Original article / research
Year :
2022 |
Month :
October
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Volume :
11 |
Issue :
4 |
Page :
PO13 - PO18 |
Full Version
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Analysis of Haematological Parameters of Peripheral Blood in COVID-19 Patients with a Special Emphasis on D-dimer
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Parameswaran Sakthidasan Chinnathambi, Tholem Sripriya, Gvrn Krishnakanth 1. Assistant Professor, Department of Pathology, ESIC Medical College, Sanath Nagar, Hyderabad, Telangana, India.
2. Senior Resident, Department of Pathology, ESIC Medical College, Sanath Nagar, Hyderabad, Telangana, India.
3. Professor, Department of Pathology, ESIC Medical College, Sanath Nagar, Hyderabad, Telangana, India.
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Correspondence
Address :
Parameswaran Sakthidasan Chinnathambi, Tholem Sripriya, Gvrn Krishnakanth, Parameswaran Sakthidasan Chinnathambi,
Flat No: 202, 2nd Floor, Adarsh Elite II Apartments, Plot No: 43, Prakash Nagar, Begumpet, Hyderabad, Telangana, India.
E-mail: sakthidasanmbbs@gmail.com
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| ABSTRACT | | : Introduction: Coronavirus Disease-2019 (COVID-19) is assessed by nasal/throat swab test, and further confirmed by Polymerase Chain Reaction (PCR) technique, albeit the day-to-day monitoring of COVID-19 patients depends largely on biochemical and haematological tests. There are differing results by various studies with respect to haematological parameters in COVID-19 infection.
Aim: To analyse the haematological parameters in peripheral blood samples of COVID-19 patients with a special emphasis on D-dimer.
Materials and Methods: A prospective study was conducted on 75 COVID-19 patients, for six months from August 2020 to January 2021 in Department of Pathology, ESIC Medical College Sanath Nagar, Hyderabad, Telangana, India after obtaining ethical clearance from Institutional Ethical Committee. Patient blood samples were evaluated for complete haemogram, coagulation parameters, followed by correlation with various categories of D-dimer levels. Following demographic assessment, the patient data was then stratified into four distinct categories based on D-dimer levels. Pearson’s correlation test was used to analyse the correlation of D-dimer and fibrinogen levels with various haematological parameters. Stratification analysis of D-dimer categories with haematological parameters were assessed with respect to mean, standard deviation, median and interquartile range, significance (p-value) of which was calculated using Kruskall wallis test. A p-value of <0.05 was considered to be statistically significant.
Results: Total 29 patients (38.7%) belonged to age range of 31-50 years category. Sixteen patients had normal D-dimer levels, 18 had mild elevation, moderately elevated D-dimer levels was noted in 26 patients, followed by 15 patients who had a severe elevation of D-dimer. Changes in Haemoglobin (Hb), Red Blood Cells (RBC) count and haematocrit were found to be significantly correlated with D-dimer levels, with p-values of 0.006, 0.021 and 0.010, respectively. Changes in Neutrophil (N) count, absolute Lymphocyte counts (L) and N:L ratio were also found to be statistically correlated (p-values 0.032, 0.011, 0.001 respectively) with D-dimer levels.
Conclusion: Assessment of haematological parameters can be a valuable tool in finding the severity of COVID-19 infection, thereby helping the clinicians in triaging, and treating the COVID-19 patients. |
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Keywords
: Coagulation, Coronavirus disease-2019, Haemoglobin, Lymphopenia, Pandemic |
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DOI and Others
: DOI: 10.7860/NJLM/2022/56219.2673
Date of Submission: Mar 09, 2022
Date of Peer Review: Apr 14, 2022
Date of Acceptance: Jun 04, 2022
Date of Publishing: Oct 01, 2022
AUTHOR DECLARATION:
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. NA
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Mar 16, 2022
• Manual Googling: Jun 01, 2022
• iThenticate Software: Jul 11, 2022 (5%)
Etymology: Author Origin |
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INTRODUCTION |
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Coronavirus Diseases-2019 is a pandemic disease caused by a novel Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). It belongs to the family of beta coronavirus. It started in China and now has spread all over the world taking major toll of lives in many countries (1). It is suspected clinically by common flu like symptoms such as sore throat, fever, myalgia, dry cough and breathlessness and tested by nasal and/or throat swab test, confirmed by PCR technique (1).
Considering the haematological changes, COVID-19 patients are prone to get lymphopenia, neutrophilia with an increased neutrophil/lymphocyte ratio to name a few. There are also changes in the morphology of the blood cells as documented by myriad studies, but with differing results. Studies have also documented changes in D-dimer and serum fibrinogen values, as the pathogenesis of COVID-19 involves even the clotting/fibrinolytic system (2). Hence, this study was undertaken while COVID-19 was in its peak, to find any significant changes in haematological parameters that help in triaging patients for further management. The aim of the study was to analyse the haematological parameters in peripheral blood samples of COVID-19 patients. The objectives were, to categorise patients based on D-dimer levels thereby, to find any significant association, if exists between the haematological parameters.
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Material and Methods |
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A prospective study for a period of six months, from August 2020 to January 2021 was conducted on 75 COVID-19 positive patients who were admitted in the isolation ward in the Department of Pathology at ESIC Medical College Sanath Nagar, Hyderabad, Telangana, India. The Institutional Ethical Clearance was obtained prior to the study (number is 799/U/IEC/ESICMC/F0202/08-2020). After obtaining proper ethical clearance and by taking formal consent, the blood samples were taken in COVID-19 positive patients and from those patients who were symptomatic but tested negative, served as control.
Inclusion criteria: All patients who tested positive for COVID-19 were included in the study.
Exclusion criteria: Patients who had associated co-morbidities such as diabetes, hypertension, heart disease etc were excluded from study population.
Study Procedure
Samples were taken in Ethylenediamine Tetraacetic Acid (EDTA) and sodium citrate vacutainers (2 mL each) for complete haemogram and coagulation analysis, respectively. Complete blood count was assessed by automated five part sysmex XS1000i Haematology analyser, followed by a peripheral smear, which was stained by routine leishman staining. Samples for coagulation analysis were subjected to D-dimer and fibrinogen levels. This was carried out with Sysmex CA 50 semi-automated coagulation analyser. All the data were compiled, and statistical analysis was carried out for any significant observations in haematological values in the COVID-19 patients. Following demographic assessment, the patient data was then stratified into four distinct categories based on D-dimer levels such as normal (D-dimer levels of <250), mild elevation in D-dimer levels (>250<500), moderate (D-dimer >500<2000) and severe (D-dimer >2000) (2).
All haematological parameters were evaluated with various categories of D-dimer levels, with an intent to know if there was any significant association of these parameters with the severity of disease. This was based on the well-established role of D-dimer in predicting severity of COVID-19 disease as patients who suffer from severe COVID-19 had high D-dimer levels.
Statistical Analysis
Correlation of D-dimer and fibrinogen levels with various haematological parameters were done with Pearson’s correlation test. Stratification analysis of D-dimer categories with haematological parameters were assessed with respect to mean, standard deviation, median and interquartile range, significance (p-value) of which were calculated using Kruskall wallis test. A p-value of <0.05 was considered to be statistically significant. Microsoft Excel software (Microsoft office 365) was used for the data analysis.
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Results |
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The age and gender distribution of 75 COVID-19 positive patients was presented in (Table/Fig 1). Most patients 29 (38.7%) belonged to age range of 31-50 years category. With respect to gender distribution, male:female ratio was found to be 2.2:1. The mean, standard deviation, median and interquartile range of all haematological parameters which were assessed in the study is shown in (Table/Fig 2). The frequency and percentage of stratified D-dimer levels was seen in (Table/Fig 3). Correlation statistics of D-dimer with haematological parameters where, changes in haemoglobin, RBC count and haematocrit were found to be significantly correlated with D-dimer levels, with p-values of 0.006, 0.021 and 0.010 respectively, is shown in (Table/Fig 4). Among the RBC indices, Mean Corpuscular Haemoglobin Concentration (MCHC) showed significant (p-value of 0.044) correlation with D-dimer levels. Not surprisingly, changes in neutrophil count, absolute lymphocyte counts and N:L ratio were also found to be statistically correlated (p-value 0.032, 0.011, 0.001 respectively) with D-dimer levels.
Changes in all other parameters were not statistically significant with respect to D-dimer levels. Correlation statistics of fibrinogen with haematological parameters is presented in (Table/Fig 5), where changes in Mean Corpuscular Haemoglobin (MCH) and Plateletcrit found to be significantly correlated with fibrinogen levels (p-values of 0.034 and 0.023 respectively). The statistical analysis of red cell, platelet and White Blood Cells (WBC) parameters with respect to stratified D-dimer levels, respectively, significance of which were calculated by performing Kruskall wallis test was seen in (Table/Fig 6),(Table/Fig 7),(Table/Fig 8). There were significant association noted with varying grades of D-dimer values and haemoglobin, RBC count, haematocrit with p-values of 0.002, 0.003 and 0.003 respectively. In addition, the change in neutrophil counts, lymphocyte absolute counts and N:L ratio had significant association with different grades of D-dimer values (p-values of 0.013, 0.010, and 0.001 respectively).
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Discussion |
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In the present study, the levels of D-dimer, fibrinogen and other haematological parameters in COVID-19 positive patients admitted in the isolation ward, of a tertiary care hospital, in Hyderabad were analysed. The patients were categorised into four categories viz., normal, mild, moderate, and severe based on the levels of D-dimer in blood. The stratification is performed because D-dimer is a well-established factor which helps in predicting the severity of the disease (2). This is followed by the assessment of individual haematological parameters and their significance of association among distinct categories of patients with elevated D-dimer levels and fibrinogen levels.
Of 75 COVID-19 positive patients admitted in the hospital, haematological parameters namely, haemoglobin, Red Blood Cell (RBC) count, haematocrit, Mean Corpuscular Haemoglobin Concentration (MCHC), neutrophil counts, absolute lymphocyte counts, and neutrophil/lymphocyte ratio were significantly correlated with the values of D-dimer. There was a significant correlation between fibrinogen values with Mean Corpuscular Haemoglobin (MCH) and plateletcrit. Haematological parameters mentioned above not only correlated with the values of D-dimer but also showed significant association with varying grades of the disease based on the D-dimer values.
Viral infections like influenza, Human Immunodeficiency Virus (HIV), varicella, dengue along with the present pandemic SARS-CoV-2 infections can have laboratory abnormalities and haematological changes at various stages of infection help to monitor as well as suspect the severity of the disease.
A meta-analysis of four studies done by Lippi G and Mattiuzzi C found a significantly low concentration of haemoglobin in severe COVID-19 positive patients (3). According to Cavezzi A et al., there is a possibility for haemoglobin denaturation and iron dysmetabolism in the pathogenesis of reduced haemoglobin in COVID-19 patients (4). Rahman MA et al., 2021 found a positive association among severe COVID-19 patients with haemoglobin, packed cell volume, Mean Corpuscular Volume (MCV) (5). In the present study, it was found that there was a significant association of haemoglobin, haematocrit, and RBC count with the D-dimer values of varying grades of severity of the disease based on the levels of D-dimer.
Numerous studies such as Huang C et al., Wang D et al., Wu C et al., Fan BE et al., Young BE et al., and Arentz M et al., showed significant correlation between the lymphocyte counts and severity of the disease among the COVID-19 patients who needed Intensive Care Unit (ICU) care (6),(7),(8),(9),(10),(11). A meta-analysis performed by Yang H et al., found association between lymphocyte counts, neutrophil counts, neutrophil/lymphocyte ratio and severe COVID-19 positive patients needing ICU care, thus suggesting the use of these parameters as markers for severity of the disease (12).
Rahman A et al., found common haematological abnormalities in COVID-19 disease as lymphocyte counts, elevated D-dimer levels and thrombocytopenia which can serve as possible biomarkers for the disease (13). Huang I et al., and Yan X et al., suggested association between haematological parameters like lymphocyte counts, neutrophil counts, neutrophil/lymphocyte ratio in COVID-19 patients with the severity of disease (14),(15). Study done by Amer SA et al., analysed the outcomes of COVID-19 infection such as disease severity, ICU admission, and mortality of all which found to be significantly correlated to Neutrophil Lymphocyte ratio (16). Meta-analysis of 18 studies done by Shah S et al., 2020 assessed the relationship between levels of D-dimer with the grades of severity of the disease (17). The present study correlated well with the most of above-mentioned studies on the association of haematological parameters with the severity of the disease.
A special note on peripheral smear finding of these COVID-19 patients, showed neutrophils with densely vacuolated cytoplasm, analogous to mott cells in the bone marrow of myeloma patients. In addition, there were giant platelets, platelet aggregates which showed spurious thrombocytopenia on counters. A manual count was preferred for these patients. There were reactive lymphocytes seen, similar to a dengue like picture in some patients. Interestingly, apoptotic neutrophils were prominently noted in severely ill patients. Those patients who had increased haematocrit, showed smears with closely populated RBCs at places forming agglutination.
In a study done by Kaur G et al., few morphologic findings seen in peripheral smear were neutrophils bearing clumped nuclear chromatin, anisokaryosis, pseudo Pelger-Huet anomaly, lymphoplasmacytoid lymphocytes, activated monocytes with cytoplasmic vacuolation, and platelet clumping (18).
In a study by Bahadur S et al., the authors studied the peripheral blood picture of COVID-19 patients and found that complete blood count with peripheral smear analysis provided only a partial support in understanding disease pathogenesis (19). On the contrary Gabr H et al., in their study, on changes in peripheral blood parameters in COVID-19 patients found a significant change in morphology in COVID-19 patients which can be used to assess the severity of disease (20).
Limitation(s)
In the present study the clinical assessment parameters were not included. Instead, the stratification levels of D-dimer were directly taken as an attempt to assess the severity of the disease.
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Conclusion |
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Assessment of haematological parameters can be of a valuable tool in finding the severity of COVID-19 infection, thereby helping the clinician in formulating risk stratification and prognostic work-up of these patients.
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| 1. | Toledo SL, Nogueira LS, Carvalho MG, Alves Rios DR, Pinheiro MB. COVID-19: Review and hematologic impact: Clinica Chimica Acta. 2020;510:170-76. ?doi?https://doi.org/10.1016/j.cca.2020.07.016#doi# ?pmid?32659224#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 2. | Li J, Liu Z, Wu G, Yi M, Chen Y, Li K, et al. D-Dimer as a prognostic indicator in critically Ill patients hospitalised with COVID-19 in Leishenshan hospital, Wuhan, China. Front Pharmacol.2020;11:600592. ?doi?https://doi.org/10.3389/fphar.2020.600592#doi# ?pmid?33408630#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 3. | Lippi G, Mattiuzzi C. Hemoglobin value may be decreased in patients with severe corona virus disease 2019. Hematol Transfus Cell Ther. 2020;42(2):116-17. ?doi?https://doi.org/10.1016/j.htct.2020.03.001#doi# ?pmid?32284281#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 4. | Cavezzi A, Troiani E, Corrao S. COVID-19: Hemoglobin, iron, and hypoxia beyond inflammation. A narrative review. Clin Pract. 2020;10(2):1271. ?doi?https://doi.org/10.4081/cp.2020.1271#doi# ?pmid?32509258#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 5. | Rahman MA, Shanjana Y, Tushar MI, Mahmud T, Rahman GMS, Milan ZH, et al. Hematological abnormalities and comorbidities are associated with COVID-19 severity among hospitalized patients: Experience from Bangladesh. PLoS ONE. 2021;16(7):e0255379. ?doi?https://doi.org/10.1371/journal.pone.0255379#doi# ?pmid?34314447#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 6. | Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with COVID-19 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-06. ?doi?https://doi.org/10.1016/S0140-6736(20)30183-5#doi# ?pmid?31986264#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 7. | 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(11):1061-69. ?doi?https://doi.org/10.1001/jama.2020.1585#doi# ?pmid?32031570#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 8. | Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):1031. ?doi?https://doi.org/10.1001/jamainternmed.2020.0994#doi# ?pmid?32167524#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 9. | Fan BE, Chong VCL, Chan SSW, Lim GH, Eric Lim KG, Tan GB, et al. Haematological parameters in patients with COVID-19 infection. Am J Hematol. 2020;95(6):E131-E134. ?doi?https://doi.org/10.1002/ajh.25774#doi#
[ Google Scholar] [ CrossRef] | 10. | Young BE, Ong SWX, Kalimuddin S, Low JG, Tan SY, Loh J, et al. Epidemiologic features and clinical course of patients infected with SARS-COV-2 in Singapore. JAMA. 2020;323(15):1488-94. ?doi?https://doi.org/10.1001/jama.2020.3204#doi# ?pmid?32125362#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 11. | Arentz M, Yim E, Klaff L, Lokhandwala S, Riedo FX, Chong M, et al. Characteristics and outcomes of 21 critically ill patients with COVID-19 in Washington State. JAMA. 2020;323(16):1612-14. ?doi?https://doi.org/10.1001/jama.2020.4326#doi# ?pmid?32191259#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 12. | Yang H, Xu Y, Li Z, Yan L, Wang J, Liao P. The clinical implication of dynamic hematological parameters in COVID-19: A retrospective study in Chongqing, China. Int Journ of General Medicine. 2021;14:4073-80. ?doi?https://doi.org/10.2147/IJGM.S321292#doi# ?pmid?34354369#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 13. | Rahman A, Niloofa R, Jayarajah U, Mel SD, Abeysuriya V, Seneviratne SL. Hematological abnormalities in COVID-19: A narrative review. Am J Trop Med Hyg. 2021;104(4):1188-01. ?doi?https://doi.org/10.4269/ajtmh.20-1536#doi# ?pmid?33606667#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 14. | Huang I, Pranata R. Lymphopenia in severe coronavirus disease-2019 (COVID-19): Systematic review and meta-analysis. J Intensive Care. 2020;8:36. ?doi?https://doi.org/10.1186/s40560-020-00453-4#doi# ?pmid?32483488#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 15. | Yan X, Li F, Wang X, Yan J, Zhu F, Tang S, et al. Neutrophil to lymphocyte ratio as prognostic and predictive factor in patients with coronavirus disease 2019: A retrospective cross-sectional study. J Med Virol. 2020;92(11):2573-81. ?doi?https://doi.org/10.1002/jmv.26061#doi# ?pmid?32458459#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 16. | Amer SA, Albeladi OA, Elshabrawy AM, Alsharief NH, Alnakhli FM, Almugathaui AF, et al. Role of neutrophil to lymphocyte ratio as a prognostic indicator for COVID-19. Health Sci Rep. 2021;4(4):e442. ?doi?https://doi.org/10.1002/hsr2.442#doi# ?pmid?34988293#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 17. | Shah S, Shah K, Patel SB, Patel FS, Osman M, Velagapudi P, et al. Elevated D-dimer levels are associated with increased risk of mortality in COVID-19: A systematic review and meta-analysis. Cardiology in Review. 2020;28(6):295-02. ?doi?https://doi.org/10.1097/CRD.0000000000000330#doi# ?pmid?33017364#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 18. | Kaur G, Sandeep F, Olayinka O, Gupta G. Morphologic changes in circulating blood cells of COVID-19 patients. Cureus. 2021;13(2):e13416. ?doi?https://doi.org/10.7759/cureus.13416#doi#
[ Google Scholar] [ CrossRef] | 19. | Bahadur S, Kalonia T, Kamini K, Gupta B, Kalhan S, Jain M. Changes in peripheral blood in SARS CoV-2 patients and its clinico-pathological correlation: A prospective cross-sectional study. Int J Lab Hematol. 2021;43(6):1334-40. ?doi?https://doi.org/10.1111/ijlh.13720#doi# ?pmid?34596329#pmid#
[ Google Scholar] [ CrossRef] [ PubMed] | 20. | Gabr H, Bastawy S, Abdel Aal AA, Khalil NM, Fateen M. Changes in peripheral blood cellular morphology as diagnostic markers for COVID-19 infection. Int J Lab Hematol. 2022;44(3):454-60. ?doi?https://doi.org/10.1111/ijlh.13799#doi# ?pmid?35048518#pmid# [ Google Scholar] [ CrossRef] [ PubMed]
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TABLES AND FIGURES | |
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