Skip to main content
Elsevier - PMC COVID-19 Collection logoLink to Elsevier - PMC COVID-19 Collection
. 2022 May 26;158(12):603–607. doi: 10.1016/j.medcle.2021.06.022

Influence of influenza vaccine and comorbidity on the evolution of hospitalized COVID-19 patients⋆

Influencia de la vacunación antigripal y la comorbilidad en la evolución de los pacientes hospitalizados por COVID-19

José Manuel Fernández Ibáñez a,, María del Carmen Morales Ballesteros a, Manuel José Fernández Anguita b, María Ángeles Galindo Andúgar d, Ángel Arias Arias c, José Ramón Barberá-Farré d
PMCID: PMC9132981  PMID: 35637933

Abstract

Background and objective

The COVID-19 coronavirus disease outbreak is evolving around the world. Objective: To evaluate the associations between influenza vaccination and other factors and the risk of mortality in hospitalized COVID-19 patients.

Materials and methods

Retrospective observational study. This study was conducted among hospitalized patients with COVID-19 at Hospital La Mancha Centro between March 5 and 25, 2020. Information on influenza vaccination was extracted from electronic medical records. We used a multivariate logistic regression to explore the association between influenza vaccination and mortality from COVID and other risk factors.

Results

410 patients were included. Influenza vaccine had no effect among COVID-19 hospitalized patients [OR: 1.55 (95%CI: 0.96–2.48; p = 0.071)]. Increasing hospital mortality was associated with older age [OR: 1.05 (95% CI 1.02–1.07), per year increase; p < 0.001)], Charlson ≥3 [OR: 1.84 (95%CI: 1.07–3.15, p = 0.027)] and heart failure on admission [OR: 6 (IC95%: 1.6–21.7; p = 0.007)].

Conclusions

Influenza vaccine had no effect among COVID-19 hospitalized patients. The risk factors identified were older age, higher comorbidity and heart failure on admission.

Keywords: Influenza vaccine, COVID-19, Hospitalized patients, Age, Comorbidity, Mortality

Introduction

COVID-19 is a disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has given rise to a pandemic that began in Wuhan (China) in December 2019. By February 2021, the number of cases worldwide had exceeded 103 million with more than 2.2 million deaths.1

There are currently no treatments with a sufficient level of evidence. Most countries have resorted to public health measures such as isolation, quarantine, and social distancing to prevent the spread of the disease.

Until vaccination for SARS-CoV-2 becomes universally available, several authors suggest that influenza vaccination may offer cross-protection against respiratory viruses other than influenza and minimise the severity of COVID-192 disease.

Other authors propose increasing influenza vaccination rates to avoid co-infection of influenza with SARS-CoV-2.3 However, others suggest that vaccination may increase susceptibility to SARS-CoV-2 infection.4

This article analyses the influence of influenza vaccination and other prognostic factors on the mortality of COVID-19 patients admitted to the Mancha Centro hospital during the first wave of the pandemic.

Material and methods

Design and participants

Retrospective observational cohort study. A total of 410 patients admitted with a diagnosis of COVID-19 at the Hospital Mancha Centro from 5 to 25 March 2020 were consecutively included. Information on influenza vaccination in the fall of 2019 was obtained from Primary Care records.

The diagnosis of COVID-19 was confirmed by polymerase chain reaction (PCR) testing. Patients with negative PCR, inconclusive PCR or no PCR but with high clinical suspicion of disease were also included.

Variables studied

The main outcome variable was mortality. Influenza vaccination was the main independent variable. Control covariates were age, sex, residence (community or institution), functionality (Barthel scale), comorbidity (Charlson index), and underlying comorbidities on admission: Obesity, chronic respiratory diseases, ischemic heart disease and/or heart failure, kidney failure, chronic liver disease, hematologic malignancies, other neoplasms, receiving immunosuppressive treatment, diabetes, high blood pressure (HBP), cognitive impairment and other neurological diseases and depression. Heart failure and cardiovascular events during admission were also included.

Statistical analysis

Quantitative variables were described by mean and standard deviation (SD) and qualitative variables by absolute and relative frequencies.

By means of a bivariate analysis we identified the factors involved in mortality, using Student's t test for quantitative variables and the χ2 test (or Fisher's exact test) for qualitative variables.

A multivariate analysis (binary logistic regression) was performed to independently identify possible risk factors and the role of influenza vaccination in the mortality of admitted COVID-19 patients.

All analyses were performed using the SPSS v18 statistical software and a p-value < 0.05 was considered statistically significant.

Results

410 patients admitted for COVID-19 were included. The mean age was 70.7 years (SD: 13.9; range 28-100). 49.3% were men and 50.7% women; 209 (51%) were vaccinated against influenza (101 men and 108 women) and 201 (49%) were not. The Barthel scale was >60 in 84.4% of cases and ≤60 in 15.6%. The Charlson index was < 3 in 78.8% and ≥ 3 in 21.2% of cases. The most common chronic diseases were hypertension (62.4% of patients), chronic respiratory diseases (35.4%), neurological diseases (35.4% including cognitive impairment), diabetes (26.6%) and obesity (21.5%). The PCR test was positive in 354 patients (86.3%), negative in 35 (8.5%), inconclusive in 6 (1.5%) and not performed in 15 (3.7%). 5.9% of patients (24) were admitted to the intensive care unit (ICU) and hospital mortality was 34.6% (142) (Table 1 ).

Table 1.

Main characteristics of the patients included in the study and differences between vaccinated and unvaccinated patients.

Overall (n = 410) Unvaccinated (n = 201) Vaccinated (n = 209) p
Mean age in years (SD; range) 70.7 (13.9; 28–100) 65.6 (14.3) 75.6 (11.6) <0.001
Age by groups
 Under 65 132 (32.2%) 103 (51.2%) 29 (13.9%) <0.001
 Between 65 and 75 years 103 (25.1%) 45 (22.4%) 58 (27.8%)
 Between 75 and 85 years 113 (27.6%) 30 (14.9%) 83 (39.7%)
 More than 85 years 62 (15.1%) 23 (11.4%) 39 (18.7%)
Sex
 Male 202 (49.3%) 101 (50.2%) 101 (48.3%) 0.697
 Female 208 (50.7%) 100 (49.8%) 108 (51.7%)
Barthel
 > 60 319 (77.8%) 167 (89.8%) 152 (79.2%) 0.004
 ≤ 60 59 (14.4%) 19 (10.2%) 40 (20.8%)
 Not available 32 (7.8%)
Charlson
 <3 232 (78.8%) 176 (87.6%) 147 (70.3%) <0.001
 ≥ 87 (21.2%) 25 (12.4%) 62 (29.7%)
Comorbidities
 Obesity 88 (21.5%) 40 (19.9%) 48 (23%) 0.450
 Chronic Respiratory Disease 145 (35.4%) 49 (24.4%) 96 (45.9%) <0.001
 Ischemic heart disease / Heart failure 50 (12.2%) 14 (7%) 36 (17.2%) 0.002
 Renal failure 49 (12%) 20 (10%) 29 (13.9%) 0.221
 Chronic liver disease 7 (1.7%) 4 (2%) 3 (1.4%) 0.719
 Hematologic malignancy 9 (2.2%) 4 (2%) 5 (2.4%) 0.999
 Other neoplasms 60 (7.3%) 12 (6%) 18 (8.6%) 0.304
 Diabetes 109 (26.6%) 37 (18.4%) 72 (34.4%) <0.001
 HBP 256 (62.4%) 106 (52.7%) 150 (71.8%) <0.001
 Cognitive impairment 49 (12%) 16 (8%) 33 (15.8%) 0.015
 Other neurological diseases 96 (23.4%) 41 (20.4%) 55 (26.3%) 0.157
 Depressive syndrome 61 (14.9%) 27 (13.4%) 34 (16.3%) 0.420
Heart failure on admission 20 (4.9%) 6 (3%) 14 (6.7%) 0.081
Cardiovascular event during admission 6 (1.5%) Twenty-one% 4 (1.9%) 0.686
Immunosuppressive treatment 14 (3.4%) 6 (3%) 8 (3.8%) 0.639
Institutionalized 32 (7.8%) 10 (5%) 22 (10.5%) 0.036
ICU admission 24 (5.9%) 18 (9%) 6 (2.9%) 0.009
In-hospital death 142 (34.6%) 49 (24.4%) 93 (44.5%) <0.001

Vaccinated patients had a higher percentage of over 65 year olds (86.2%), higher level of dependency (Barthel < 60 20.8 vs. 10.2%; p = 0.004 vs. non-vaccinated), had a higher comorbidity (Charlson > 3 29.7 vs. 12.4%; p < 0.001), a higher percentage of chronic respiratory diseases (45.9 vs. 24.4%; p < 0.001), ischaemic heart disease (17.2 vs. 7%; p = 0.002), diabetes (34.4 vs. 18.4%; p < 0.001), HBP (71.8 vs. 52.7%; p < 0.001), cognitive impairment (15.8 vs. 8%; p = 0.015) and institutionalised patients (10.5 vs. 5%; p = 0.036). Vaccinated patients were admitted to the ICU less often (2.9 vs. 9%; p = 0.009) (Table 1).

Factors associated with mortality were: age, being more significant with increasing age (61.3% of patients over 85 years of age died), Barthel scale (patients with Barthel ≤ 60 [54.2 vs. 29.5%; p < 0.001]), Charlson index ≥ 3 (56.3 vs. 28.8%; p < 0.001), history of ischaemic heart disease/heart failure (56 vs. 31.7%; p < 0.001), having non-haematological malignancies (63.3 vs. 32.4%; p = 0.001), AHT (42.2 vs. 22.1%; p < 0.001), renal failure (53.1 vs. 32.1%; p = 0.004), being institutionalised (53.1 vs. 33.1%; p = 0.022) and influenza vaccination (44.5 vs. 24.4%; p < 0.001). Another risk factor for mortality is the presence of heart failure during admission (85 vs. 32.1%; p < 0.001) (Table 2 ).

Table 2.

Factors associated with hospital mortality according to bivariate analysis.

No death (n = 268) Death (n = 142) p
Mean age in years (SD) 67.4 (13.8) 77 (12) <0.001
Age groups
 Under 65 113 (85.6%) 19 (14.4%) <0.001
 Between 65 and 75 years 67 (65%) 36 (35%)
 Between 75 and 85 years 64 (56.6%) 49 (43.4%)
 More than 85 years 24 (38.7%) 38 (61.3%)
Sex
 Male 131 (64.9%) 71 (35.1%) 0.829
 Female 137 (65.9%) 71 (34.1%)
Barthel
 > 60 225 (70.5%) 94 (29.5%) <0.001
 ≤ 60 27 (45.8%) 32 (54.2%)
 Not available
Charlson
 < 3 230 (71.2%) 93 (28.8%) <0.001
 = > 38 (43.7%) 49 (56.3%)
Obesity
 Yes 51 (58%) 37 (42%) 0.099
 No 217 (67.4%) 105 (32.6%)
Respiratory disease
Chronic
 Yes 86 (59.3%) 59 (40.7%) 0.057
 No 182 (68.7%) 83 (31.3%)
Ischemic Heart Disease / Heart Failure
 Yes 22 (44%) 28 (56%) <0.001
 No 246 (68.3%) 114 (31.7%)
Renal failure
 Yes 23 (46.9%) 26 (53.1%) 0.004
 No 245 (67.9%) 116 (32.1%)
Chronic liver disease
 Yes 5 (71.4%) 2 (28.6%) 0.999
 No 263 (65.3%) 140 (34.7%)
Hematologic malignancy
 Yes 4 (44.4%) 5 (55.6%) 0.286
 No 264 (65.8%) 137 (34.2%)
Other neoplasms
 Yes 11 (36.7%) 189 (63.3%) 0.001
 No 257 (67.6%) 123 (32.4%)
Diabetes
 Yes 68 (62.4%) 41 (37.6%) 0.445
 No 200 (66.4%) 101 (33.6%)
HBP
 Yes 148 (57.8%) 108 (42.2%) <0.001
 No 120 (77.9%) 34 (22.1%)
Cognitive impairment
 Yes 29 (59.2%) 20 (40.8%) 0.332
 No 239 (66.2%) 122 (33.8%)
Other neurological diseases
 Yes 58 (60.4%) 38 (39.6%) 0.244
 No 210 (66.9%) 104 (33.1%)
Depressive syndrome
 Yes 35 (57.4%) 26 (42.6%) 0.155
 No 233 (66.8%) 116 (33.2%)
Heart failure during admission
 Yes 3 (15%) 17 (85%) <0.001
 No 265 (67.9%) 125 (32.1%)
Cardiovascular event during admission
 Yes 2 (33.3%) 4 (66.7%) 0.190
 No 262 (65.5%) 138 (34.5%)
Immunosuppressive treatment
 Yes 9 (64.3%) 5 (35.7%) 0.999
 No 259 (65.4%) 137 (34.6%)
Institutionalized
 Yes 15 (46.9%) 17 (53.1%) 0.022
 No 253 (66.9%) 125 (33.1%)
Influenza vaccine
 Yes 116 (55.5%) 93 (44.5%) <0.001
 No 152 (75.6%) 49 (24.4%)
ICU admission
 Yes 14 (58.3%) 10 (41.7%) 0.456
 No 254 (65.8%) 132 (34.2%)

The multivariate analysis finally identified age (OR: 1.05 [95% CI; 1.02–1.07 per year increase; p < 0.001]), Charlson index > 3 (OR: 1.84 [95% CI; 1.07–3.15; p = 0.027]) and having heart failure during admission (OR: 6 [95% CI; 1.6–21.7; p = 0.007]) as independent risk factors for in-hospital mortality. Influenza vaccination had no association with mortality (OR: 1.55 [0.96–2.48; p = 0.071]) (Table 3 ).

Table 3.

Multivariate analysis of factors associated with mortality.

Variables OR (95% CI) p
Age 1.045 (1.024−1.066) <0.001
Charlson (≥ 3 vs <3) 1.835 (1.07−3.148) 0.027
Heart failure on admission 5.993 (1.625−21.659) 0.007
Influenza vaccine 1.545 (0.963−2.477) 0.071

Discussion

This study shows that influenza vaccination has no effect on mortality in patients admitted for COVID-19 in agreement with other authors.5, 6

Vaccinated patients are older and have higher comorbidity, which are the factors associated with higher mortality in COVID-19 patients with no influence from influenza vaccination.

Age, a high number of comorbidities prior to admission, and the presence of heart failure at admission were the risk factors independently associated with higher hospital mortality in COVID-19 patients.

The vast majority of studies find age as an independent risk factor for mortality in COVID-19 patients which could be explained in relation to immunosenescence.7

Our high comorbidity patients have a significantly higher mortality compared to those with low comorbidity8, in line with other studies.8

The presence of heart failure at admission was shown to be an important independent predictor of mortality in our study. According to some studies, left ventricular diastolic dysfunction is reported to be common in acute SARS infection, even among those without underlying heart disease.9

Our study has some limitations. We have not included analytical data that may be associated with increased mortality in various studies,8 but our aim was to assess influenza vaccination and other comorbidities on the risk of in-hospital mortality. Nor have the treatments administered during admission been taken into account, due to their heterogeneity and the low level of evidence in the published studies.10 Additionally, the epidemiological situation may have determined the criteria for admission and bed availability and influenced mortality outcomes.

The strengths of our study were that the vast majority of COVID-19 cases were laboratory confirmed and all patient data were systematically collected, so we believe that the sample is representative of COVID-19 cases managed in our area.

Conclusions

Influenza vaccination does not seem to have an effect on hospital mortality in COVID-19 patients admitted to our hospital. Age, high comorbidity, and the presence of heart failure at admission are independent prognostic factors for mortality, which could help physicians identify patients with a poor prognosis for their management and treatment

Funding

This paper has not received any type of funding.

Conflict of interests

The authors declare that they have no conflict of interest.

Footnotes

Please cite this article as: Fernández Ibáñez JM, Morales Ballesteros MC, Fernández Anguita MJ, Galindo Andúgar MÁ, Arias Arias Á, Barberá-Farré JR. Influencia de la vacunación antigripal y la comorbilidad en la evolución de los pacientes hospitalizados por COVID-19. Med Clin (Barc). 2022;158:603–607.

References

  • 1.COVID-19 Map - Johns Hopkins Coronavirus Resource Center. [Accessed 4 January 2021]. Available from: https://coronavirus.jhu.edu/map.html.
  • 2.Zheng J., Perlman S. Immune responses in influenza A virus and human coronavirus infections: an ongoing battle between the virus and host. Curr Opin Virol. 2018;28:43–52. doi: 10.1016/j.coviro.2017.11.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Zanettini C., Omar M., Dinalankara W., Luidy E., Colantuoni E., Luidy Imada E., et al. Influenza vaccination and COVID-19 mortality in the USA: an ecological study. Vaccines (Basel) 2021;9:427. doi: 10.3390/vaccines9050427. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Tetro J.A. Is COVID-19 receiving ADE from other coronaviruses? Microbes Infect. 2020;22:72–73. doi: 10.1016/j.micinf.2020.02.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Skowronski D.M., Zou M., Clarke Q., Chambers C., Dickinson J.A., Sabaiduc S., et al. Influenza vaccine does not increase the risk of coronavirus or other noninfluenza respiratory viruses: retrospective analysis from Canada, 2010–2011 to 2016–2017. Clin Infect Dis. 2020;71:2285–2288. doi: 10.1093/cid/ciaa626. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Del Riccio M., Lorini C., Bonaccorsi G., Paget J., Caini S. The association between influenza vaccination and the risk of SARS-COV-2 infection, severe illness, and death: a systematic review of the literature. Int J Environ Res Public Health. 2020;17:1–9. doi: 10.3390/ijerph17217870. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Sun H., Ning R., Tao Y., Yu C., Deng X., Zhao C., et al. Risk factors for mortality in 244 older adults with covid-19 in Wuhan, China: a retrospective study. J Am Geriatr Soc. 2020;68:E19–E23. doi: 10.1111/jgs.16533. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Guan W.J., Liang W.H., Zhao Y., Liang H.R., Chen Z.S., Li Y.M., et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J. 2020;55 doi: 10.1183/13993003.00547-2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Shi S., Qin M., Shen B., Cai Y., Liu T., Yang F., et al. Association of cardiac injury with mortality in hospitalized patients with COVID-19 in Wuhan, China. JAMA Cardiol. 2020;5:802–810. doi: 10.1001/jamacardio.2020.0950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Song Y., Zhang M., Yin L., Wang K., Zhou Y., Zhou M., et al. COVID-19 treatment: close to a cure? A rapid review of pharmacotherapies for the novel coronavirus (SARS-CoV-2) Int J Antimicrob Agents. 2020;56 doi: 10.1016/j.ijantimicag.2020.106080. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Medicina Clinica (English Ed.) are provided here courtesy of Elsevier

RESOURCES