| Abstract|| |
Background: The epidemic of coronavirus disease 2019 (COVID-19) has been rapidly spreading on a global scale affecting many countries and territories. There is rapid onset of generalized inflammation resulting in acute respiratory distress syndrome. We, thus, aimed to explore the potential of immune-inflammatory parameters in predicting the severity of COVID-19. Materials and Methods: Age, neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), Lactate Dehydrogenase (LDH), C-reaction protein (CRP), and procalcitonin (PCT) of 611 patients with laboratory-confirmed COVID-19 were investigated and compared. Patients were divided on the basis of severity and survival into two groups. Data were expressed as mean or median values and percentages. The receiver operating characteristic curve was applied to determine the optimal cut-off values of these biomarkers. Results: The median age was 50 years and the male to female ratio was 3.7:1. The mean NLR, LMR, PLR, LDH, CRP, and Procalcitonin for the non-severe group were 4.16, 10.8, 133.7, 666.1, 49.9, and 0.15, respectively. In the severe group mean values of the above-mentioned immune-inflammatory markers were 17.8, 4.69, 268.2, 1277, 158.6, and 3.05, respectively. Elevated levels were significantly associated with disease severity. In ROC curve analysis, NLR had the largest area under the curve at 0.923 with the highest specificity (0.83) and sensitivity (0.88). Conclusion: This study shows that NLR, PLR, LDH, CRP, and Procalcitonin may be a rapid, widely available, useful predictive factor for determining the severity of COVID-19 patients.
Keywords: COVID-19, inflammation, lymphocyte, neutrophil
|How to cite this article:|
Singh A, Bhadani PP, Surabhi, Sinha R, Bharti S, Kumar T, Nigam JS. Significance of immune-inflammatory markers in predicting clinical outcome of COVID-19 patients. Indian J Pathol Microbiol 2023;66:111-7
|How to cite this URL:|
Singh A, Bhadani PP, Surabhi, Sinha R, Bharti S, Kumar T, Nigam JS. Significance of immune-inflammatory markers in predicting clinical outcome of COVID-19 patients. Indian J Pathol Microbiol [serial online] 2023 [cited 2023 May 29];66:111-7. Available from: https://www.ijpmonline.org/text.asp?2023/66/1/111/367971
| Introduction|| |
In early December 2019, many cases of pneumonia of unknown etiology were reported in Wuhan, Hubei province, China. The disease resembles severe acute respiratory syndrome coronavirus (SARS-CoV). The Coronaviridae Study Group (CSG) of the International Committee on Taxonomy of Viruses named this virus as SARS-CoV-2. This virus was sister species to the prototype human and bat severe acute respiratory syndrome coronavirus( SARS-CoV). It was subsequently named as the 2019-novel coronavirus disease (COVID-19) by the World Health Organization (WHO).
On January 7, 2020, the Chinese Center for Disease Control and Prevention (CDC) has informed about a novel beta-coronavirus, that was isolated from the throat swab sample of a patient through high-throughput sequencing. Since then many countries and territories have been affected. Globally, as of 17 November 2020, there have been 54,771,888 confirmed cases of COVID-19. As per WHO, India is the 2nd worst affected country by the COVID-19 pandemic with more than 8 million confirmed cases around mid-November.
Several studies showed an increased level of neutrophils and a decrease in lymphocyte numbers in patients with COVID-19.,, These studies indicated that neutrophils or lymphocytes could be a potential risk factor for the progression of SARS-CoV-2- infected patients. The neutrophil-lymphocyte ratio (NLR) is a potential marker of the systemic inflammatory response. It is obtained from the ratio of absolute neutrophil and absolute lymphocyte counts of a complete blood count. High NLR indicates the increased intensity of the inflammatory response and damage to the immune system, respectively. Activated immune cells and infected cells release proinflammatory cytokines and chemokines. This cytokine storm led to organ dysfunction and mortality in SARS and COVID-19 patients. NLR, PLR, LMR, CRP, LDH, and Procalcitonin are immune-inflammatory markers. These are investigated as predictors of prognosis in many diseases.,, However, the clinical value of these markers in the peripheral blood of Covid-19 patients is unclear. These biomarkers were associated with COVID-19 in its different degrees of severity Only limited studies have compared the clinical characteristics of severe and non-severe patients.,, In this study, we have investigated the potential of these serological biomarkers in predicting the severity of COVID-19.
| Materials and Methods|| |
Study Design and Participants
We conducted a retrospective and observational study in a COVID-19-dedicated hospital and collected clinical data in patients diagnosed with COVID-19 between July 1 and July 31, 2020. A total of 611 patients were included in this study. The diagnosis of COVID-19 was made according to the Ministry of Health and Family Welfare (MOHFW), Government of India (GOI) guidelines and confirmed by RTPCR performed on nasopharyngeal and oropharyngeal samples. All pediatric and adult cases were included in the study.
In this analysis, we divided COVID-19 patients into two categories: non-severe and severe. The non-severe category included patients with the mild and moderate illnesses. Symptoms of fever, sore throat, and cough were included in mild illness. An additional symptom of breathlessness with oxygen saturation of 90% to <93% was included in moderate illness.
The severe category included patients with symptoms of breathlessness with oxygen saturation <90%, respiratory failure, septic shock, and/or multiple organ dysfunction.
Clinical data included presenting complaints, demographic inforefcmations (gender, age, comorbid conditions, duration of hospital stay), and laboratory tests such as Complete Blood Count, Lactate Dehydrogenase (LDH), C-reaction protein (CRP), procalcitonin (PCT), which were routinely done for Covid-19 patients. Hence, we collected the result of these tests (done on the first day of hospitalization of patients) from the hospital information system for both non-severe and severe categories. Neutrophil lymphocyte ratio, Lymphocyte Monocyte ratio, and Platelet Lymphocyte ratio were calculated. CRP and LDH are measured quantitatively by Beckman Coulter Auto analyzer AU5811 and Procalcitonin by Siemens XT. The normal reference range of CRP is below 5 mg/L, LDH is 105-333 IU/L and procalcitonin is less than 0.05 ng//ml.
Tabulated data were analyzed systematically by the use of appropriate statistical methods and SSPS software (Version 22.0) and results were obtained. Two groups were formed on the basis of severity and survival. The primary cause for deaths in this study was Covid-19. None of the deaths occurred due to any other non-inflammatory disease. Data were expressed as mean/median values and percentages. Standard deviation, sensitivity, and specificity were analyzed. Comparison between groups was done by paired -test and on-way ANOVA test. A P value of less than 0.05 was considered to be statistically significant. The optimal cut-off values of the age, NLR, LMR, PLR, LDH, CRP, and Procalcitonin were calculated by applying the receiver operating curve (ROC) analysis.
| Results|| |
611 laboratory-confirmed COVID-19 cases were included in our study. There were 602 adults and 9 children. The male to female ratio was 3.7:1 and the median age was 50 yrs (youngest patient was 1 year old and the oldest patient was of 92 years). There were 332 males and 110 females in the severity group. There were 442 (72.3%) patients in non-severe group and 169 (27.7%) in the severe group. Out of total cases, the number of survivors was 530 (86.7%) and non-survivors were 81 (13.3%) patients. Out of 169 severe patients, 88 patients survived. The most common presenting complaint was fever (95.4%) and cough (58.9%). The median hospital stay was 8 days (7 days for non-severe group and 13 days for the severe group). However median hospital stay for the non-survival group was 7 days (ranging from 1 day to 25 days) and for the survival group, it was 8 days (ranging from 2 to 35 days). The comorbidity percentage was 63.9% for the severe group and 22.7% for the non-severe group. [Figure 1] shows Pie chart showing the percentage of different comorbid conditions of both the severe and the non-severe groups.
|Figure 1: Pie Chart showing percentage of different comorbid conditions in Severe and Non Severe Group|
Click here to view
Results of NLR, LMR, PLR, LDH, CRP, and PCT of Study Subjects
Comparison of laboratory findings between the male and female are shown in [Table 1]. In males, the median age was 51 years and the mean NLR, LMR, PLR, LDH, CRP, and Procalcitonin were 8.78, 6.85, 178.4, 903.6, 95.2, and 1.13 respectively. In the females median age was 48 years and the mean values of above-mentioned biomarkers were 4.80, 17.5, 143.1, 760.9, 49.1, and 0.75, respectively. The mean value of these biomarkers was found to be elevated more in males. P values of all were statistically significant except procalcitonin.
|Table 1: Comaparison of mean age, NLR, LMR, PLR, LDH, CRP, PCT Of Covid-19 patients on the basis of gender|
Click here to view
[Table 2] shows a comparison of laboratory findings between non-severe and severe groups. The Mean values of NLR, LMR, PLR, LDH, CRP, and Procalcitonin for the non-severe group were 4.16, 10.8, 133.7, 666.1, 49.9, and 0.15, respectively and in the severe group were 17.8, 4.69, 268.2, 1277, 158.6, and 3.05, respectively. These Mean values were higher in the severe group except LMR. These were found to be statistically significant except LMR.
|Table 2: Comaparison of mean age, NLR, LMR, PLR, LDH, CRP, PCT Of Covid-19 patients on the basis of severity|
Click here to view
[Table 3] shows a comparison of laboratory findings between non-survivor and the survivor groups. Mean NLR, LMR, PLR, LDH, CRP, and Procalcitonin for the survivor group were 6.47, 9.79, 157.6, 775.3, 69.5, and 0.81, respectively. In non-survivor group there were 17.5, 4.6, 258.2, 1439.3, 180.8, and 2.82, respectively. Non-survivor group had higher mean values of these immune-inflammatory biomarkers. Except LMR and LDH, all had statistically significant P value.
|Table 3: Comaparison of mean age, NLR, LMR, PLR, LDH, CRP, PCT Of Covid-19 patients on the basis of survival|
Click here to view
Use of the Optimum Cut-off Values of Laboratory Results to Differentiate Severe from Non-severe COVID-19 Infection
The diagnostic accuracy of each variable was evaluated by ROC curve analysis in both severity and survival groups. We analyzed the optimal cut-off values calculated by the ROC analysis. [Figure 2] shows the ROC curve of the severe and non-severe groups. In [Table 4], for severity group, area under curve (AUC) of age, NLR, LMR, PLR, LDH, CRP, and Procalcitonin were 0.74, 0.92, 0.15, 0.81, 0.88, 0.81, and 0.76 and the optimal cut-off values were 57.5, 6.47, 189.2, 845.8, 97, and 0.095, respectively. Highest sensitivity and specificity for age, NLR, PLR, LDH, CRP, and Procalcitonin were 0.58 and 0.75, 0.88 and 0.83, 0.70 and 0.75, 0.81 and 0.83, 0.66 and 0.80, 0.75 and 0.62, respectively.
|Table 4: Areas under the curve (AUC) of NLR, LMR, PLR, LDH, CRP, PCT (Severity Group)|
Click here to view
[Figure 3] shows the ROC curve of the survival and non-survival group. In [Table 5], for survival group, area under curve (AUC) of age, NLR, LMR, PLR, LDH, CRP, and Procalcitonin were 0.70, 0.80, 0.25, 0.74, 0.81, 0.76, and 0.74 and the optimal cut-off values were 57.5, 8.67, 210.6, 1035.9, 125.8, and 0.135, respectively. Highest sensitivity and specificity for age, NLR, PLR, LDH, CRP, and Procalcitonin were 0.60 and 0.67, 0.78 and 0.71, 0.60 and 0.725, 0.73 and 0.77, 0.60 and 0.75, 0.60 and 0.75, respectively. These were found to be potential diagnostic biomarkers except LMR as its AUC was less than 0.50.
|Table 5: Areas under the curve (AUC) of NLR, LMR, PLR, LDH, CRP, PCT (Survival Group)|
Click here to view
Association of NLR, LMR, PLR, LDH, CRP and Procalcitonin Results with the Risk of COVID-19 Pneumonia
To identify the factors affecting COVID-19 progression, we calculated the crude odds ratio (OR). Criteria for pneumonia was chest X-ray which was routinely done in all COVID-19 patients in our hospital. Given that the blood test results were influenced by age and gender, we excluded the possible effects of age and gender and obtained the adjusted odds ratio after the adjustment of gender and age. [Table 6] shows, odds ratio (OR) and adjusted odds ratio (ORa) of the severity group, and [Table 7] shows the odds ratio (OR) and adjusted odds ratio (ORa) of the survival group. All the biomarkers had statistically significant P value for the odds ratio. However, NLR and LDH had P values less than 0.05 for the adjusted odds ratio in the severity group and only LDH had a statistically significant P value in the survival group. NLR, PLR, LDH, CRP, and Procalcitonin were found to be positively correlated with the risk of COVID-19.
|Table 6: The OR and ORa in each of the NLR, LMR, PLR, LDH, CRP, PCT (Severity Group)|
Click here to view
|Table 7: The OR and ORa in each of the NLR, LMR, PLR, LDH, CRP, PCT (Survival Group)|
Click here to view
| Discussion|| |
COVID-19 results in rapid onset of generalized inflammation. In recent publications,, fever and cough were the dominant symptoms in COVID-19 patients, as found in the present study. Fever was more frequently absent in COVID-19 than in SARS-CoV (1%) and MERS-CoV infection (2%) and such patients may be missed if the surveillance is based on fever detection. Median hospital stay was found to be more in the severe group than non-severe group. However, the median hospital stay of severe patients who did not survive was 7 days. The severe group had more comorbidities. Diabetes was the most common comorbid condition in non-severe group and hypertension most common comorbid condition for the severe group. Individuals with pre-existing comorbidities are at a substantially higher risk of dying from COVID-19, according to evidence from the global outbreak. Angiotensin-converting enzyme inhibitors (ACEI) and angiotensin-receptor blockers are routinely used to treat hypertensive individuals (ARB). Many believe that ACEI and ARB are to blame for the increased risk in hypertensive patients because they might increase ACE2 expression. The underlying pathogenesis of comorbidities may increase vulnerability to hyperinflammation and cytokine storm upon SARS-CoV-2 infection, resulting in severe COVID-19.
The demographic characteristics of our study showed that males were affected more often than females. This is in accordance with various studies conducted by Guan WJ et al., Zhang JJ et al., Nanshan Chenet al. There were 9 pediatric patients. All of them were in non-severe group and did not present with Pediatric Multisystem Inflammatory syndrome. The number of cases (611) was comparable with the study done by Ma et al. (635). In our study, the mean age of the severe group and non-survivor group was higher than non-severe group and survivor group which is in accordance with other studies.
In the present study, mean values of NLR, PLR, LDH, CRP, and PCT were higher in severe and no-survivor group and were found to be statistically significant. These immune-inflammatory markers were found to be potential diagnostic biomarkers except LMR as its AUC was less than 0.50. [Table 8] and [Table 9] show comparison of various studies. Hence, our results proved our hypothesis and indicated that elevated NLR, PLR, LDH, CRP, and Procalcitonin were potential prognostic biomarkers in predicting the severity of COVID-19. Our findings were consistent with those of previous studies on the relationship between these biomarkers and the severity and prognosis of COVID-19., In this study, these biomarkers were found to be positively correlated with the risk of COVID-19, however, adjusted odds ratio calculated after normalization of sex and age showed only NLR and LDH to be associated with risk of covid 19 for severity group [Table 6] and [Table 7] and adjusted odds ratio of survival group showed only LDH to be positively correlated. This is in accordance with the study done by Yang et al. This finding suggests LDH be a better biomarker for COVID-19 in this study.
|Table 8: Comparision of NLR and PLR of severity group among various studies|
Click here to view
|Table 9: Comparision of CRP and PCT of severity group among various studies|
Click here to view
Innate and adaptive immune responses are activated by SARS-CoV-2 infection. Cao et al. have proposed that local and systemic tissue damage is due to excessive inflammatory drive of innate and adaptive response. NLR is a better biomarker for systemic inflammation and illness severity than a single neutrophil or lymphocyte count. In our study, we confirmed that an increased NLR usually indicates higher disease severity. This may be due to the fact that most the severe COVID-19 patients exhibit substantially elevated serum levels of proinflammatory cytokines (such as interleukin-6 and interleukin-8, tumor necrosis factor-alpha, and granulocyte colony-stimulating factor, and interferon-gamma) and inflammatory biomarkers which trigger neutrophils. The triggered neutrophils dampen the virus infection by producing reactive oxygen species (ROS) and other cytotoxic mediators. Lymphocytes were significantly decreased in severe and critically ill patients. Decrease or exhaustion of lymphocyte in severe cases may be due to viruses attacking and damaging target cells and causing immune cells to enter an activated state which results in systemic inflammation and stimulate the production of neutrophil and speed up the apoptosis of lymphocyte. Severe COVID-19 patients have an increase of PCT and CRP, indicating a potential bacterial co-infection or superinfection which might affect the immune response.
| Conclusion|| |
The present study is one of the first studies from COVID-19 dedicated hospital in the eastern part of the Indian subcontinent Incorporating a higher number of patients. This study shows that NLR, PLR, LDH, CRP, and Procalcitonin may be a rapid, widely available, useful severity predictor of COVID-19 patients. We found that NLR which is quickly calculated from routine CBC can be used to determine the severity of Covid-19. Hypertension was the most common comorbid condition in severe COVID-19 patients. LDH was found to be a better severity biomarker for COVID-19 in this study.
Statement of Ethics
The study was approved by the institutional ethical committee.
Dr Shalini, Senior Resident (Department of Obstetrics and Gynaecology, AIIMS, Patna) for the help in data collection and tabulation.
Financial Support and Sponsorship
Conflicts of Interest
There are no conflicts of interest.
| References|| |
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.
Hui DS, Azhar IE, Madani TA, Ntoumi F, Kock R, Dar O, et al
. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health-The latest 2019 novel coronavirus outbreak in Wuhan, China. Int J Infect Dis 2020;91:264-6.
Gorbalenya A, Baker S, Baric R, de Groot R. The species severe acute respiratory syndrome-related coronavirus: Classifying 2019-nCoV and naming it SARS-CoV-2. Nat Microbiol 2020;5:536-44.
Lu H, Stratton CW, Tang Y. Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. J Med Virol 2020;92:401-2.
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.
Li K, Wu J, Wu F, Guo D, Chen L, Fang Z, et al
. The clinical and chest CT features associated with severe and critical COVID-19 pneumonia. Invest Radiol 2020;55:327-31.
Zhang J-J, Dong X, Cao Y-Y, Yuan Y-D, Yang Y-B, Yan Y-Q, et al
. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy 2020;75:1730-41.
Guthrie GJ, Charles KA, Roxburgh CS, Horgan PG, McMillan DC, Clarke SJ. The systemic inflammation-based neutrophil-lymphocyte ratio: Experience in patients with cancer. Crit Rev Oncol Hematol 2013;88:218-30.
Huang K-J, Su I-J, Theron M, Wu Y-C, Lai S-K, Liu C-C, et al
. An interferon-gamma-related cytokine storm in SARS patients. J Med Virol 2005;75:185-94.
Chen L, Kong X, Yan C, Fang Y, Wang J. The research progress on the prognostic value of the common hematological parameters in peripheral venous blood in breast cancer. Onco Targets Ther 2020;13:1397-412.
Chen J-H, Zhai E-T, Yuan Y-J, Wu K-M, Xu J-B, Peng J-J, et al
. Systemic immune-inflammation index for predicting prognosis of colorectal cancer. World J. Gastroenterol 2017;23:6261-72.
Tai H, Zhu Z, Mei H, Sun W, Zhang W. Albumin-to-fibrinogen ratio independently predicts 28-day mortality in patients with peritonitis-induced sepsis. Mediators Inflamm 2020;2020:7280708.
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.
Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al
. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: A retrospective cohort study. Lancet 2020;395:1054-62.
Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al
. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol 2020;146:110-8.
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al
. A novel Coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020;382:727-33.
Song H-D, Tu C-C, Zhang G-W, Wang S-Y, Zheng K, Lei L-C, et al
. Cross-host evolution of severe acute respiratory syndrome coronavirus in palm civet and human. Proc Natl Acad Sci USA 2005;102:2430-5.
Callender LA, Curran M, Bates SM, Mairesse M, Weigandt J, Betts CJ. The impact of pre-existing comorbidities and therapeutic interventions on COVID-19. Front Immunol 2020;11:1991.
Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, He J-x, et al
. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20.
Ma Y, Shi N, Fan Y, et al
. Predictive value of the neutrophil- to-lymphocyte ratio (NLR) for diagnosis and worse clinical course of the COVID-19: Findings from ten provinces in China. 2020. Available from: https://ssrn.com/abstract=3569838
Feng X, Li S, Sun Q, Zhu J, Chen B, Xiong M, et al
. Immune-inflammatory parameters in COVID-19 cases: A systematic review and meta-analysis. Front Med (Lausanne) 2020;7:301.
Chan AS, Rout A. Use of neutrophil-to-lymphocyte and platelet-to- lymphocyte ratios in COVID-19. J Clin Med Res 2020;12:448-53.
Yang A-P, Lui J-p, Tao W-q, Li H-m. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol 2020;84:106504.
Gong J, Ou J, Qiu X, Jie Y, Chen Y, Yuan L, et al
. A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): A Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China. Clin Infect Dis 2020;71:833-40.
Sun S, Cai X, Wang H, He G, Lin Y, Lu B, et al
. Abnormalities of peripheral blood system in patientswith COVID-19 in Wenzhou, China. Clin Chim Acta 2020;507:174-80.
Zhu Z, Cai T, Fan L, Lou K, Hua X, Huang Z, et al
. Clinical value of immune-inflammatory parameters to assess the severity of coronavirus disease 2019. Int J Infect Dis 2020;95:332-9.
Cheng B, Gui T-M, Huang L, et al
. Clinical features predicting mortality risk in older patients with COVID-19. 2020. Available from: https://ssrn.com/abstract 3569846
Zhang B, Zhou X, Zhu C, Song Y, Feng F, Qiu Y, et al
. Immune phenotyping based on the neutrophil-to-lymphocyte ratio and IgG level predicts disease severity and outcome for patients with COVID-19. Front Mol Biosci 2020;7:157.
Zhang Y, Zheng L, Liu L, Zhao M, Xiao J, Zhao Q. Liver impairment in COVID-19 patients: A retrospective analysis of 115 cases from a single centre in Wuhan city, China. Liver Int 2020;40:2095-103.
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.
Cai Q, Huang D, Ou P, Yu H, Zhu Z, Xia Z, et al
. COVID-19 in a designated infectious diseases hospital outside Hubei Province, China. Allergy 2020;75:1742-52.
Gao W, Yang X, Zhang XQ, Su X, Dou AH, Hui W, et al
. Clinical characteristic of 90 patients with COVID-19 hospitalized in a grade-A hospital in Beijing. Acad J Chin PLA Med Sch 2020.
Li D, Long Y, Huang P, Guo W, Wu S, Zhou Q, et al
. Clinical characteristics of 80 patients with COVID-19 in Zhuzhou City. Chin J Infect Control 2020;3:227-33.
Peng YD, Meng K, Guan HQ, Leng L, Zhu RR, Wang BY, et al
. Clinical characteristics and outcomes of 112 cardiovascular disease patients infected by 2019-nCoV. Zhonghua Xin Xue Guan Bing Za Zhi 2020;48:450-5.
Qin C, Zhou L, Hu Z, Zhang S, Yang S, Tao Y, et al
. Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin Infect Dis 2020;71:762-8.
Wan Q, Shi A, He T, Tang L. Analysis of clinical features of 153 patients with novel coronavirus pneumonia in Chongqing. Chin J Clin Infect Dis. 2020;1:16-20.
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;180:934-43.
Cao X. COVID-19: Immunopathology and its implications for therapy. Nat Rev Immunol 2020;20:269-70.
Agraz-Cibrian JM, Giraldo DM, Mary FM, Urcuqui-Inchima S. Understanding the molecular mechanisms of NETs and their role in antiviral innate immunity. Virus Res 2017;228:124-33.
Chen X, Tong J, Xiang J, Hu J. Retrospective study on the epidemiological characteristics of 139 patients with novel coronavirus pneumonia on the effects of severity. Chongqing Med 2020.
Department of Pathology, All India Institute of Medical Sciences, Phulwarisharif, Patna - 801 507, Bihar
Source of Support: None, Conflict of Interest: None
[Figure 1], [Figure 2], [Figure 3]
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7], [Table 8], [Table 9]