Role of Serum Ferritin, D-Dimer, and C-Reactive Protein Parameters in COVID 19 Severity

Document Type : Original Articles

Authors

Department of Biology, College of Science, University of Baghdad, Baghdad, Iraq

Abstract

Following the epidemics caused by the transmission of the common virus between humans and animals (COVID-19), coronavirus 2 (SARS-CoV-2) is the third and most deadly strain of RNA virus that can cause respiratory, digestive, and nervous system problems, and there are many unknown complications. This study included 170 clinical samples of nasopharyngeal swaps (100 patients and 70 controls for both males and females). RT-PCR was performed, and blood samples were taken for biochemical analyses. They were obtained from Iraqi patients aged 25 to 92 years old. Between November 2021 and March 2022, COVID-19 patients were admitted to Dar al-salam Hospital, Alyarmok Teaching Hospital, and Alshefaa Hospital. AFIAS D-Dimer, AFIAS ferritin, and NycoCard CRP tests were performed on the patients and were classified depending on the severity of their infection (mild or moderate, severe and critical). The results showed a significant increase in ferritin in critically ill patients (545.58 ± 57.71). A significant increase of D-dimer was found with different severity with highly significant in the critical group (3.93 ± 0.79). With varying degrees of severity, a substantial rise in CRP was discovered with highly significant in the critical group (96.27 ± 14.55) between the severity group (p-value <0.001). Also, COVID-19 individuals in the age range (50 – 60) tended to be more severe than younger people, whereas the effect of gender is not significant in any patient group. The biochemical factors, including D-Dimer, ferritin, and CRP, are effective in the disease's occurrence of symptoms and severity.

Keywords

Main Subjects


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  2. Gao Y, Li T, Han M, Li X, Wu D, Xu Y, et al. Diagnostic utility of clinical laboratory data determinations for patients with the severe COVID-19. J Med Virol. 2020;92(7):791-6.
  3. Mo P, Xing Y, Xiao Y, Deng L, Zhao Q, Wang H, et al. Clinical characteristics of refractory coronavirus disease 2019 in Wuhan, China. Clin Infect Dis. 2021;73(11):e4208-e13.
  4. Luo X, Zhou W, Yan X, Guo T, Wang B, Xia H, et al. Prognostic value of C-reactive protein in patients with coronavirus 2019. Clin Infect Dis. 2020;71(16):2174-9.
  5. Wang G, Wu C, Zhang Q, Wu F, Yu B, Lv J, et al., editors. C-reactive protein level may predict the risk of COVID-19 aggravation. Open forum infectious diseases; 2020: Oxford University Press US.
  6. 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(6):669-77.
1. Rothe C, Schunk M, Sothmann P, Bretzel G,
Froeschl G, Wallrauch C, et al. Transmission of 2019-
nCoV infection from an asymptomatic contact in Germany.
N Engl J Med. 2020;382(10):970-1.
2. Xu C, Luo X, Yu C, Cao S-J. The 2019-nCoV
epidemic control strategies and future challenges of
building healthy smart cities. SAGE Publications Sage UK:
London, England; 2020. p. 639-44.
3. Chen Y, Liu Q, Guo D. Emerging coronaviruses:
genome structure, replication, and pathogenesis. J Med
Virol. 2020;92(4):418-23.
4. Hotez PJ, Bottazzi ME, Corry DB. The potential
role of Th17 immune responses in coronavirus
immunopathology and vaccine-induced immune
enhancement. Elsevier; 2020. p. 165-7.
5. Jin Y, Yang H, Ji W, Wu W, Chen S, Zhang W, et
al. Virology, epidemiology, pathogenesis, and control of
COVID-19. Viruses. 2020;12(4):372.
6. De Haan CA, Kuo L, Masters PS, Vennema H,
Rottier PJ. Coronavirus particle assembly: primary
structure requirements of the membrane protein. J Virol.
1998;72(8):6838-50.
7. Woo PC, Huang Y, Lau SK, Yuen K-Y.
Coronavirus genomics and bioinformatics analysis.
Viruses. 2010;2(8):1804-20.
8. Al-Suhail RGA, Ali LF. Statistical Analysis of
COVID-19 Pandemic Across the Provinces of Iraq. Iraqi J
Sci. 2021:811-24.
9. Ghahramani S, Tabrizi R, Lankarani KB, Kashani
SMA, Rezaei S, Zeidi N, et al. Laboratory features of
severe vs. non-severe COVID-19 patients in Asian
populations: a systematic review and meta-analysis. Eur J
Med Res. 2020;25(1):1-10.
10. Salehi-Abari I, Khazaeli S, Salehi-Abari F, SalehiAbari A. Practical guideline for screening the patients with
SARS-CoV-2 infection and Persian Gulf criteria for
diagnosis of COVID-19. Adv Infect Dis. 2020;10(03):67.
11. Yang A-P, Liu 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.
12. Cary N. Statistical analysis system, User's guide.
Statistical. Version 9. SAS Inst Inc USA. 2012.
13. Kernan KF, Carcillo JA. Hyperferritinemia and
inflammation. Int Immunol. 2017;29(9):401-9.
14. Taneri PE, Gómez-Ochoa SA, Llanaj E, Raguindin
PF, Rojas LZ, Roa-Díaz ZM, et al. Anemia and iron
metabolism in COVID-19: a systematic review and metaanalysis. Eur J Epidemiol. 2020;35(8):763-73.
15. 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(1):110-8.
16. 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(10229):1054-
62.
742 Abdullateef Abdullah et al / Archives of Razi Institute, Vol. 78, No. 2 (2023) 737-742
17. Cao P, Wu Y, Wu S, Wu T, Zhang Q, Zhang R, et
al. Elevated serum ferritin level effectively discriminates
severity illness and predicts prognosis of COVID-19
patients. 2020.
18. Tang N, Li D, Wang X, Sun Z. Des paramètres de
coagulation anormaux sont associés à un mauvais pronostic
chez les patients atteints de pneumonie à nouveau
coronavirus. J Thromb Haemost. 2020;18(4):844-7.
19. Querol-Ribelles JM, Tenias JM, Grau E, QuerolBorras JM, Climent JL, Gomez E, et al. Plasma d-dimer
levels correlate with outcomes in patients with communityacquired pneumonia. Chest. 2004;126(4):1087-92.
20. Snijders D, Schoorl M, Schoorl M, Bartels PC,
van der Werf TS, Boersma WG. D-dimer levels in
assessing severity and clinical outcome in patients with
community-acquired pneumonia. A secondary analysis of
a randomised clinical trial. Eur J Intern Med.
2012;23(5):436-41.
21. 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(10223):507-13.
22. Chen T, Wu D, Chen H, Yan W, Yang D, Chen G,
et al. Clinical characteristics of 113 deceased patients with
 coronavirus disease 2019: retrospective study. BMJ.
2020;368.
23. Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, He Jx, et al. Clinical characteristics of coronavirus disease 2019
in China. N Engl J Med. 2020;382(18):1708-20.
24. Gao Y, Li T, Han M, Li X, Wu D, Xu Y, et al.
Diagnostic utility of clinical laboratory data determinations
for patients with the severe COVID-19. J Med Virol.
2020;92(7):791-6.
25. Mo P, Xing Y, Xiao Y, Deng L, Zhao Q, Wang H,
et al. Clinical characteristics of refractory coronavirus
disease 2019 in Wuhan, China. Clin Infect Dis.
2021;73(11):e4208-e13.
26. Luo X, Zhou W, Yan X, Guo T, Wang B, Xia H, et
al. Prognostic value of C-reactive protein in patients with
coronavirus 2019. Clin Infect Dis. 2020;71(16):2174-9.
27. Wang G, Wu C, Zhang Q, Wu F, Yu B, Lv J, et al.,
editors. C-reactive protein level may predict the risk of
COVID-19 aggravation. Open forum infectious diseases;
2020: Oxford University Press US.
28. 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(6):669-77.1. Rothe C, Schunk M, Sothmann P, Bretzel G,
Froeschl G, Wallrauch C, et al. Transmission of 2019-
nCoV infection from an asymptomatic contact in Germany.
N Engl J Med. 2020;382(10):970-1.
2. Xu C, Luo X, Yu C, Cao S-J. The 2019-nCoV
epidemic control strategies and future challenges of
building healthy smart cities. SAGE Publications Sage UK:
London, England; 2020. p. 639-44.
3. Chen Y, Liu Q, Guo D. Emerging coronaviruses:
genome structure, replication, and pathogenesis. J Med
Virol. 2020;92(4):418-23.
4. Hotez PJ, Bottazzi ME, Corry DB. The potential
role of Th17 immune responses in coronavirus
immunopathology and vaccine-induced immune
enhancement. Elsevier; 2020. p. 165-7.
5. Jin Y, Yang H, Ji W, Wu W, Chen S, Zhang W, et
al. Virology, epidemiology, pathogenesis, and control of
COVID-19. Viruses. 2020;12(4):372.
6. De Haan CA, Kuo L, Masters PS, Vennema H,
Rottier PJ. Coronavirus particle assembly: primary
structure requirements of the membrane protein. J Virol.
1998;72(8):6838-50.
7. Woo PC, Huang Y, Lau SK, Yuen K-Y.
Coronavirus genomics and bioinformatics analysis.
Viruses. 2010;2(8):1804-20.
8. Al-Suhail RGA, Ali LF. Statistical Analysis of
COVID-19 Pandemic Across the Provinces of Iraq. Iraqi J
Sci. 2021:811-24.
9. Ghahramani S, Tabrizi R, Lankarani KB, Kashani
SMA, Rezaei S, Zeidi N, et al. Laboratory features of
severe vs. non-severe COVID-19 patients in Asian
populations: a systematic review and meta-analysis. Eur J
Med Res. 2020;25(1):1-10.
10. Salehi-Abari I, Khazaeli S, Salehi-Abari F, SalehiAbari A. Practical guideline for screening the patients with
SARS-CoV-2 infection and Persian Gulf criteria for
diagnosis of COVID-19. Adv Infect Dis. 2020;10(03):67.
11. Yang A-P, Liu 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.
12. Cary N. Statistical analysis system, User's guide.
Statistical. Version 9. SAS Inst Inc USA. 2012.
13. Kernan KF, Carcillo JA. Hyperferritinemia and
inflammation. Int Immunol. 2017;29(9):401-9.
14. Taneri PE, Gómez-Ochoa SA, Llanaj E, Raguindin
PF, Rojas LZ, Roa-Díaz ZM, et al. Anemia and iron
metabolism in COVID-19: a systematic review and metaanalysis. Eur J Epidemiol. 2020;35(8):763-73.
15. 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(1):110-8.
16. 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(10229):1054-
62.
742 Abdullateef Abdullah et al / Archives of Razi Institute, Vol. 78, No. 2 (2023) 737-742
17. Cao P, Wu Y, Wu S, Wu T, Zhang Q, Zhang R, et
al. Elevated serum ferritin level effectively discriminates
severity illness and predicts prognosis of COVID-19
patients. 2020.
18. Tang N, Li D, Wang X, Sun Z. Des paramètres de
coagulation anormaux sont associés à un mauvais pronostic
chez les patients atteints de pneumonie à nouveau
coronavirus. J Thromb Haemost. 2020;18(4):844-7.
19. Querol-Ribelles JM, Tenias JM, Grau E, QuerolBorras JM, Climent JL, Gomez E, et al. Plasma d-dimer
levels correlate with outcomes in patients with communityacquired pneumonia. Chest. 2004;126(4):1087-92.
20. Snijders D, Schoorl M, Schoorl M, Bartels PC,
van der Werf TS, Boersma WG. D-dimer levels in
assessing severity and clinical outcome in patients with
community-acquired pneumonia. A secondary analysis of
a randomised clinical trial. Eur J Intern Med.
2012;23(5):436-41.
21. 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(10223):507-13.
22. Chen T, Wu D, Chen H, Yan W, Yang D, Chen G,
et al. Clinical characteristics of 113 deceased patients with
 coronavirus disease 2019: retrospective study. BMJ.
2020;368.
23. Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, He Jx, et al. Clinical characteristics of coronavirus disease 2019
in China. N Engl J Med. 2020;382(18):1708-20.
24. Gao Y, Li T, Han M, Li X, Wu D, Xu Y, et al.
Diagnostic utility of clinical laboratory data determinations
for patients with the severe COVID-19. J Med Virol.
2020;92(7):791-6.
25. Mo P, Xing Y, Xiao Y, Deng L, Zhao Q, Wang H,
et al. Clinical characteristics of refractory coronavirus
disease 2019 in Wuhan, China. Clin Infect Dis.
2021;73(11):e4208-e13.
26. Luo X, Zhou W, Yan X, Guo T, Wang B, Xia H, et
al. Prognostic value of C-reactive protein in patients with
coronavirus 2019. Clin Infect Dis. 2020;71(16):2174-9.
27. Wang G, Wu C, Zhang Q, Wu F, Yu B, Lv J, et al.,
editors. C-reactive protein level may predict the risk of
COVID-19 aggravation. Open forum infectious diseases;
2020: Oxford University Press US.
28. 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(6):669-77.