COVID-19 Patients with Recent Influenza A/B Infection: A Retrospective Study
Authors: Ping Wu, Wanrong Lu, Liang He, Yifan Meng, Peng Wu, Wencheng Ding, Ke Ma, Jia Liu
Journal: Journal of Infection (2020)

We read with the interest the recent paper by Chen et al. who described the clinical progression of 249 patients with coronavirus disease 2019 (COVID-19).1Chen J. et al.Clinical progression of patients with COVID-19 in Shanghai, China.J Infect. 2020; 80: e1-e6Abstract Full Text Full Text PDF PubMed Scopus (539) Google Scholar As the author mentioned, some factors, such as age and CD4 T cell counts, would be associated with intensive care units (ICU) admission. In addition, the application of host-directed therapy and early control of viral replication might be crucial for improving the prognosis of COVID-19. We are interested in investigating the potential risk factors associated with the progression and prognosis of COVID-19. To date, cases of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) and influenza A co-infection have been reported in COVID-19 patients.2Azekawa S. Namkoong H. Mitamura K. Kawaoka Y. Saito F. Co-infection with SARS-CoV-2 and influenza A virus.IDCases. 2020; 20: e00775Crossref PubMed Scopus (66) Google Scholar, 3Khodamoradi Z. Moghadami M. Lotfi M. Co-infection of Coronavirus Disease 2019 and Influenza A: A Report from Iran.Arch Iran Med. 2020; 23: 239-243Crossref PubMed Scopus (64) Google Scholar, 4Wu X. et al.Co-infection with SARS-CoV-2 and Influenza A Virus in Patient with Pneumonia, China.Emerg Infect Dis. 2020; 26Crossref Scopus (26) Google Scholar We suspected that the recent infection with influenza among COVID-19 patients might affect disease prognosis and progression to some extent. The high specificity and the sensitivity of Immunoglobulin M (IgM) assays suggest that IgM is a reliable biomarker for the surveillance of recent influenza infection.5Qiu C. et al.Early adaptive humoral immune responses and virus clearance in humans recently infected with pandemic 2009 H1N1 influenza virus.PLoS One. 2011; 6: e22603Crossref PubMed Scopus (12) Google Scholar,6Buchner Y.I. Heath R.B. Collins J.V. Pattison J.R. Serum IgM antibody and influenza A infection.J Clin Pathol. 1977; 30: 723-727Crossref PubMed Scopus (10) Google Scholar Here, we reported that recent infection of influenza A/B and produce specific IgM in COVID-19 might be a common phenomenon, and influenza IgM status could be the significant factor associated with clinical outcomes and prognosis of COVID-19. For this retrospective study, the 1386 COVID-19 patients were hospitalized between 18 January and 26 April 2020 at Tongji Hospital in Wuhan, China. All patients were pathogen-confirmed COVID-19 cases and accepted serological influenza A/B IgM antibody tests upon admission. SARS-CoV-2 infection was confirmed by reverse transcriptase polymerase chain reaction assay (RT-PCR), and the methods were consistent with other studies.7Huang C. et al.Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China.Lancet. 2020; 395: 497-506Abstract Full Text Full Text PDF PubMed Scopus (32456) Google Scholar The influenza A/B IgM antibody tests were conducted by indirect immunofluorescence assay (IIFA) of specific IgM antibodies (EUROIMMUN, FI 2821-17M, Germany). All operations were carried out according to the provided instructions. The patients analyzed in this study were not vaccinated against influenza A/B at the time of admission. In our study, severe COVID19 cases were defined as oxygen saturation of 94% or less while breathing ambient air or needing oxygen support, consistent with the report of Ohmagari et al. 8Grein J. et al.Compassionate Use of Remdesivir for Patients with Severe Covid-19.N Engl J Med. 2020; Crossref PubMed Scopus (2002) Google Scholar The Ethical Committee of Tongji Hospital approved the study. Informed consent was not obtained because this retrospective study was analyzed anonymously. We performed a retrospective analysis on 1386 confirmed COVID-19 patients with influenza A/B IgM antibody test results. In total, 88.8% (1231/1386) of patients survived and 11.2% (155/1386) of patients died. More than half of patients (60.8%, 842/1386) were identified as severe cases, and 39.3% (544 of 1386) were classified as non-severe. According to patients' specific IgM status, influenza A IgM positive (A IgM+) or negative (A IgM−) and influenza B IgM positive (B IgM+) or negative (B IgM−), the patients were divided into three categories: A IgM−/ B IgM− group (47.6%, 660/1386), A IgM+/ B IgM− group (47.5%, 659/1386), and A IgM−/ B IgM+ group (4.8%, 67/1386). The A IgM+/ B IgM+ group was not included as we identified no such cases. In Figure 1, in terms of the clinical outcome, the mortality rates of the A IgM+/ B IgM− group and A IgM−/ B IgM+ group were lower than that of the A IgM−/ B IgM− group. Figure 1 also indicates that the A IgM−/B IgM− group had the highest rate of severe cases among the three groups. Statistically significant differences existed across the different groups when considering mortality (P = 0.0008) and severe illness rates (P < 0.0001). To further explore the relationship between the influenza A/B IgM status and clinical outcome and illness severity among the COVID-19 patients, we established univariate analysis and multivariate analysis models (Table 1). For the univariate analysis, we found that sex, age, and comorbidities were significant cofactors among mortality and severe illness. The A IgM+/ B IgM− group has showed lower risk of mortality (OR =0.514, 95%CI: 0.360–0.732) and severe illness (OR =0.511, 95% CI:0.408–0.640). For multivariate analysis, after adjustment for cofactors, patients in the A IgM+/ B IgM− group were less likely to die than patients in the A IgM−/ B IgM− group (OR = 0.671, 95% CI: 0.463–0.973). However, the mortality rate of the A IgM−/ B IgM+ group was not statistically different from that of the A IgM−/ B IgM− group according to the adjusted model (OR = 0.903, 95% CI: 0.359–2.272). Furthermore, our analysis also indicated that a similar trend was also observed in severe/non-severe analysis. The A IgM+/B IgM− group had a lower rate of severe illness than the A IgM−/B IgM− group (OR = 0.601, 95% CI: 0.476–0.760), whereas no such difference was found for the A IgM−/B IgM+ group (OR = 0.968, 95% CI: 0.563–1.665).Table 1Univariate and multivariate analysis of risk factors of Death vs. Discharged or Severe vs.Non-severe.aThe statistically significant differences are shown in bold. Abbreviations: A IgM, influenza A IgM; B IgM, influenza B IgM; OR, odds ratio; 95%CI, 95% confidence interval; IQR, interquartile range.Variables[n(%)]Death vs. Discharged [OR (95%CI)]Severe vs. Non-severe [OR (95%CI)]Died (n=155)Discharged (n=1231)Non-severe (n=544)Severe (n=842)Univariate analysisMultivariate analysisUnivariate analysisMultivariate analysisSex Male104 (14.9)596 (85.1)251 (35.9)449 (64.1)REFREFREFREF Female51 (7.4)635 (92.6)293 (57.3)393 (42.7)0.460 (0.323-0.655)0.458 (0.316-0.662)0.750 (0.604-0.931)0.753 (0.599-0.946)Age (mean [SD])69.6 (12.2)57.1 (15.7)53.5 (16.4)61.7 (14.6)1.069 (1.054-1.085)1.067 (1.050-1.083)1.035 (1.027-1.042)1.035 (1.027-1.043)Comorbidities No64 (8.3)708 (91.7)324 (42.0)448 (58.0)REFREFREFREF Yes91 (14.8)523 (85.2)220 (35.8)394 (64.2)1.925 (1.371-2.702)1.154 (0.803-1.658)1.295 (1.041-1.611)0.863 (0.677-1.100)Influenza A/B IgM status groupsA IgM−/ B IgM−96 (14.6)564 (85.5)207 (31.4)453 (68.6)REFREFREFREFA IgM+/ B IgM−53 (8.0)606 (92.0)311 (47.2)348 (52.8)0.514 (0.360-0.732)0.671 (0.463-0.973)0.511 (0.408-0.640)0.601 (0.476-0.760)A IgM−/ B IgM+6 (9.0)61 (91.0)26 (38.8)41 (61.2)0.578 (0.243-1.374)0.903 (0.359-2.272)0.721 (0.429-1.210)0.968 (0.563-1.665)a The statistically significant differences are shown in bold.Abbreviations: A IgM, influenza A IgM; B IgM, influenza B IgM; OR, odds ratio; 95%CI, 95% confidence interval; IQR, interquartile range. Open table in a new tab In the analysis, older age, male gender, and comorbidities were more prone to poor outcomes and progression, which were consistent with previous studies.1Chen J. et al.Clinical progression of patients with COVID-19 in Shanghai, China.J Infect. 2020; 80: e1-e6Abstract Full Text Full Text PDF PubMed Scopus (539) Google Scholar,9Zhang J.J. et al.Clinical characteristics of 140 patients infected with SARS-CoV-2 in Wuhan, China.Allergy. 2020; Crossref Scopus (2534) Google Scholar Therefore, in the multivariate analysis, we adjusted these cofactors. We found that COVID-19 patients positive for influenza A IgM had a lower risk of mortality and severe illness compared with those showing negative A/B IgM status. However, these trends were not significant differences between A IgM−/ B IgM+ group and A IgM−/ B IgM− group. The reason for better prognosis and clinical outcome in influenza A IgM+ COVID-19 patients is likely complicated, but could be due to potential interactions between influenza A and SARS-Cov-2, or because IgM+ is a marker of patient functional immune status. However, the second hypothesis cannot fully explain why these protective effects were not observed among influenza B IgM+ COVID-19 patients. Due to the suddenness of the COVID-19 pandemic outbreak, more studies are needed to confirm these findings. In summary, our results showed that recent influenza A/B infection in confirmed COVID-19 patients might be a common phenomenon. Moreover, we also observed that COVID-19 patients positive for influenza A IgM showed a lower risk of mortality and severe illness compared with those showing negative A/B IgM status. In contrast, this trend was not observed in influenza B IgM+ patients. Jia Liu, Ping Wu, Wanrong Lu designed and conceived the study; Ping Wu, Wanrong Lu performed the statistical analysis and drafted the article; Liang He, Yifan Meng, Peng Wu, Wencheng Ding, Ke Ma contributed to data collection; Jia Liu made critical revisions to the manuscript. All authors revised and commented on the article and approved the final version before submission. All authors have declared there is no competing interest exists. We would like to show our great respect to all the workers and volunteers in the fight against COVID-19, especially to the medical workers who work with the authors on the frontline. This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.