|Year : 2021 | Volume
| Issue : 2 | Page : 4-12
Association of hematological and biochemical parameters with clinical profile of COVID-19 patients in Visakhapatnam, India
Himavathy Kodandarao Gara1, Dharma Rao Vanamali2, Adhikarla Surya Veeramani Kartheek3
1 Department of Physiology, Gayatri Vidya Parishad Institute of Healthcare and Medical Technology, Visakhapatnam, Andhra Pradesh, India
2 Department of General Medicine, Gayatri Vidya Parishad Institute of Healthcare and Medical Technology, Visakhapatnam, Andhra Pradesh, India
3 Department of General Medicine, Government Medical College, Srikakulam, Andhra Pradesh, India
|Date of Submission||23-Jul-2021|
|Date of Acceptance||27-Jul-2021|
|Date of Web Publication||05-Oct-2021|
Dr. Adhikarla Surya Veeramani Kartheek
Department of General Medicine, Government Medical College, D.no. 14-413, Sri Manikanta Nilayam, Behind Lakshmi Talkies, Naidu Cheruvugattu, Gujarathipeta, Srikakulam, Andhra Pradesh, 532001
Source of Support: None, Conflict of Interest: None
Background: The cytokine cascade in COVID-19 is responsible for its clinical manifestations. Timely management of patients with dismal prognosis may improve their clinical outcome. The study aimed to analyze the hematological and biochemical parameters among COVID-19 patients and the factors associated with laboratory changes and COVID-19 infection. Materials and Methods: A retrospective, cross-sectional study was conducted in a designated district COVID hospital. COVID-19 patient’s medical records were converted into an electronic database which included demographic data, recent exposure history, existing co-morbidities, symptoms, and laboratory findings. Results: Out of the 1340 patients, 69.25% were males. Symptomatics accounted for 57.61%. The common co-morbidities among infected patients were diabetes mellitus (13.88%), hypertension (15%), and chronic obstructive pulmonary disease/asthma (2.16%), which had a significant positive correlation with COVID-19. The common symptoms were fever (50.39%), dry cough (46.24%), dyspnea (30.7%), and myalgia (28.5%). Leucocytosis, neutrophilia, lymphopenia, and thrombocytopenia were reported in 5.22%, 11.34%, 27.16%, and 3.41% of patients, respectively. Elevated aspartate aminotransferase, alanine aminotransferase, hypoalbuminemia, and hyperglobulinemia were observed in 13.88%, 19.4%, 24.77%, and 10% of patients, respectively. Symptomatics had significantly higher values for neutrophil percentage, neutrophil–lymphocyte ratio (NLR), derived NLR, lymphocyte-to-monocyte ratio, platelet-to-lymphocyte ratio, lymphocyte–leucocyte ratio, systemic immune-inflammatory index, blood urea, and indirect bilirubin levels and significantly lower values for lymphocyte percentage, absolute lymphocyte count, and serum albumin. The logistic regression analysis revealed a significant association of deranged laboratory parameters among symptomatic COVID-19 patients and those with pre-existing co-morbidities. Conclusion: Neutrophilia, lymphopenia, and deranged liver function tests were significantly present in COVID-19 patients. The inflammation in COVID-19 is exhibited as remarkable hematological and laboratory changes whose careful interpretation can offer a clinical window for risk stratification and appropriate therapeutic interventions.
Keywords: Biochemical parameters, co-morbidities, COVID-19, hematological parameters, inflammation
|How to cite this article:|
Gara HK, Vanamali DR, Kartheek AS. Association of hematological and biochemical parameters with clinical profile of COVID-19 patients in Visakhapatnam, India. Assam J Intern Med 2021;11:4-12
|How to cite this URL:|
Gara HK, Vanamali DR, Kartheek AS. Association of hematological and biochemical parameters with clinical profile of COVID-19 patients in Visakhapatnam, India. Assam J Intern Med [serial online] 2021 [cited 2021 Oct 18];11:4-12. Available from: http://www.ajimedicine.com/text.asp?2021/11/2/4/327546
| Introduction|| |
Since the first reported case in December 2019 in China, coronavirus disease 2019 (COVID-19) has spread globally affecting 215 countries and territories. Despite the adoption of a series of preventive and control measures, the rapid and unprecedented dissemination of COVID-19 among the Indian population has perplexed into a serious public health threat. Following viremia, COVID-19 primarily affects the tissues expressing high levels of angiotensin-converting enzyme (ACE)-2, including the lungs, heart, and gastrointestinal tract. After an incubation period of 7–14 days, there is a pronounced systemic increase of inflammatory mediators which translates into cytokine storm, effectuating as extensive tissue damage with dysfunctional coagulation. The clinical manifestations range from prodromal symptoms such as fever and myalgia to significant hypoxia with acute respiratory distress syndrome (ARDS).,
The current challenges in the COVID-19 pandemic are the limited medical resources and uncertainty regarding virus–host interaction and therapeutic designs. Peripheral total leucocyte count (TLC), neutrophil-to-lymphocyte ratio (NLR), derived NLR, platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), and systemic immune-inflammatory index (SII) have evolved as indicators of the systemic inflammatory response and have been perused for the prognosis of patients with inflammation. Circulating biomarkers can be potential prognosticators in COVID-19 patients with dismal prognosis. Careful interpretation of routine laboratory parameters can help in understanding the evolution of disease. The primary outcome of the study was to analyze the hematological and biochemical parameters among COVID-19 patients. The secondary outcome was to determine the factors associated with laboratory changes and COVID-19 infection.
| Materials and Methods|| |
It was a retrospective, observational, cross-sectional study conducted in a designated district COVID hospital, Gayatri Vidya Parishad Institute of Healthcare and Medical Technology (GVP IHC and MT), Visakhapatnam, India. The study was approved by the Institutional Ethical Committee and was conducted in compliance with the Declaration of Helsinki. The study included patients admitted from June 5, 2020 to August 19, 2020. The inclusion criteria were (i) positive result of real-time reverse transcriptase–polymerase chain reaction (RT–PCR) assay or TrueNat assay comprising of screening (E gene) and confirmatory (Orf1a) targets or rapid antigen test or cartridge-based nucleic acid amplification test (CBNAAT) from nasal or pharyngeal swab specimens, and (ii) fulfillment of the diagnostic criteria of confirmed cases of COVID-19 as per guidelines of Ministry of Health and Family Welfare (MOHFW), India. Patients with age less than 18 years and those with missing baseline data/investigation details were excluded from the study. Based on the patients admitted during the study period, a convenient sampling strategy was adopted. Therefore, formal sample size was not calculated.
It was a fully case-sheet-based study and patients were not contacted in any phase of the study. The patient with a confirmed diagnosis of COVID-19 was identified by one of the investigators and his/her medical records were cross-checked for consistency before final data entry into a customized form. The in-patient ID was converted into Study ID (SID) and the principal investigator received an electronic database with SID. Thus, the patient remained unidentifiable, assuring the patient’s anonymity and full database protection. Also, the requirement of informed consent was waived off.
The clinical data which were extracted from the electronic database included demographic data, recent exposure history, existing co-morbidities, symptomatology, and laboratory findings. Laboratory assessments consisted of complete blood cell counts, random blood glucose levels, renal function tests (RFTs), and liver function tests (LFTs). In this study, TLC, NLR, d-NLR (estimated as neutrophil count divided by the result of TLC count minus neutrophil count), lymphocyte-to-leucocyte ratio (LLR), LMR, PLR, and SII (estimated as the result of the product of neutrophils and platelet divided by lymphocyte) were considered as the indicators of systemic inflammatory response.,
The electronic database was organized into a Microsoft Excel sheet and subjected to statistical analyses with the help of Statistical Package for Social Sciences (SPSS) software version 26. Categorical variables were expressed as frequencies (N) and percentages (%). Continuous variables with normal distribution were computed into mean ± standard deviation (SD). The frequency of various clinical symptoms was graphically depicted as a bar diagram. The patients were dichotomized as asymptomatics and symptomatics based on guidelines of MOHFW, India. The statistical significance of the difference in mean values of laboratory parameters was determined by an independent “t” test. The logistic regression analysis was conducted to examine (i) the association of various factors such as age, gender, and co-morbidities with symptomatic patients, (ii) the relationship between symptomatics and deranged laboratory parameters, and (iii) the association between co-morbidities and deranged laboratory parameters. The odds ratio (OR) along with 95% confidence interval (CI) was reported. P < 0.05 was considered to be statistically significant for all analyses.
| Results|| |
In the present study, case-sheets of 1458 COVID-19 patients were evaluated, of which 118 patients were excluded due to the reasons as per [Figure 1]. So, the final analysis was restricted to 1340 cases.
|Figure 1: Flowchart of recruitment of COVID-19 patient’s case sheets for the study|
Click here to view
Out of the 1340 COVID-19 patients, majority were males [n = 928 (69.25%)]. The mean age of the patients was 36±12.3 years. Symptomatic patients accounted for 57.61% (n = 772) [Table 1]. Co-morbidities were reported in 25.97% (n = 348). The most common co-morbidities found in COVID-19 asymptomatic and symptomatic patients were diabetes mellitus (DM) (5.45% vs. 20.07%), hypertension (HTN) (5.98% vs. 21.63%), chronic obstructive pulmonary disease (COPD)/asthma (0.53% vs. 3.36%), and coronary artery disease (CAD) (0.7% vs. 2.33%). The most common symptoms were fever [n = 389 (50.39%)], followed by dry cough [n = 357 (46.24%)], dyspnea [n = 237 (30.7%)], and myalgia [n = 220 (28.5%)] [Figure 2].
|Figure 2: Frequency of clinical symptoms in symptomatic COVID-19 patients (n = 772)|
Click here to view
The logistic regression analysis [Table 2] revealed that females had negative association for being symptomatic (β= −0.275, OR=0.759, P = 0.035). Symptomatics had significant positive association with DM (β= 1.436, OR=4.204, P ≤ 0.0001), HTN (β = 1.432, OR=4.186, P ≤ 0.0001), DM+HTN (β = 1.125, OR = 0.474, P = 0.018), and COPD/asthma (β = 2.006, OR =7.433, P = 0.001).
|Table 2: Logistic regression analysis of factors associated with symptomatic COVID-19|
Click here to view
Among the hematological parameters [Table 3], symptomatic patients had significantly higher percentage of neutrophils (P = 0.007), NLR (P = 0.004), d-NLR (P = 0.001), LMR (P = 0.016), PLR (P = 0.019), LLR (P = 0.004), SII (P = 0.044), blood urea (P = 0.001), and indirect bilirubin (P = 0.007) when compared with asymptomatics. The percentages of lymphocytes (P = 0.004), absolute lymphocyte count (P = 0.01), LMR (P = 0.016), LLR (P = 0.004), serum albumin (P = 0.005), and albumin–globulin ratio (P = 0.006) were significantly lower in symptomatics than in asymptomatics.
|Table 3: Hematological and biochemical parameters in COVID-19 patients (n = 1340)|
Click here to view
The multivariate logistic regression analysis [Table 4] revealed that when compared with asymptomatic patients, symptomatics exhibited statistically significant neutrophilia (8.62% vs. 13.34%; P = 0.007), lymphopenia (30.67% vs. 22.36%; P = 0.001), and raised aspartate aminotransferase (AST) (11.8% vs. 15.41%; P = 0.049). Leucocytosis and neutrophilia had a significant positive association with DM [Table 5]. DM, HTN, and CAD were positively associated with raised creatinine levels and liver enzymes.
|Table 4: Multivariate logistic regression analysis of deranged laboratory parameters with COVID-19|
Click here to view
|Table 5: Multivariate logistic regression analysis of deranged laboratory parameters with co-morbidities in COVID-19 patients|
Click here to view
| Discussion|| |
The cytokine cascade in COVID-19 translates into hyper-inflammatory condition, being reflected as hematological and biochemical changes which have been explored in the present study.
In the present study, females were less in proportion and had a significant negative association for being symptomatic. A systematic review of 61 studies with more than 10,100 cases highlighted that males had a relative risk of 1.2 (P < 0.001) for severe infection. When compared with males, females have a lesser expression on ACE-2 and augmented humoral and cell-mediated immune responses to vaccination and infections. These gender-based immunological variations are driven by the protective effect of estrogen receptor signaling and X-chromosome. Other attributes could be a higher prevalence of risk behaviors such as smoking and drinking and co-morbidities in males.
Symptomatic patients accounted for 57% of cases in our study as these patients were sent to our district COVID hospital from the designated government COVID testing centers in a randomized manner. Also, a few diagnosed patients opted for home isolation as per revised guidelines by MOHFW. The common clinical symptoms in COVID-19 patients were fever and dry cough (almost 50%), followed by dyspnea and myalgia (almost 30%). Kayina et al. reported similar findings in 235 patients in a tertiary care hospital, New Delhi.
In the present study, neutrophilia and lymphopenia were observed in 10% and 25%, respectively, and had a significant association with symptomatics. A well-coordinated innate response is the first defense against viral infection, and the adaptive immune system regulates inflammatory response to injury. It is postulated that in response to inflammation, the neutrophil production may be accentuated, which may induce apoptosis of lymphocytes. The drift of progressive rise in neutrophils with lymphocytic depletion is augmented in cytokine storm. Lymphocytes confer both innate and adaptive immunity. Sustained lymphopenia, if associated with lymphocytic anergy, may impede the resolution of inflammation, resulting in poor clinical outcome.
The present study revealed significantly higher mean values of NLR, d-NLR, LMR, LLR, PLR, and SII among symptomatic patients when compared with asymptomatics, suggestive of hyperinflammatory state. SII takes into account neutrophils, lymphocytes, and platelets and can reflect the immune-inflammatory status. Previous studies have substantiated its predictive role in the prognosis in inflammatory conditions. Kong et al. in their studies observed higher mean NLR in severe cases of COVID-19 than the mild group (6.6 vs. 3.3, P < 0.001) and suggested that NLR was positively correlated with the incidence of severe illness. COVID-19-associated hyper-inflammation is detrimental as it might escalate the need of intensive care support for patients.,
Thrombocytopenia was observed in around 3% of the patients. A similar finding of thrombocytopenia was documented in 5% of patients by Huang et al. Thrombocytopenia in COVID-19 may be a consequence of direct infection of the hematopoietic progenitor cells leading to reduced thrombopoiesis and/or immune-mediated destruction and/or enhanced consumption in the form of aggregation or microthrombi.
The present study has revealed hyperglobulinemia and hypoalbuminemia in almost 10% and 25% of COVID-19 patients, respectively, with no significant difference among asymptomatics and symptomatics. Interleukin-6-induced differentiation of activated B-cells into antibody-producing plasma cells may contribute to hypergammaglobulinemia. The surge in viral copies as well as inflammatory cytokines may induce hepatic injury. As the serum half-life of albumin is approximately 21 days, viral-induced hepatic synthetic dysfunction would less likely cause hypoalbuminemia. However, acute systemic inflammation when associated with increased capillary permeability facilitates albumin flux into the interstitium and its increased volume distribution. Also, the half-life of albumin is shortened as it functions as intracellular amino-acid donor. These amino-acids are utilized as building blocks for other proteins and other intermediate metabolism. Thus in inflammatory states, there is enhanced catabolism and reduced synthesis of albumin. The consequential hypoalbuminemia could be associated with coagulopathy and poor prognosis in COVID-19 patients.
In the present study, elevation of AST and alanine aminotransferase (ALT) was observed in one-fifth of patients. Similar findings were documented in a meta-analysis of 128 papers, which correlated the disease severity with a relative risk of hypoalbuminemia—2.65 (1.38–5.07), ALT—1.76 (1.44–2.15), and AST—2.30 (1.82–2.90). The elevated liver enzymes are suggestive of direct liver injury, either immune-mediated or drug-induced during hospitalization. Altered LFTs are linked to higher odds for severity and disease progression.
In the present study, blood urea was significantly higher in symptomatics when compared with asymptomatics. Elevated blood urea and creatinine were present in 3% and 7% of patients, respectively. A similar increase was reported in less than 10% of infected patients by Wang et al. However, monitoring of RFTs should be emphasized even in mild cases with no severe symptoms to prefigure nephrotoxicity which could be attributed to either cytokine storm-induced apoptosis of the renal tubular epithelium or pharmacological/iatrogenic interventions.
In the present study, co-morbidities such as DM and HTN were reported in approximately 15% of the COVID-19 patients, similar to the study by Huang et al. Symptomatics had a significant positive correlation with DM, HTN, and COPD/asthma when compared with asymptomatics. Similar findings were featured in a meta-analysis that highlighted the pooled OR of DM, HTN, and respiratory disease as 2.07, 2.36, and 2.46, respectively. Also, these co-morbidities revealed significant association with elevated liver enzymes and raised creatinine levels. A significant association with leucocytosis and neutrophilia was observed among diabetic patients. Pre-existing co-morbidities are often coupled with immune dysfunction and/or exaggerated cytokine expression. Hence, assimilating co-morbidities should be integral for stratified risk strategy and patient management as they have strong epidemiological associations with deteriorating outcomes such as pneumonia, ARDS, or coagulopathy and can independently influence prognosis and mortality.
The inflammatory storm in COVID-19 is responsible for the clinical manifestation of COVID-19. CBC, LFTs, and RFTs are routinely performed and their serial monitoring can be utilized as a bedside risk-assessment tool for patient stratification. Conglomeration of knowledge, praxis, and interpretation of laboratory findings shall help to extrapolate risk prediction models to monitor disease progression and optimize therapeutic interventions for patients.
A larger sample size emerges to be the strength of the study. But the main limitations are the retrospective nature of the study and data collection from one hospital. It has the potential scope for the interviewer’s bias and recall bias of the patient. Only preliminary measures of association with elevated biomarkers could be obtained. A prospective study with the inclusion of multiple centers can lead to a validation approach to establish causal relationships in the COVID-19 cohort and its generalization to the population.
| Conclusion|| |
The present study showed that females had a significant negative association, and comorbidities such as DM, HTN, and COPD/asthma had a positive correlation with COVID-19. Neutrophilia, lymphopenia, and thrombocytopenia were present in around 10%, 25%, and 3% patients, respectively. When compared with asymptomatics, symptomatics had significantly higher neutrophil percentages and lower lymphocyte percentages and absolute count. Also, the mean values of NLR, d-NLR, LMR, PLR, and SII were raised in symptomatic patients. Hypoalbuminemia and elevated liver enzymes were observed in approximately 20% of the patients. The present study clearly shows that COVID-19 is accompanied by notable changes in hematological and biochemical profiles, which may help in early identification of COVID-related complications and may facilitate supportive medical care for positive patient outcomes.
We sincerely offer gratitude to all the healthcare providers fighting against in COVID-19 pandemic. We would like to thank all the patients whose data were involved in the study. We are indebted to our Chairman, Dr. P. Somaraju, and our Dean Prof. Dr. D.V.V.S. Ramamurthy for their support and encouragement throughout the study. We also acknowledge the hospital staff for their efforts in collecting the information. We express deep condolences to the victims and bereaved families.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Zou X, Chen K, Zou J, Han P, Han Z. Single-cell RNA-seq data analysis on the receptor ACE2 expression reveals the potential risk of different human organs vulnerable to 2019 nCov infection. Front Med 2020;14:185-92.
Ye Q, Wang B, Mao J. The pathogenesis and treatment of the “cytokine storm” in COVID-19. J Infect2020;80:607-13.
Kayina CA, Haritha D, Soni L, Behera S, Nair PR, Gouri M, et al
. Epidemiological & clinical characteristics & early outcome of COVID-19 patients in a tertiary care teaching hospital in India: A preliminary analysis. Indian J Med Res 2020;152:100-4.
] [Full text]
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.
Lagunas-Alvarado M, Mijangos-Huesca FJ, Terán-González JO, Lagunas Alvarado MG, Martínez Zavala N, Reyes-Franco I, et al
. Systemic immune inflammatory index in sepsis. Med Int Mex2017;33:303-9.
Kong M, Zhang H, Cao X, Mao X, Lu Z. Higher level of neutrophil-to-lymphocyte is associated with severe COVID-19. Epidemiol Infect 2020;148:e139.
Fang X, Li S, Yu H, Wang P, Zhang Y, Chen Z, et al
. Epidemiological, comorbidity factors with severity and prognosis of COVID-19: A systematic review and meta-analysis. Aging 2020;12:12493-503.
Channappanavar R, Fett C, Mack M, Ten Eyck PP, Meyerholz DK, Perlman S. Sex-based differences in susceptibility to severe acute respiratory syndrome coronavirus infection. J Immunol 2017;198:4046-53.
Shelley O, Murphy T, Paterson H, Mannick JA, Lederer JA. Interaction between the innate and adaptive immune systems is required to survive sepsis and control inflammation after injury. Shock 2003;20:123-9.
Xu P, Zhou Q, Xu J. Mechanism of thrombocytopenia in COVID-19 patients. Ann Hematol 2020;99:1205-8.
Tanaka T, Narazaki M, Kishimoto T. IL-6 in inflammation, immunity, and disease. Cold Spring Harb Perspect Biol 2014;6:a016295.
Soeters PB, Wolfe RR, Shenkin A. Hypoalbuminemia: Pathogenesis and clinical significance. J Parenter Enteral Nutr 2019;43:181-93.
Huang W, Li C, Wang Z, Wang H, Zhou N, Jiang J, et al
. Decreased serum albumin level indicates poor prognosis of COVID-19 patients: Hepatic injury analysis from 2,623 hospitalized cases. Sci China Life Sci 2020;63:1678-87.
Feng G, Zheng KI, Yan QQ, Rios RS, Targher G, Byrne CD, et al
. COVID-19 and liver dysfunction: Current insights and emergent therapeutic strategies. J Clin Transl Hepatol 2020;8:18-24.
Wang L, Li X, Chen H, Yan S, Li D, Li Y, et al
. Coronavirus disease 19 infection does not result in acute kidney injury: An analysis of 116 hospitalized patients from Wuhan, China. Am J Nephrol 2020;51:343-8.
Uribarri A, Núñez-Gil IJ, Aparisi A, Becerra-Muñoz VM, Feltes G, Trabattoni D, et al
; HOPE COVID-19 Investigators. Impact of renal function on admission in COVID-19 patients: An analysis of the International HOPE COVID-19 (health outcome predictive evaluation for COVID 19) registry. J Nephrol 2020;33:737-45.
Yang J, Zheng Y, Gou X, Pu K, Chen Z, Guo Q, et al
. Prevalence of comorbidities and its effects in patients infected with SARS-CoV-2: A systematic review and meta-analysis. Int J Infect Dis 2020;94:91-5.
[Figure 1], [Figure 2]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5]