S, Singh M, et al. Association of Hematologic biomarkers and their combinations with disease severity and mortality in COVID-19 – An Indian perspective. Am J Blood Res 2021;11:180-90.  Back to cited text no. 35
    
36.
Qu R, Ling Y, Zhang YH, Wei LY, Chen X, Li XM, et al. Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19. J Med Virol 2020;92:1533-41.  Back to cited text no. 36
    
37.
Lissoni P, Rovelli F, Monzon A, Privitera C, Messina G, Porro G, et al. Evidence of abnormally low lymphocyte-to-monocyte ratio in Covid-19-induced severe acute respiratory syndrome. J Immunol Allergy 2020;1:1-6.  Back to cited text no. 37
    
38.
Letko M, Marzi A, Munster V. Functional assessment of cell entry and receptor usage for SARS-CoV-2 and other lineage B betacoronaviruses. Nat Microbiol 2020;5:562-9.  Back to cited text no. 38
    
39.
Du M, Cai G, Chen F, Christiani DC, Zhang Z, Wang M. Multiomics evaluation of gastrointestinal and other clinical characteristics of COVID-19. Gastroenterology 2020;158:2298-301.e7.  Back to cited text no. 39
    
40.
Joannidis M, Forni LG, Klein SJ, Honore PM, Kashani K, Ostermann M, et al. Lung-kidney interactions in critically ill patients: Consensus report of the Acute Disease Quality Initiative (ADQI) 21 Workgroup. Intensive Care Med 2020;46:654-72.  Back to cited text no. 40
    
41.
Chen G, Wu D, Guo W, Cao Y, Huang D, Wang H, et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Invest 2020;130:2620-9.  Back to cited text no. 41
    
42.
Cheng A, Hu L, Wang Y, Huang L, Zhao L, Zhang C, et al. Diagnostic performance of initial blood urea nitrogen combined with D-dimer levels for predicting in-hospital mortality in COVID-19 patients. Int J Antimicrob Agents 2020;56:106110.  Back to cited text no. 42
    
43.
Cai Q, Huang D, Yu H, Zhu Z, Xia Z, Su Y, et al. COVID-19: Abnormal liver function tests. Journal of hepatology 2020;73:566-74.  Back to cited text no. 43
    
44.
Xu Z, Shi L, Wang Y, Zhang J, Huang L, Zhang C, et al. Pathological findings of COVID-19 associated with acute respiratory distress syndrome. Lancet Respir Med 2020;8:420-2.  Back to cited text no. 44
    
45.
Tiwari N, Nath D, Madan J, Singh S, Bajpai P, Madan U. The neutrophil lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR) and routine hematological parameter of COVID-19 patient: A perspective of the Indian scenario from a frontline pilot study of 32 COVID-19 cases in a tertiary care institute of North India. medRxiv 2020. [Doi: 10.1101/2020.05.29.20102913].  Back to cited text no. 45
    
46.
Kumar A, Sepolia S, Shilpa RH, Rezayani G, Kumari S, Aastha, et al. Role of hematological and immunological parameters in COVID-19 patients. J Pharm Bioallied Sci 2021;13:238-43.  Back to cited text no. 46
    

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Correspondence Address:
Sabina Khan,
Department of Pathology, Hamdard Institute of Medical Sciences and Research, Jamia Hamdard, New Delhi - 110 062
India
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/jmau.jmau_59_22




 
 
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  [Table 1], [Table 2], [Table 3]



 

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Abstract
Introduction
Material and Methods
Results
Discussion
Conclusion
References
Article Tables

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