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Vol 7, No 2 (2022)
Research paper
Published online: 2022-06-24
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Systematic review and meta-analysis of serum amyloid a prognostic value in patients with COVID-19

Bartosz Fialek1, Olha Yanvarova2, Michal Pruc3, Aleksandra Gasecka4, Alicja Skrobucha4, Maria Boszko4, Czeslaw Ducki5, Maciej Cyran6, Lukasz Szarpak7
·
Disaster Emerg Med J 2022;7(2):107-113.
Affiliations
  1. Rheumatology Department, Marshal Józef Piłsudski Memorial Hospital, Plonsk, Poland
  2. European School of Medicine, International European University, Kyiv, Ukraine
  3. Research Unit, Polish Society of Disaster Medicine, Warsaw, Poland
  4. First Chair and Department of Cardiology, Medical University of Warsaw, Warsaw, Poland
  5. Mazovian „Bródnowski” Hospital, Warsaw, Poland
  6. Institute of Outcomes Research, Maria Sklodowska-Curie Medical Academy, Warsaw, Poland
  7. Henry JN Taub Department of Emergency Medicine, Baylor College of Medicine, Houston, TX, United States

open access

Vol 7, No 2 (2022)
ORIGINAL ARTICLES
Published online: 2022-06-24

Abstract

INTRODUCTION: This study was designed to assess the levels of human serum amyloid A (SAA) among COVID-19 patients.
MATERIAL AND METHODS: A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. A comprehensive literature search was performed (PubMed, Web of Science, Scopus, and Cochrane network), and studies comparing SSA levels in: (A) with non-severe vs severe COVID-19; (B) severe vs critical COVID-19 condition; (C) survived vs died due to COVID-19 in-hospital treatment period — were included. Random-effects meta-analyses were performed to obtain pooled estimates.
RESULTS: Thirty studies met the criteria and were included in the meta-analysis. Pooled analysis showed that SAA levels were statistically significantly lover in non-severe group 58.7 ± 53.9 mg/L compared to 154.5 ± 169.6 mg/L for patients with severe condition (MD = –120.29; 95% CI: –135.35 to –105.22; p < 0.001). SAA levels among patients with critical condition were 89.5 ± 90.4 mg/L compared to 195.3 ± 206.2 mg/L (MD = –56.66; 95% CI: –101.81 to –11.51; p = 0.01). SAA levels in patient who survived were 108.7 ± 157.3 mg/L, and 206.8 ± 58.8 mg/L for patients who not survived (MD = –85.04; 95% CI: –145.78 to –24.29; p = 0.006).
CONCLUSIONS: In conclusion, this updated meta-analysis suggests that SAA concentrations are positively correlated with the severity of the COVID-19. Therefore, SAA can be considered a biomarker for predicting the severity and prognosis of COVID-19. Measurement of this parameter might assist clinicians in monitoring and evaluating the severity and prognosis of COVID-19.

Abstract

INTRODUCTION: This study was designed to assess the levels of human serum amyloid A (SAA) among COVID-19 patients.
MATERIAL AND METHODS: A systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis. A comprehensive literature search was performed (PubMed, Web of Science, Scopus, and Cochrane network), and studies comparing SSA levels in: (A) with non-severe vs severe COVID-19; (B) severe vs critical COVID-19 condition; (C) survived vs died due to COVID-19 in-hospital treatment period — were included. Random-effects meta-analyses were performed to obtain pooled estimates.
RESULTS: Thirty studies met the criteria and were included in the meta-analysis. Pooled analysis showed that SAA levels were statistically significantly lover in non-severe group 58.7 ± 53.9 mg/L compared to 154.5 ± 169.6 mg/L for patients with severe condition (MD = –120.29; 95% CI: –135.35 to –105.22; p < 0.001). SAA levels among patients with critical condition were 89.5 ± 90.4 mg/L compared to 195.3 ± 206.2 mg/L (MD = –56.66; 95% CI: –101.81 to –11.51; p = 0.01). SAA levels in patient who survived were 108.7 ± 157.3 mg/L, and 206.8 ± 58.8 mg/L for patients who not survived (MD = –85.04; 95% CI: –145.78 to –24.29; p = 0.006).
CONCLUSIONS: In conclusion, this updated meta-analysis suggests that SAA concentrations are positively correlated with the severity of the COVID-19. Therefore, SAA can be considered a biomarker for predicting the severity and prognosis of COVID-19. Measurement of this parameter might assist clinicians in monitoring and evaluating the severity and prognosis of COVID-19.

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Keywords

serum amyloid A; SAA; marker; SARS-CoV-2; COVID-19; meta-analysis

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Title

Systematic review and meta-analysis of serum amyloid a prognostic value in patients with COVID-19

Journal

Disaster and Emergency Medicine Journal

Issue

Vol 7, No 2 (2022)

Article type

Research paper

Pages

107-113

Published online

2022-06-24

Page views

4408

Article views/downloads

315

DOI

10.5603/DEMJ.a2022.0021

Bibliographic record

Disaster Emerg Med J 2022;7(2):107-113.

Keywords

serum amyloid A
SAA
marker
SARS-CoV-2
COVID-19
meta-analysis

Authors

Bartosz Fialek
Olha Yanvarova
Michal Pruc
Aleksandra Gasecka
Alicja Skrobucha
Maria Boszko
Czeslaw Ducki
Maciej Cyran
Lukasz Szarpak

References (47)
  1. Simonsen L, Viboud C. A comprehensive look at the COVID-19 pandemic death toll. Elife. 2021; 10.
  2. Tan C, Huang Y, Shi F, et al. C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early. J Med Virol. 2020; 92(7): 856–862.
  3. Wilson PG, Thompson JC, Shridas P, et al. Serum amyloid A, but not C-reactive protein, stimulates vascular proteoglycan synthesis in a pro-atherogenic manner. Am J Pathol. 2008; 173(6): 1902–1910.
  4. Page M, McKenzie J, Bossuyt P, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021: n71.
  5. Sterne J, Hernán M, Reeves B, et al. ROBINS-I: a tool for assessing risk of bias in non-randomised studies of interventions. BMJ. 2016(355): i4919.
  6. Sterne JAC, Savović J, Page MJ, et al. RoB 2: a revised tool for assessing risk of bias in randomised trials. BMJ. 2019; 366: l4898.
  7. McGuinness LA, Higgins JPT. Risk-of-bias visualization (robvis): an R package and shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021; 12(1): 55–61.
  8. Welton NJ, White IR, Lu G, et al. The interpretation of random-effects meta-analysis in decision models. Med Decis Making. 2005; 25(6): 646–654.
  9. Egger M, Davey Smith G, Schneider M, et al. Bias in meta-analysis detected by a simple, graphical test. BMJ. 1997; 315(7109): 629–634.
  10. Abdelhakam DA, Badr FM, Abd El Monem Teama M, et al. Serum amyloid A, ferritin and carcinoembryonic antigen as biomarkers of severity in patients with COVID-19. Biomed Rep. 2022; 16(2): 13.
  11. Bhatraju PK, Morrell ED, Zelnick L, et al. Comparison of host endothelial, epithelial and inflammatory response in ICU patients with and without COVID-19: a prospective observational cohort study. Crit Care. 2021; 25(1): 148.
  12. Chen R, Sang L, Jiang M, et al. Medical Treatment Expert Group for COVID-19. Longitudinal hematologic and immunologic variations associated with the progression of COVID-19 patients in China. J Allergy Clin Immunol. 2020; 146(1): 89–100.
  13. Chen M, Wu Y, Jia W, et al. The predictive value of serum amyloid A and C-reactive protein levels for the severity of coronavirus disease 2019. Am J Transl Res. 2020; 12(8): 4569–4575.
  14. Cheng Li, Yang JZ, Bai WH, et al. Prognostic value of serum amyloid A in patients with COVID-19. Infection. 2020; 48(5): 715–722.
  15. Dong Y, Zhou H, Li M, et al. A novel simple scoring model for predicting severity of patients with SARS-CoV-2 infection. Transbound Emerg Dis. 2020; 67(6): 2823–2829.
  16. Fu J, Huang PP, Zhang S, et al. The value of serum amyloid A for predicting the severity and recovery of COVID-19. Exp Ther Med. 2020; 20(4): 3571–3577.
  17. Gong J, Ou J, Qiu X, 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(15): 833–840.
  18. Haroun RAH, Osman WH, Eessa AM. Interferon-γ-induced protein 10 (IP-10) and serum amyloid A (SAA) are excellent biomarkers for the prediction of COVID-19 progression and severity. Life Sci. 2021; 269: 119019.
  19. Li L, Chen C. Contribution of acute-phase reaction proteins to the diagnosis and treatment of 2019 novel coronavirus disease (COVID-19). Epidemiol Infect. 2020; 148: e164.
  20. Li H, Xiang X, Ren H, et al. Serum Amyloid A is a biomarker of severe Coronavirus Disease and poor prognosis. J Infect. 2020; 80(6): 646–655.
  21. Liu SL, Wang SY, Sun YF, et al. Expressions of SAA, CRP, and FERR in different severities of COVID-19. Eur Rev Med Pharmacol Sci. 2020; 24(21): 11386–11394.
  22. Liu Q, Dai Y, Feng M, et al. Associations between serum amyloid A, interleukin-6, and COVID-19: A cross-sectional study. J Clin Lab Anal. 2020; 34(10): e23527.
  23. Liu J, Li S, Liu J, et al. Longitudinal characteristics of lymphocyte responses and cytokine profiles in the peripheral blood of SARS-CoV-2 infected patients. EBioMedicine. 2020; 55: 102763.
  24. Liu J, Tu C, Zhu M, et al. The clinical course and prognostic factors of severe COVID-19 in Wuhan, China: A retrospective case-control study. Medicine (Baltimore). 2021; 100(8): e23996.
  25. Liu N, Long H, Sun J, et al. New laboratory evidence for the association between endothelial dysfunction and COVID-19 disease progression. J Med Virol. 2022; 94(7): 3112–3120.
  26. Ma KL, Liu ZH, Cao CF, et al. COVID-19 myocarditis and severity factors: an adult cohort study. .
  27. Mo XN, Su ZQ, Lei CL, et al. Serum amyloid A is a predictor for prognosis of COVID-19. Respirology. 2020; 25(7): 764–765.
  28. Tufa A, Gebremariam T, Manyazewal T, et al. Cytokine and chemokine profile in patients hospitalized with COVID-19: A comparative study. [preprint]. 2022.
  29. Wang D, Li R, Wang J, et al. Correlation analysis between disease severity and clinical and biochemical characteristics of 143 cases of COVID-19 in Wuhan, China: a descriptive study. BMC Infect Dis. 2020; 20(1): 519.
  30. Wang R, Pan M, Zhang X, et al. Epidemiological and clinical features of 125 hospitalized patients with COVID-19 in Fuyang, Anhui, China. Int J Infect Dis. 2020; 95: 421–428.
  31. Wang Q, Cheng J, Shang J, et al. Clinical value of laboratory indicators for predicting disease progression and death in patients with COVID-19: a retrospective cohort study. BMJ Open. 2021; 11(10): e043790.
  32. Xia X, Wen M, Zhan S, et al. [An increased neutrophil/lymphocyte ratio is an early warning signal of severe COVID-19]. Nan Fang Yi Ke Da Xue Xue Bao. 2020; 40(3): 333–336.
  33. Xu Bo, Fan CY, Wang AL, et al. Suppressed T cell-mediated immunity in patients with COVID-19: A clinical retrospective study in Wuhan, China. J Infect. 2020; 81(1): e51–e60.
  34. Yang R, Gui X, Gao S, et al. Clinical progression and changes of chest CT findings among asymptomatic and pre-symptomatic patients with SARS-CoV-2 infection in Wuhan, China. Expert Rev Respir Med. 2021; 15(3): 411–417.
  35. Yu Y, Liu T, Shao L, et al. Novel biomarkers for the prediction of COVID-19 progression a retrospective, multi-center cohort study. Virulence. 2020; 11(1): 1569–1581.
  36. Zeng Z, Hong XY, Li Y, et al. Serum-soluble ST2 as a novel biomarker reflecting inflammatory status and illness severity in patients with COVID-19. Biomark Med. 2020; 14(17): 1619–1629.
  37. Zhang JJ, Dong X, Cao YY, et al. Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China. Allergy. 2020; 75(7): 1730–1741.
  38. Zhao K, Huang J, Dai D, et al. Serum iron level as a potential predictor of coronavirus disease 2019 severity and mortality: a retrospective study. Open Forum Infect Dis. 2020; 7(7): ofaa250.
  39. Zhou J, Xu XP, Xu F, et al. Clinical symptoms and psychological changes of patients with COVID-19 in Jiangxi Province. [preprint]. .
  40. Khan M, Khan H, Khan S, et al. Epidemiological and clinical characteristics of coronavirus disease (COVID-19) cases at a screening clinic during the early outbreak period: a single-centre study. J Med Microbiol. 2020; 69(8): 1114–1123.
  41. Zhou Y, Yang Q, Chi J, et al. Comorbidities and the risk of severe or fatal outcomes associated with coronavirus disease 2019: A systematic review and meta-analysis. Int J Infect Dis. 2020; 99: 47–56.
  42. Zeng F, Huang Y, Guo Y, et al. Association of inflammatory markers with the severity of COVID-19: a meta-analysis. Int J Infect Dis. 2020; 96: 467–474.
  43. Mahat RK, Panda S, Rathore V, et al. The dynamics of inflammatory markers in coronavirus disease-2019 (COVID-19) patients: A systematic review and meta-analysis. Clin Epidemiol Glob Health. 2021; 11: 100727.
  44. Li Y, Xiaojing He, Zhuanyun Li, et al. Prognostic value of serum amyloid A in COVID-19: A meta-analysis. Medicine (Baltimore). 2022; 101(7): e28880.
  45. Wang L, Yang LuM, Pei SF, et al. CRP, SAA, LDH, and DD predict poor prognosis of coronavirus disease (COVID-19): a meta-analysis from 7739 patients. Scand J Clin Lab Invest. 2021; 81(8): 679–686.
  46. Zhang D, Huang WJ, Lan MQ, et al. Association between serum amyloid A levels and predicting disase severity in COVID-19 patients: a systematic review and meta-analysis. Eur Rev Med Pharmacol Sci. 2021; 25(13): 4627–4638.
  47. Zinellu A, Paliogiannis P, Carru C, et al. Serum amyloid A concentrations, COVID-19 severity and mortality: an updated systematic review and meta-analysis. Int J Infect Dis. 2021; 105: 668–674.

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