Prognostic value of serum amyloid A in COVID-19: A meta-analysis. Issue 7 (18th February 2022)

• Record Type: Journal Article
• Authors: Li, Yongkai; Xiaojing, He; Zhuanyun, Li; Li, Dandan; Yang, Jianzhong
• Other Names: Kumar. Pavan section editor.
• Is Part Of: Medicine. Volume 101:Issue 7(2022)
• Publication Date: 2022-02-18
• Subjects: coronavirus disease 2019 -- meta-analysis -- serum amyloid A; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000028880
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract: Background: There is still a lack of large-scale clinical studies and evidence-based evidence to prove the relationship between serum amyloid A (SAA) and the severity and prognosis of patients with new coronavirus pneumonia (COVID-19). Methods: We searched PubMed, Cochrane Library, Excerpta Medica Database, and Web of Science for original articles from December 1, 2019 to December 19, 2020. Search criteria include free text search, explosive MESH/EMTREE terms, and all synonyms for SAA and COVID-19. There are no language restrictions on the searched documents. Statistical methods were performed using Stata 14.0 software, and RevMan 5.4 software provided by the Cochrane Collaboration for meta-analysis. The 10 included studies in the literature were classified according to the severity of the novel coronavirus treatment guidelines, with mild/moderate categorized as nonsevere and severe/critical as severe, and the data were meta-analyzed using multiple subgroup standard deviations combined. Severe and nonsevere were finally divided into 2 groups, and the combined data were meta-analyzed according to the standardized mean difference. Results: The results of the meta-analysis given by random effects showed that SAA levels were significantly higher in severe vs nonsevere (standardized mean difference 1.20 [95% confidence interval 0.91–1.48]), which was statistically significant ( P < .001). The 3 literatures studied (random effect size 0.11 [95% confidence interval 0.05–0.19]; I 2 = 56.68%) and were statistically significant, z = 5.46 P < .01, suggesting that the risk of death occurs at higher levels with increasing SAA values, with the risk of death in the severe group being 11% higher than in the nonsevere group. Conclusion: SAA can be considered as a biomarker for predicting the severity and prognosis of COVID-19. SAA can be used for early warning of the poor prognosis of COVID-19 and for monitoring the recovery process, which has important clinical value.