Abstract
Objectives
We investigated the occurrence of non-respiratory bacterial and fungal secondary infections, causative organisms, impact on clinical outcomes, and association between the secondary pathogens and mortality in hospitalized patients with coronavirus disease 2019 (COVID-19).
Methods
This was a retrospective cohort study that included data from inpatients with COVID-19 from multiple centers participating in the Japan COVID-19 Taskforce (April 2020 to May 2021). We obtained demographic, epidemiological, and microbiological data throughout the course of hospitalization and analyzed the cases of COVID-19 complicated by non-respiratory bacterial infections.
Results
Of the 1914 patients included, non-respiratory bacterial infections with COVID-19 were diagnosed in 81 patients (4.2%). Of these, 59 (3.1%) were secondary infections. Bacteremia was the most frequent bacterial infection, occurring in 33 cases (55.9%), followed by urinary tract infections in 16 cases (27.1%). Staphylococcus epidermidis was the most common causative organism of bacteremia. Patients with COVID-19 with non-respiratory secondary bacterial infections had significantly higher mortality, and a multivariate logistic regression analysis demonstrated that those with bacteremia (aOdds Ratio = 15.3 [5.97–39.1]) were at higher risk of death. Multivariate logistic regression analysis showed that age, male sex, use of steroids to treat COVID-19, and intensive care unit admission increased the risk for nosocomial bacteremia.
Conclusions
Secondary bacteremia is an important complication that may lead to poor prognosis in cases with COVID-19. An appropriate medical management strategy must be established, especially for patients with concomitant predisposing factors.
Keywords: SARS-CoV-2 infection, Bacteremia, Secondary infection, Fungemia, Mortality
Non-respiratory bacterial secondary infections are not considered a common complication in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection [1]. However, these complications, represented by bacteremia with coronavirus disease 2019 (COVID-19), have been associated with poor prognosis [2,3]. Characteristics of these non-respiratory secondary bacterial infections, including incidence rate, site of infection, causative organisms, and impact on clinical outcomes, have not been investigated simultaneously in a single study. In this study, we investigated these items in hospitalized patients with COVID-19.
Patients with COVID-19 were recruited through the Japan COVID-19 Task Force, the largest Japanese cohort with biospecimen resources, and a large-scale multicenter retrospective study was conducted [4,5]. From April 2020 to May 2021, data from consenting inpatients aged 18 years or older were registered in an electronic case record at the affiliated research institute. The patients were diagnosed with COVID-19 using a SARS-CoV2 polymerase chain reaction test or an antigen test, at one of the 157 affiliated hospitals. Patients with incomplete medical records were excluded (Fig. 1 ). We obtained written or oral informed consent from all the enrolled patients, and the study was approved by the ethics committees of Keio University School of Medicine (20,200,061) and related research institutions. The following information was obtained: age, sex, body mass index (BMI), comorbidities, treatment, length of hospital stay, and disease severity parameters such as intensive care unit (ICU) admission and survival rates. During the course of hospitalization, standard microbiological tests were performed when bacterial infections were suspected. The diagnosis of bacterial infection was determined by the attending clinician. If the bacterial infection was diagnosed after 48 h of COVID-19 admission, it was defined as a hospital-acquired secondary infection [6]. To assess the impact of bacterial infection on COVID-19 severity and the risk of bloodstream infection, we conducted univariate and multivariate logistic regression analyses adjusted for patient characteristics, including BMI group, age, sex, chronic obstructive pulmonary disease (COPD), and presence of comorbidities associated with COVID-19 severity [[7], [8], [9], [10],14]. We presented the adjusted odds ratio (aOR) with a 95% CI. Statistical significance was set at p < 0.05. All data were analyzed using the JMP 16 program (SAS Institute Japan Ltd., Tokyo, Japan).
Fig. 1.
Study flow chart: identification and selection. A total of 75 records were excluded from the 1989 cases registered in the COVID-19 taskforce database because of the following reasons: 26 lacked essential clinical information, and 49 had an unknown outcome. Ultimately, 1914 cases met the eligibility criteria, of which 228 had complications from bacterial infections. Among these cases, 81 were non-respiratory bacterial infections: 22 co-infections and 59 secondary infections. COVID-19, coronavirus disease 2019.
We assessed a total of 1989 adult patients with COVID-19 at one of the hospitals that participated in the Japan COVID-19 Task Force. Of these, 1914 patients met the inclusion criteria, and 228 (11.9%) had bacterial infections along with COVID-19. Non-respiratory bacterial infections with COVID-19 were diagnosed in 81 patients (4.2%). Of these, 59 (3.1%) were found to be secondary infections (Fig. 1). Infectious disease specialists were involved in COVID-19 treatment in almost all participating facilities in our study, and the clinicians were supervised by the Antimicrobial Stewardship Team and Infection Control Team. Most of these secondary infections occurred in general hospitals with more than 500 beds, including university hospitals (49/59 cases). The details of secondary extrapulmonary infections and organisms identified from culture samples are shown in Table 1 . Bacteremia was found to be the most common finding, occurring in 33 cases (55.9%), followed by urinary tract infections in 16 cases (27.1%). Catheter-related events accounted for the majority of the bacteremia cases. Staphylococcus epidermidis was the most common causative organism of bacteremia, and Candida albicans or Candida parapsilosis was detected in five patients (Table 1). We found that patients with COVID-19 with non-respiratory secondary bacterial infections had significantly higher mortality, higher ICU admission rate, and longer hospitalization compared to those without bacterial infections (Supplementary Figs. 1 and 2). Among these infections, bacteremia was significantly associated with worse mortality (Fig. 2 A). A multivariate logistic regression analysis demonstrated that those with bacteremia (aOR = 15.3 [5.97–39.1]) were at higher risk of death (Fig. 2B). Among the cases of secondary infection, fungemia resulted in significant worsening of mortality compared to non-fungemia (Fig. 2C). Moreover, multivariate logistic regression analysis showed that age (aOR = 1.05 [1.02–1.08]), male sex (aOR = 6.55 [1.51–28.4]), use of steroids to treat COVID-19 (aOR = 4.19 [1.20–14.7]), and ICU admission (aOR = 5.23 [2.25–12.1]) increased the risk for nosocomial bacteremia (Fig. 2D). Additionally, patients with prior broad-spectrum antimicrobial use had a significantly higher incidence of secondary infections (Fig. 2E).
Table 1.
Bacterial pathogens detected in patients with coronavirus disease 2019 (COVID-19) and extrapulmonary secondary bacterial infections.
| Total 59 | 63 events | Bacteremia | Urinary tract infection | ||
|---|---|---|---|---|---|
| Bacteremia | 33 | Staphylococcus Epidermidis * | 10 | Escherichia coli * | 7 |
| Urinary tract infection | 16 | Enterococcus faecium | 4 | Candida albicans | 3 |
| Clostridioides difficile infection | 4 | Enterococcus faecalis | 4 | Enterococcus faecalis | 2 |
| Sinusitis | 1 | Staphylococcus aureus (MRSA) | 4 | Klebsiella oxytoca | 1 |
| Streptococcal pharyngitis | 1 | Candida albicans | 3 | Proteus mirabilis | 1 |
| Acute pancreatitis・Intraperitoneal abscess | 1 | Candida parapsilosis | 2 | Aerococcus species | 1 |
| Enteritis | 1 | Propionibacterium acnes | 2 | Actinobaculum schaalii | 1 |
| Wound infection at tracheostomy site | 1 | Klebsiella pneumoniae | 1 | Klebsiella pneumoniae | 1 |
| Intramuscular abscess | 1 | Pseudomonas aerginosa | 1 | Staphylococcus hominis | 1 |
| Tympanitis | 1 | Enterobacter cloacae | 1 | Staphylococcus aureus (MRSA) | 1 |
| Appendicitis | 1 | Staphylococcus capitis | 1 | Streptococcus anginosus | 1 |
| Mastitis | 1 | Staphylococcus haemolyticus | 1 | *Extended-spectrum β-lactamase | |
| Cholecystitis | 1 | Bacteroides thetaiotaomicron | 1 | producing bacteria = 3 cases | |
| Klebsiella oxytoca | 1 | ||||
| Empedobacter brevis | 1 | ||||
| Focus of bacteremia events | 33 | Escherichia coli | 1 | Acute pancreatitis・Intraperitoneal abscess | |
| Central line-associated bloodstream infection | 14 | Bacillus cereus | 1 | Candida krusei | 1 |
| Urinary tract infection | 2 | Enterococcus faecium | 1 | ||
| Appendicitis | 1 | *Methicillin-Resistant | Enterococcus faecalis | 1 | |
| Acute pancreatitis・Intraperitoneal abscess | 1 | Staphylococcus epidermidis | Klebsialla pneumoniae | 1 | |
| Unknown | 15 | (MRSE) = 3 cases | Staphylococcus haemolyticus | 1 | |
| Wound infection at tracheostomy site | |||||
| Clostridioides difficile infection | 4 | Pseudomonas aeruginosa | 1 | ||
| Clostridioides difficile | 4 | Staphylococcus epidermidis | 1 | ||
Fig. 2.
A. Difference in mortality rates depending on the site of secondary infection. Result of the univariate analysis. Proportion of deaths in patients with COVID-19 without bacterial infections (n = 1686) and with secondary bacterial infections consisting of bacteremia (n = 33), urinary tract infection (n = 16), and other secondary infection (n = 14). COVID-19, coronavirus disease 2019. *p < 0.05, **p < 0.01 B. Risk factors for death. Forest plot of the adjusted Odds ratio using a multiple logistic analysis of the risk factors for death in patients with COVID-19 and secondary bacteremia (n = 1719). COVID-19, coronavirus disease 2019; COPD, chronic obstructive pulmonary disease. *p < 0.05 C. Comparison of mortality between patients with fungemia (n = 5) and non fungal bloodstream infections (n = 28). Results of univariate analysis. Proportion of deaths in COVID-19-associated bacteremia. COVID-19, coronavirus disease 2019. *p < 0.05 D. Risk factors for secondary bacteremia. Forest plot of the adjusted odds ratio using a multiple logistic analysis of the risk factors of secondary bacteremia (n = 1719). IL-6, interleukin 6. COVID-19, coronavirus disease 2019. E. Association of secondary infection development with prior broad-spectrum antimicrobial use. A total of 316 patients had a history of antimicrobial use, and 1429 did not. *p < 0.05, **p < 0.01.
Our research is novel in three respects. First, this is the first large-scale study to identify the site of extrapulmonary bacterial infections, their causative organisms, and clinical outcomes in hospitalized Japanese COVID-19 patients. Previous studies have examined the association of secondary bacteremia with clinical outcomes, such as length of hospitalization and mortality [2,3,11,12]. Consistent with these studies, we found that secondary bacteremia is a serious, albeit infrequent, complication in the Japanese population. Second, we have indicated that fungemia has a worse prognosis than non-fungal bloodstream infections in Japanese COVID-19 patients. Although poor prognosis in patients with COVID-19-associated candidemia has been reported [13], our study demonstrated that the mortality associated with fungemia was higher than that associated with non-fungal infections. Third, this study identified multiple risk factors for secondary bacteremia. Khatri et al. reported that immunosuppressive therapy predisposed COVID-19 patients to developing bloodstream infections [12]. Our findings also suggested that steroid administration is independently associated with the development of bacteremia. Glucocorticoids are widely used to treat severe cases of COVID-19, as their efficacy has been proven [14]. Considering this, clinicians must stay vigilant and perform careful evaluations as steroids often reduce body temperature and levels of acute phase proteins such as C-reactive protein, and may thereby mask signs of infection. In addition, the present study also revealed an association between male sex, older age, and ICU admission as risk factors for bacteremia. These factors have not been reported in previous studies and are considered one of the novelties of our study. Our findings suggest that clinicians need to be particularly cautious when treating elderly male COVID-19 patients in the ICU, in order to prevent bacteremia.
Our study has several limitations that should be acknowledged. First, it does not include cases of Omicron variants, and thus we have not been able to assess the differences in the complication rate of bacterial infections and their impact on the clinical course caused by changes of the prevalent COVID-19 mutant variants. Second, the diagnosis of bacterial complications was entirely dependent on the clinical judgment of the respective physician, and microbiological tests were not necessarily required to prove the causative pathogens. Therefore, Table 1 might include bacteria that are uncommon as causative organisms, and the possibility of contamination cannot be completely excluded. We recognize that this is one of the major limitations of our study. Regrettably, in this multicenter study we were unable to prospectively assess all cases for the rigorous approach to detect bacterial pathogens. Third, the sample size of this study was determined incidentally and was not designed to be statistically sufficient for detecting the effects of complications from bacterial infections on severe illness and death. Hence, further studies are needed to address these limitations and develop optimal treatment strategies.
In conclusion, secondary bacteremia is an important complication that may lead to poor prognosis in cases of COVID-19. Therefore, an appropriate medical management strategy including early detection of bacteremia needs to be established, especially for patients with concomitant predisposing factors.
Authorship statement
All authors meet the criteria specified in the ICMJE guidelines.
Conceptualization: K.N., H.K., S.C., H.N., K.M., H.K., M.I., N.H., K.F. Data curation and interpretation: K.N., H.K., S.C., H.N., H.T., H.L., S.O., T.F., T.K., A.M., S.A., M.W., K.M., T.A, M.I., A.E., R.K., H.I., T.T., Y.M., N.H., H.K., T.Y., K.K., Y.M., M.M., S.U., H.O., T.O., T.S., H.M., K.K., N.M., T.M., M.F., Y.C., Y.N., M.O., M.A., T.O., M.T., K.N., Y.S., R.E., A.A, N. H., S.O., Y.K., T.K., T.K., Y.K., N.M., T.T., S.F., K.M., H.S., Y.S., Y.T., R.O., S.M., M.K., Y.H., Y.H., T.U., Y.T., T.I., A.F., N.K., H.K., E.H., Y.N., F.S., Y.K., S.A., T.I., T.O., Y.K., H.W., M.M., H.W., Y.K., A.K., Y.K., S.H., Y.O., T.T., K.K., M.A., A.K., T.S., K.T., S.I., Y.K., A.K., S.M., N.H., S.O., T,K., K.F. Formal analysis: K.N., H.K., S.C., H.N. Methodology: K.N., H.K., S.C., H.N. Supervision: K.N., H.K., S.C., H.N. K.M., M.I., N.H., N.H., T.U., S.U., T.I., K.A., F.S., T.Y., Y.N., Y.M., Y.S., K.M., Y.O., R.K., Y.K., A.K., S.I., S.M., S.O., T.K., K.F. Visualization: H.K., S.C., H.N. Writing—original draft: K.N., H.K. Writing—review and editing: K.N., H.K., S.O., H.T., H.L., A.M., T.F., M.W., T.K., R.K., T.T., N.H., T.Y.,Y.M., S.U., H.O., T.S., K.K., T.M., Y.O., T.T., M.O., T.O., K.N., R.E., N.H., Y.K., T.K., N.M., T.Y., K.M., M.Y., Y.S., Y.S., S.M., S.H., Y.H., T.U., T.I., N.K., T.K.,T.O., F.S., Y.K., S.A., T.I., Y.K., H.W., H.W., M.N., Y.K., S.H., Y.O., T.T., K.K., M.A., A.K., T.S., K.T., S.I., Y.K., A.K., S.M., N.H., S.O., T.K., K.F.
Ethics approval
This study was approved by the ethics committee of Keio University School of Medicine (20,200,061) and affiliated institutes.
Funding
This study was supported by AMED (JP20nk0101612, JP20fk0108415, JP21jk0210034, JP21km0405211, JP21km0405217); JST CREST (JPMJCR20H2); MHLW (20CA2054); Takeda Science Foundation; Mitsubishi Foundation; and Bioinformatics Initiative of Osaka University Graduate School of Medicine, Osaka University.
Data availability statement
Data that support the findings of this study are available from the corresponding author upon reasonable request.
Declaration of competing interest
The authors declare that they have no conflicts of interest.
Acknowledgements
We would like to thank all the participants involved in this study and all members of the Japan COVID-19 Task Force engaged in clinical management and research on COVID-19. All members contributed cases to this study.
Footnotes
Supplementary data to this article can be found online at https://doi.org/10.1016/j.jiac.2023.01.006.
Appendix A. Supplementary data
The following are the Supplementary data to this article.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
Data that support the findings of this study are available from the corresponding author upon reasonable request.