Pathology

Assessing Platelet Count as a Confounding Factor In Covid-19 Positive Patients

Global Journal of Pathology & Laboratory Medicine
Volume 1, Issue 4, January 2022, Pages: 58-64

Received: September 28, 2021, Reviewed: October 01, 2021, Accepted: October 11, 2021, Published: January 17, 2022

Unified Citation Journals, Pathology 2022, 1(4) 1-06; https://doi.org/10.52402/Pathology212
ISSN 2754-0952

Authors: Dr. Shubhangi Gupta 1, Dr. Atul Verma 2, Dr. Natasha Singh 2, Dr. Garima Agarwal 3, Dr. M.S. Bindra 4

1,2,3 Assistant Professor, Dept. of Pathology, SMS&R, Sharda University, Greater Noida
4 Professor, Dept. of Pathology, SMS&R, Sharda University, Greater Noida

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Introduction:
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) leads to various infections including COVID-19 infection , which produces a respiratory and systemic illness which progresses to a severe form of pneumonia in 10–15% of patients[3].Severe COVID- 19 infection can land up in critical illness, with complications like acute respiratory distress (ARDS) and multi-organ dysfunction primarily, eventually followed by intravascular coagulopathy[4].
Since its emergence in December 2019, the outbreak of novel Coronavirus Disease 2019 (COVID-19) outbreak has infected over 86,09,516people globally with nearly 4,56,960 deaths[1].Whereas in India total 382143 people got affected with nearly 12610 deaths reported so far[2]. Severe COVID- 19 infection can land up in critical illness, with complications like acute respiratory distress (ARDS) and multi-organ dysfunction primarily, eventually followed by intravascular coagulopathy[4]. It also causes cytokine storm, DIC leading to pulmonary embolism.
Few studies have shown platelet count is independently associated with disease[5-7].In order to optimize patient care and resource allocation during this pandemic, biomarkers are urgently needed for stratifying patients’ risk and for actively monitoring illness severity.
Moreover, a low platelet count correlates with higher disease severity scores such as Multiple Organ Dysfunction Score (MODS), Simplified Acute Physiology Score (SAPS) II, and Acute Physiology and Chronic Health Evaluation (APACHE) II.6 In the severe acute respiratory syndrome (SARS) outbreak, thrombocytopenia was reported to occur in up to 55% of patients and was identified as a significant risk factor for mortality[8,9].
Platelet count, with hypoxemia, were the only two variables used by Zou et al. for developing a SARS prognostic model which displayed 96.2% accuracy[10].
There is still a wide scope of researches to establish the laboratory markers available to evaluate illness severity in Coronavirus disease 2019 (COVID-19). In the present study, we focus to  investigate whether platelet count could differentiate between COVID-19 patients with or without severe disease.

MATERIALS AND METHODS
Study design: Retrospective and prospective Analytical study
Place of study:  Department of Pathology, Central lab, Sharda Hospital, Greater Noida
Period of study:  Nov 2019 to April 2020.
Study population: Patients admitted in In-Patient  in COVID Isolation, COVID ward and COVID ICU of Sharda Hospital, Greater Noida
Sample size:100 cases of SARS COV 2 positive patients already confirmed by RT-PCR test before admission.
Inclusion criteria-All the COVID-19 positive cases admitted in our hospital
Mild form of disease: mild fever, cough, sore throat, nasal congestion, malaise, headache and ARDS is further categorized into 3 groups: Mild, moderate and severe type of ARDS
Statistical analysis will be performed, with calculation of difference and 95% confidence interval (95% CI) of platelet number in COVID- 19 patients (asymyptomatic and mild form), as well as the odds ratio (OR) of thrombocytopenia for severe COVID-19. Subgroup analysis will be performed based on study definition of severity. The statistical analysis was performed by SPSS 21.
Exclusion criteria

  • COVID-19 positive patients with past history of coagulation dysfunction,
  • COVID-19 positive patients suffering malaria or
  • COVID-19 patients with moderate and severe disease

RESULT
The study is conducted in School of Medical Sciences and Research , Sharda University, for 6 months period including in-hospital patients (average of stay in hospital 9.32 ± 7.56) with covid 19 diagnosed by PCR & non-enhancing chest CT scan , the including patients were 100 with mean age 44.24 ± 16.42 years with 57% male & 43% female the majority with pneumonia but non critical & no one had clinically significant bleeding with the majority did not need RCU. For all patients included in the study (PCR & CT +ve cases )the platelets count show statistically significant increment when compare between the admission & discharge No. & this finding is go with most study as the increment indicate healing.
Table 1 show the patients distribution with COIVD 19 according to study variables (age, gender, symptoms, duration of resolution of the clinical features, clinically significant bleeding, severity , death and stay in hospital).

Study variables
Age (years) (44.24 ± 16.42) (13-78)
Duration of resolution of the clinical features (days) (2.35 ± 0.945) (1-6)
Hospital stay (days) (9.32 ± 7.56) (1-24)
Gender
Female    43
Male 57
Total 100
Symptoms
Pneumonia 78
No pneumonia 22
Total  100
Severity (need for ICU)
Yes 46
No 54
Total 100
Death
Yes 14
No 86
Total 100

As seen with table 2: There were statistically significant differences among means of platelets count on admission and on discharge.
Table 2: The mean differences of platelets count on two assessment periods on admission and on discharge

Study variables Assessment periods Mean SD Paired t-test P-value
 

Platelets count

On admission 241.22 62.48  

-6.548

 

<0.001*

On discharge 274.23 63.11

*P value ≤ 0.05 was considered as significant.
The correlation between of platelets count on admission and study variables including (age, duration of resolution of the clinical features and stay in hospital). There was significant negative correlation between platelets count on admission and age.

Table 3: The correlation between of platelets count on admission and study variables

Study variables Mean SD t-test P-value
Age (years) 44.24 16.42 -0.251 0.03*
Platelets count on admission 241.22 62.48
Duration of resolution of the clinical features (days) (2.35 0.945 -0.162 0.177
Platelets count on admission 241.22 62.48
Stay in hospital (days) 9.32 7.56 -0.222 0.061
Platelets count on admission 241.22 62.48

Table 4: There were significant negative correlation between platelets count on discharge and duration of resolution of the clinical features and stay in hospital.
Table 4: The correlation between of platelets count on discharge and study variables

Study variables Mean SD t-test P-value
Age (years) 44.24 16.42  

-0.084

 

0.489

Platelets count on discharge 241.22 62.48
Duration of resolution of the clinical features (days) (2.35 0.945  

-0.298

 

0.014*

Platelets count on discharge 274.23 63.11
Stay in hospital (days) 9.32 7.56  

-0.326

 

0.003*

Platelets count on discharge 274.23 63.11

DISCUSSION:
In the presence of this rapidly emerging, novel infection uncharacteristic of the era of modern medicine, identification of biomarkers that could predict disease severity and prognosis are essential to guiding clinical care. Uniquely to COVID-19, a wide range of variability in disease severity is observed ranging from asymptomatic to critical.3 As such, biomarkers are needed to identify severe disease among hospitalized patients. In this study, we found that platelet count may be a simple, economic, rapid and commonly available laboratory parameter that could straightforwardly discriminate between COVID patients with and without severe disease.
Thrombocytopenia is commonplace in critically ill patients, and usually suggests serious organ malfunction or physiologic decompensation as opposed to primary hematologic etiology, as well as the development of intravascular coagulopathy, often evolving towards disseminated intravascular coagulation (DIC).In COVID-19 patients, the mechanism for thrombocytopenia patients is likely multi factorial. In SARS, it was suggested that the combination of viral infection and mechanical ventilation leads to endothelial damage triggering platelet activation, aggregation and thrombosis in the lung, causing vast platelet consumption.8 Moreover, as lung may be a site of platelet release from fully mature megakaryocytes, a decrease or morphologic alternation in the pulmonary capillary bed may lead to deranged platelet defragmentation8.
Some studies have found a relationship between thrombocytopenia and the severity of the COVID-19 and related mortality. It has been reported that mortality increases as platelet count decreases12 , 13. Interestingly in our study, although thrombocytopenia was more likely to occur in non-survivors than in survivors, we did not find any correlation between platelet level and disease severity or mortality. Non-survivors had lower platelet counts than survivors on both admission day and third follow-up day, but this difference was not statistically significant. Similar to our study, other studies reported that platelet values were found to be normal in many patients at the time of hospital admission14. These differences between studies may be related to the time of the tests. Also, hydroxychloroquine, azithromycin, and enoxaparin treatment have been started in most countries when COVID-19 is suspected. These drugs can cause thrombocytopenia13 , 14. Another reason for the difference between studies may be that thrombocytopenia caused by drugs and thrombocytopenia caused by the disease present an intricate structure.
Coronaviruses may also directly infect bone marrow elements resulting in abnormal hematopoiesis, or trigger an auto-immune response against blood cells14. It also has been suggested that a consistently present low grade DIC may propagate a low platelet count in SARS[8]. However, as noted by the World Health Organization (WHO), significant differences are observed between SARS and COVID-19[3].

CONCLUSION
We concluded that the  mechanism of change in platelet indices in COVID-19 patients is probably multifactorial. Three hypotheses related to platelet count and structure are proposed in COVID-19. Firstly, as with other coronavıruses, thrombocytopenia is possibly due to infection of the bone marrow. Secondly, platelet destruction by the immune system. Thirdly, platelet consumption due to aggregation in the lungs17 . Generally, platelet production increases as platelet count decreases. An increased number of young platelets is also functionally more active than older platelets. These changes may explain the increase in platelet indices, MPV, and PDW. Hence, we can say increase in platelets level is a good indicator for recovery from covid in both PCR + ve patients.

References:
[1] Revised Guidelines on clinical management of COVID-19. Government of India, Ministry of Health & Family Welfare, Directorate General of Health Services (EMR Division) March 2020: 2-3
[2] World Health Organization (WHO). Coronavirus disease (COVID-19) pandemic. [Accessed 10 Jun 2020]. Geneva: WHO. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019
[3] Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, Lancet. 2020;395(10223):497–506.
[4] Xiaofang Zhao, Kun Wang, Peiyuan Zuo, Yuwei Liu, Meng Zhang, Songpu Xie, Hao Zhang, Xinglin Chen & Chengyun Liu, EPMA Journal 2020;11:139–
[5] The Emerging understandings of 2019-nCoV. Lancet. 2020;395(10221):311.
[6] Zarychanski, D.S. Houston, Assessing thrombocytopenia in the intensive care unit: the past, present, and future, Hematol. Am. Soc. Hematol. Educ. Program. 2017:660–666.
[7] Jolicoeur, L. Lamontagne, Impairment of bone marrow pre- B and B cells in MHV3 chronically-infected mice, Adv. Exp. Med. Biol. 380 (1995) 193–195
[8] Mattiuzzi, G. Lippi, Which lessons shall we learn from the 2019 novel coronavirus outbreak? Ann. Transl. Med. 8 (2020) (accessed March 8,  2020), https://atm.amegroups.com/post/view/ which-lessons-shall- we-learn-from-the-2019-novel-coronavirus-outbreak.
[9] Khurana, S.A. Deoke, Thrombocytopenia in critically Ill patients: clinical and laboratorial behavior and its correlation with short-term outcome during hospitalization, Indian J. Crit. Care Med. 2017;21: 861–864.
[10] Vanderschueren, A. De Weerdt, M. Malbrain, D. Vankersschaever, E. Frans A. Wilmer, H. Bobbaers, Thrombocytopenia and prognosis in intensive care, Crit. Care Med. 2000;28: 1871–1876.
[11] Hui, D.J. Cook, W. Lim, G.A. Fraser, D.M. Arnold, The frequency and clinical significance of thrombocytopenia complicating critical illness: a systematic review, Chest 2011;139: 271–278.
[12] Jolicoeur, L. Lamontagne, Impairment of bone marrow pre- B and B cells in MHV3 chronically-infected mice, Adv. Exp. Med. Biol. 380 (1995) 193–195
[13] Lippi, M. Plebani, Procalcitonin in patients with severe coronavirus disease 2019 (COVID-19): a meta-analysis, Clin. Chim. Acta (2020), https://doi.org/10.1016/j. Cca. 2020.03. 004.
[14] Chan JF-W, Yuan S, Kok K-H, Tok KK-W, Chu H, Yang J et , A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet 2020;395(10223):514–523.

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To citation of this article: Dr. Shubhangi Gupta, Dr. Atul Verma, Dr. Natasha Singh, Dr. Garima Agarwal, Dr. M.S. Bindra, Assessing Platelet Count as a Confounding Factor In Covid-19 Positive Patients, Global Journal of Pathology & Laboratory Medicine

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