International Journal of Infectious Diseases 118 (2022) 197–202 Contents lists available at ScienceDirect International Journal of Infectious Diseases journal homepage: www.elsevier.com/locate/ijid Bacterial co-infection at hospital admission in patients with COVID-19 Estela Moreno-García 1 , # , Pedro Puerta-Alcalde 1 , # , ∗, Laura Letona 1 , # , Fernanda Meira 1 , Gerard Dueñas 1 , Mariana Chumbita 1 , Nicole Garcia-Pouton 1 , Patricia Monzó1 , Carlos Lopera 1 , Laia Serra 1 , Celia Cardozo 1 , Marta Hernandez-Meneses 1 , Verónica Rico 1 , Marta Bodro 1 , Laura Morata 1 , Mariana Fernandez-Pittol 2 , Ignacio Grafia 1 , Pedro Castro 3 , Josep Mensa 1 , José Antonio Martínez 1 , Gemma Sanjuan 1 , M ª Angeles Marcos 2 , Alex Soriano 1 , Carolina Garcia-Vidal 1 , ∗, COVID-19-researcher group 1 Infectious Diseases Department, Hospital Clinic of Barcelona-IDIBAPS, Universitat de Barcelona, Barcelona, Spain 2 Microbiology Department, Hospital Clinic, University of Barcelona, ISGLOBAL, Barcelona, Spain 3 Medical Intensive Care Unit, Hospital Clinic, IDIBAPS, University of Barcelona, Barcelona, Spain a r t i c l e i n f o Article history: Received 1 December 2021 Revised 31 January 2022 Accepted 1 March 2022 Key words: COVID-19 bacterial infection co-infection antibiotics SARS-CoV-2 a b s t r a c t Objectives: We described the current incidence and risk factors of bacterial co-infection in hospitalized patients with COVID-19. Methods: Observational cohort study was performed at the Hospital Clinic of Barcelona (February 2020– February 2021). All patients with COVID-19 who were admitted for > 48 hours with microbiological sam- ple collection and procalcitonin (PCT) determination within the first 48 hours were included. Results: A total of 1125 consecutive adults met inclusion criteria. Co-infections were microbiologically documented in 102 (9.1%) patients. Most frequent microorganisms were Streptococcus pneumoniae (79%), Staphylococcus aureus (6.8%), and Haemophilus influenzae (6.8%). Test positivity was 1% (8/803) for blood cultures, 10.1% (79/780) for pneumococcal urinary antigen test, and 11.4% (15/132) for sputum culture. Patients with PCT higher than 0.2, 0.5, 1, and 2 ng/mL had significantly more co-infections than those with lower levels (p = 0.017, p = 0.031, p < 0.001, and p < 0.001, respectively). In multivariate analysis, oxygen saturation ≤94% (OR 2.47, CI 1.57–3.86), ferritin levels < 338 ng/mL (OR 2.63, CI 1.69–4.07), and PCT higher than 0.2 ng/mL (OR 1.74, CI 1.11–2.72) were independent risk factors for co-infection at hospital admission owing to COVID-19. Conclusions: Bacterial co-infection in patients hospitalized for COVID-19 is relatively common. However, clinicians could spare antibiotics in patients with PCT values < 0.2, especially with high ferritin values and oxygen saturation > 94%. © 2022 Published by Elsevier Ltd on behalf of International Society for Infectious Diseases. This is an open access article under the CC BY-NC-ND license ( http://creativecommons.org/licenses/by-nc-nd/4.0/ ) I f l n B 2 c t p h h m s t h 1 (NTRODUCTION On July 23 rd , 2021, more than 190 million people had been in- ected with SARS-CoV-2 worldwide, of whom more than 4.1 mil- ion died ( WHO Coronavirus [COVID-19] Dashboard | WHO Coro- avirus [COVID-19] Dashboard With Vaccination Data, n.d. ). Ap- ∗ Corresponding authors: Infectious Diseases Department, Hospital Clinic of arcelona. C/ Villarroel 170, 08036 Barcelona, Spain. Tel: ( + 34) 93-227-5400 (ext. 887). E-mail addresses: pedro.puerta84@gmail.com (P. Puerta-Alcalde), garciav@clinic.cat (C. Garcia-Vidal). # Authors Estela Moreno-Garcia, Pedro Puerta-Alcalde, and Laura Letona con- ributed equally to this manuscript. a i fi e t L ttps://doi.org/10.1016/j.ijid.2022.03.003 201-9712/© 2022 Published by Elsevier Ltd on behalf of International Society for Infectio http://creativecommons.org/licenses/by-nc-nd/4.0/ ) roximately 10% of patients with COVID-19 pneumonia will require ospital admission for different clinical complications, including yperinflammatory response, thrombotic events, organizing pneu- onia, or co-infections. These complications may have clinically imilar presentation, such as fever, dyspnea, and/or respiratory de- erioration. However, each will require a personalized therapeutic pproach ( Garcia-Vidal et al., 2020 ). A leading challenge for physicians treating COVID-19 is decid- ng when antibiotics are necessary at hospital admission. In the rst pandemic wave, most patients received antibiotics at dis- ase onset, although few reports described low incidence of bac- erial co-infections ( Adler et al., 2020 ; Garcia-Vidal et al., 2021b ; ehmann et al., 2021 ). A year after the start of the pandemic, us Diseases. This is an open access article under the CC BY-NC-ND license E. Moreno-García, P. Puerta-Alcalde, L. Letona et al. International Journal of Infectious Diseases 118 (2022) 197–202 t f l t i d a c i c P S C a p a t o ( h ( s d r b g f 2 s w i V e T o C d d t m B r v D l s t t r d ( c o D s a a g t s c M m t f c u t s g p D T t S a i e a w e t t c a t f U R D w p t o i p ( t s p p o f there are still unresolved questions with respect to both the use- ulness of procalcitonin (PCT) in ruling out co-infection or the se- ection of clinical phenotypes or analytical patterns to identify pa- ients at a higher risk of co-infection. Although some epidemiolog- cal changes have occurred through the different waves of the pan- emic ( Garcia-Vidal et al., 2021a ), recent data regarding incidence nd epidemiological characteristics of co-infections are lacking. For all of these reasons, we aimed to describe the current in- idence of co-infection in hospitalized patients with COVID-19 and dentify factors that may help clinicians initiate or discard empiri- al antibiotics correctly. ATIENTS AND METHODS tudy design and patients This observational cohort study was performed at the Hospital linic of Barcelona, a 700-bed university center that provides broad nd specialized medical, surgical, and intensive care for an urban opulation of 50 0,0 0 0 adults ( > 18 years old). We retrospectively nalyzed all consecutive adults hospitalized for SARS-CoV-2 infec- ion between 19 February 2020 and 24 February 2021 who met all f these criteria: (1) hospital admission for more than 48 hours, 2) microbiological samples collected within the first 48 hours at ospital admission, (3) serum creatinine lower than 2 mg/dL, and 4) at least 1 PCT determination within the first 48 hours of admis- ion. Patients with a positive urine culture were excluded owing to ifficulties in assessing the clinical relevance of urinary infections etrospectively. All patients had a confirmed diagnosis of COVID-19 y real-time PCR (RT-PCR) performed using nasal and oropharyn- eal throat-swab and/or by fulfillment of clinical diagnostic criteria or SARS-CoV-2 during the first peak of the pandemic (March–April 020). The suspected bacterial co-infection was defined on the ba- is of a positive microbiological sample, with clinical significance ithin the first 48 hours of admission. Our group previously published a work about bacterial co- nfections in the first year of SARS-CoV-2 pandemic ( Garcia- idal et al., 2021b ). In the current study, we focused on those pisodes in which active co-infection screening was performed. he primary outcome of this study was to determine the incidence f bacterial co-infection in this selected population of patients with OVID-19. Secondary outcomes were (i) to evaluate the yield of the ifferent microbiological tests, (ii) to evaluate the role of PCT at ifferent thresholds to identify patients with co-infection, and (iii) o identify independent risk factors for co-infection at hospital ad- ission. The Institutional Ethics Committee of the Hospital Clinic of arcelona approved the study, and owing to the nature of the ret- ospective data review, the need for informed consent from indi- idual patients was waived (HCB/2020/0273). ata collection and clinical assessment High-quality data on demographic characteristics, clinical signs, aboratory tests, microbiological results (blood cultures, respiratory amples, and urinary antigen tests), treatments, and outcomes (in- ensive care unit [ICU] admission, need for mechanical ventila- ion, and mortality) were collected directly from electronic health ecords (EHRs) using an intelligent system to retrieve high-quality ata from EHRs (SILDv1.0 system, S34M@), as described elsewhere Garcia-Vidal et al., 2019 ). All patients with positive microbiologi- al results were reviewed by 1 of our researchers (CGV, PPA, EMG, r LLG) for clinical significance assessments. 198 efinitions Clinical diagnostic criteria for SARS-CoV-2 included clinical ymptoms (fever, respiratory tract symptoms, myalgia, diarrhea, nd smell or taste aberrancies), laboratory findings (lymphopenia, s well as elevated levels of aminotransaminase, lactate dehydro- enase, inflammatory markers such as ferritin and C-reactive pro- ein, and D-dimer), and chest x-ray or computed tomography (CT) uggestive of COVID-19 with no other etiology that would explain linical presentation in its entirety. icrobiological methods We considered bacterial infections as significant when 1 or ore of the following criteria were met: (1) positive blood cul- ure with a noncontaminant bacteria, (2) positive cultures obtained rom good-quality sputum ( < 10 squamous cells and > 25 leuko- ytes per low-power field) and/or pleural fluids, and (3) positive rinary antigen test. In addition, Streptococcus pneumoniae urinary antigen was de- ected through a rapid immunochromatographic assay (NOW As- ay; Binax Inc, Portland, ME). STANDARDTM F for serogroup 1 Le- ionella pneumophila was performed in urine samples. Blood sam- les were processed using either a BACTEC 9240 system (Becton– ickinson Microbiology Systems, Franklin Lakes, NJ, USA) or Bac- Alert (BioMérieux SA, Marcy L’Etoile, France) for a 5-day incuba- ion period. tatistical analysis Categorical variables were described using the absolute number nd percentage, whereas continuous variables were presented us- ng the median and IQR. Categorical variables were compared using ither a chi-square ( χ ²) test or Fisher exact test when appropriate, nd medians with the Mann-Whitney U test. Statistical significance as defined as p < 0.05. Factors associated with co-infection were valuated by univariate and multivariate analysis, with the mul- ivariate analysis including all significant variables (p < 0.05) from he univariate analysis. Diagnostic accuracy of PCT was assessed by alculating sensitivity, specificity, negative predictive value (NPV), nd positive predictive value of different PCT cut-off values. A 2- ailed p < 0.05 was considered as significant. Analyses were per- ormed with Microsoft SPSS-PC + , version 22.0 (SPSS, Chicago, IL, SA). ESULTS escription of overall population and co-infection During the study period, we assessed 1125 consecutive adults ho met the inclusion criteria Figure 1 . shows the flowchart of atients’ inclusion. Epidemiological and clinical characteristics of hese patients are summarized in Table 1 . Attending physicians rdered microbiological test comprising 1 or more of the follow- ng: blood cultures in 803 patients, in whom 8 (1%) were positive; neumococcal urinary antigen tests in 780 patients, in whom 79 10.1%) were positive; Legionella urinary antigen tests in 776 pa- ients, all of which were negative; and cultures of good-quality putum in 132 patients, of whom 15 (11.4%) were positive. Co-infections were microbiologically documented in 102 (9.1%) atients, representing 3.2% of the whole cohort (including those atients not meeting the inclusion criteria). Co-infection epidemi- logy is detailed in Table 2 . The most frequent microorganisms ound were S. pneumoniae in 81 patients (representing 79% of pa- ients with co-infections and causing 7.2% of co-infections in the E. Moreno-García, P. Puerta-Alcalde, L. Letona et al. International Journal of Infectious Diseases 118 (2022) 197–202 Table 1 Main epidemiological and clinical characteristics of patients All patients (n = 1125) Patients without co-infection (n = 1023) Patients with co-infection (n = 122) p- value Patient characteristics Age-Median (IQR), in years 64 (54–75) 64 (54–75) 64.5 (54.8–76) 0.955 Male sex, n (%) 700 (62.2) 645 (63.1) 55 (53.9) 0.068 Comorbidities (%) Hypertension 480 (42.7) 442 (43.2) 38 (37.3) 0.247 Diabetes mellitus 198 (17.6) 179 (17.5) 19 (18.6) 0.775 Chronic heart disease 250 (22.2) 223 (21.8) 27 (26.5) 0.279 Chronic lung disease 281 (25) 248 (24.2) 33 (32.4) 0.071 Hematological malignancy 71 (6.3) 60 (5.9) 11 (8.8) 0.235 Chronic liver disease 86 (7.6) 77 (7.5) 9 (8.8) 0.638 Solid neoplasm 162 (14.4) 144 (14.1) 18 (14.7) 0.862 Vital signs at admission; Median (IQR) Temperature ( °C) 37.3 (36.6–38.0) 37.3 (36.6–38.0) 37.2 (36.4–37.8) 0.690 Respiratory rate (bpm) 20 (18–25) 20 (18–24) 22 (18–28) 0.423 Oxygen saturation (by pulseoximetry) 95 (93–97) 95 (93–97) 94 (92–96) 0.064 Laboratory values at admission; Median (IQR) Ferritin (ng/mL) 589 (269–1121.75) 602 (276–1134) 338 (202–1078) 0.055 C-RP (mg/dL) 8.9 (4.75–15.4) 9.0 (4.7–15.4) 9.9 (4.8–16.6) 0.597 D-dimer (ng/mL) 700 (400–1300) 700 (400–1300) 700 (400–1600) 0.233 LDH (U/L) 322 (257–409) 322 (257–405) 336 (241–438) 0.827 Lymphocyte count (cells/mm 3 ) 0.8 (0.6–1.1) 0.8 (0.6–1.1) 0.8 (0.5–1.2) 0.927 PCT (ng/mL) 0.11 (0.6–0.23) 0.11 (0.06–0.22) 0.12 (0.06–0.34) 0.534 Abbreviations: bpm, breaths per minute; CRP, C-reactive protein; LDH, lactate dehydrogenase; PCT, procalcitonin. Table 2 Epidemiology of bacterial co-infections at COVID-19 admission. n = 102 (%) Respiratory co-infection diagnosed by pneumococcal urinary antigen 79 Respiratory co-infection diagnosed by sputum culture 15 a S. pneumoniae 4 b P. aeruginosa 2 S. aureus 5 K. pneumoniae 1 H. influenzae 6 Bacteremia 8 E. coli 3 S. aureus 3 P. aeruginosa 1 H. influenzae 1 a Three patients had a positive polymicrobial sputum culture. b In three of the four patients with positive S. pneumoniae in the sputum culture, pneumococcal urinary antigen was not performed. In the other patient, urinary antigen was negative. o H R i 0 P w 0 d c a s ( t o d P s v p 3 o d t n v f T tverall cohort), Staphylococcus aureus in 7 patients (6.8%; 0.6%), and aemophilus influenzae in 7 patients (6.8%; 0.6%). elationship between PCT levels and co-infection Median PCT levels were similar between patients with co- nfection and those without co-infection (0.12 ng/mL; IQR 0.06– .34 vs 0.11 ng/mL, IQR 0.06–0.22; p = 0.534). Specifically, median CT was higher in patients with bacteremia compared with those ithout bacteremia (0.48 ng/mL, IQR 0.27–36.7 vs 0.11 ng/mL, IQR .06–0.23; p = 0.019). No significant differences were found in me- ian PCT values between patients with either positive pneumococ- al urinary antigen or positive sputum culture and those with neg- tive results. Patients with PCT higher than 0.2, 0.5, 1, and 2 ng/mL had ignificantly more co-infections than those with lower levels p = 0.017, p = 0.031, p < 0.001, and p < 0.001, respectively) Table 3 . de- ails the sensitivity, specificity, NPV, and positive predictive value 199 f PCT cut-off values of 0.2, 0.5, 1, and 2 ng/mL for co-infection etection. redictors of COVID-19 co-infection In the univariate analysis, patients with co-infection at on- et presented with (i) a higher respiratory rate (20 rpm median alue vs 22; p = 0.05), (ii) a lower oxygen saturation (95% vs 94%; = 0.012), iii) decreased ferritin levels (602 ng/mL median value vs 38 ng/mL; p = 0.012), and iv) PCT higher than the cut-off value f 0.2 ng/mL (18.6% vs 11.3%; p = 0.031). No other differences were ocumented compared with patients without co-infection. In the multivariate analysis, oxygen saturation equal or lower han 94% (OR 2.47, CI 1.57–3.86), ferritin levels lower than 338 g/mL (OR 2.63, CI 1.69-4.07), and PCT higher than the cut-off alue of 0.2 ng/mL (OR 1.74, CI 1.11-2.72) were independent risk actors for co-infection at hospital admission owing to COVID-19. he goodness-of-fit of the multivariate model was assessed using he Hosmer-Lemeshow test (0.387). The discriminatory power of E. Moreno-García, P. Puerta-Alcalde, L. Letona et al. International Journal of Infectious Diseases 118 (2022) 197–202 Table 3 Sensitivity, specificity, predictive negative value, and predictive positive value of different PCT cut-offs for co-infection detection. PCT ≥0.20 ng/ml PCT ≥0.50 ng/ml PCT ≥1 ng/ml PCT ≥2 ng/ml Sensitivity 0.40 0.19 0.14 0.14 Specificity 0.71 0.89 0.95 0.97 Negative predictive value 0.92 0.92 0.92 0.92 Positive predictive value 0.12 0.14 0.21 0.34 Abbreviations: PCT, procalcitonin. Figure 1. Flowchart of patients’ inclusion. t c i D w t t 9 c c p V p n o d a t f m a c p o p t f t t a p t p m c c n c f i c t p c c p I m s t o p 2 s l 2 s m f c i r t C n c q 2 c h n O t n i the score, as evaluated by the area under the receiver operating haracteristic curve, was 0.677 (95% CI, 0.619–0.734), demonstrat- ng a moderate ability to predict co-infection. ISCUSSION The results obtained from of our study show that co-infection as relatively frequent (approximately 10%) in hospitalized pa- ients with COVID-19 during the first year of pandemic. We iden- ify that those patients with oxygen saturation equal or lower than 4% who had lower ferritin levels and had PCT higher than the ut-off value of 0.2 ng/mL had more frequent co-infection. The PCT ut-off value of 0.2 ng/mL has a high NPV to rule out co-infection. Previous studies reported lower incidence of co-infection in this opulation, ranging between 2% and 6% ( Adler et al., 2020 ; Garcia- idal et al., 2021b ; Lehmann et al., 2021 ). However, some im- ortant methodological differences among the studies should be oted. In contrast with these previous studies, the current study nly includes patients for whom microbiological tests had been or- ered to rule out this complication. Moreover, this study describes series of patients admitted to the hospital for COVID-19 during he first full year of the pandemic. This aspect of the study differs rom other studies, which included patients from only the first few onths. This point may be important for different reasons. For ex- mple, we may have improved the diagnostic approaches used for o-infection detection over the months. In addition, a change in atient characteristics over time could have an impact on the risk f co-infection. Some researchers warned of a potential increase in 200 neumococcal colonization among adults as a result of close con- act with children ( Almeida et al., 2021 ). It would be logical, there- ore, to believe that following at-home confinements, contact be- ween adults and children may have been especially close, poten- ially increasing pneumococcal colonization in seniors. Our study documented that both the pneumococcal urinary ntigen test and the sputum culture comprise 2 of the most im- ortant tests when it comes to ruling out co-infections in pa- ients with COVID-19 at hospital admission. Both techniques may rovide quick-time results and contribute to improved decision- aking processes regarding antibiotic use among treating physi- ians. Although our study recorded very infrequent use of sputum ulture, when performed, it was able to diagnose 11% of patients onetheless. Currently, S. aureus and H. influenzae co-infections annot be diagnosed by other microbiological techniques. There- ore, the incidence of such co-infections could be underestimated n most cohorts of patients with COVID-19. We recommend in- reasing the use of Gram staining and sputum culture in all pa- ients with productive sputum arriving to the hospital, which could rovide valuable, insightful information within a few minutes. In ontrast, as has been done in bacterial pneumonia management, linicians could consider not performing blood cultures, at least in atients with a PCT lower than 0.5 ng/ml ( Falguera et al., 2009 ). n our view, owing to low frequency of the pathogen, it does not ake sense to perform Legionella urinary antigen routinely at on- et. The role of PCT in ruling out co-infections in patients hospi- alized with COVID-19 remains a controversial topic. Some previ- us studies analyzing this issue included a very low number of atients and had several methodological limitations ( Heer et al., 021 ; Malinverni et al., 2021 ; Pink et al., 2021 ). May et al. retro- pectively analyzed the role of PCT in diagnosing co-infection in a arger cohort of 2443 patients admitted with COVID-19 ( May et al., 021 ). However, there are important differences between their tudy and ours. First, May et al. included patients in whom no icrobiological tests had been performed to rule out bacterial in- ections as patients without co-infection. Second, they also in- luded patients with positive urine cultures as patients with co- nfection. In our view, it is difficult to retrospectively assess the elevance of clinical infection in patients with positive urine cul- ures. It is even more challenging to associate urine infections with OVID-19. Finally, the authors do not report the incidence of re- al failure in the study cohort. In our experience, renal insuffi- iency was associated with difficult-to-assess PCT values; conse- uently, we excluded these patients from our work ( El-sayed et al., 014 ; Grace and Turner, 2014 ). Despite of all these methodologi- al differences, those authors and we similarly conclude that PCT as limited use in diagnosing bacterial co-infections. Importantly, onetheless, PCT may play a role in ruling out this complication. ther authors have described that withholding antibiotics in pa- ients with COVID-19 and a PCT cut-off value lower than 0.25 g/ml may prove to be safe ( Williams et al., 2021 ). In our study, we more frequently identified bacterial co- nfections among patients with oxygen saturation equal or lower han 94%, ferritin levels lower that 338 ng/mL, and PCT higher than E. Moreno-García, P. Puerta-Alcalde, L. Letona et al. International Journal of Infectious Diseases 118 (2022) 197–202 a v t i m e t f o o i l a t t n H t g a s c e o C a p h c t c a r F h t T f o t s N g S i i i I U D e G h a o J D f c A I r B M l S T M a t A t J O c J v J s m a R A A E F G G G G G H L M cut-off value of 0.2 ng/mL. The relationship between low ferritin alues and bacterial co-infection may be attributable to the fact hat patients with COVID-19 with high ferritin levels have hyper- nflammatory syndrome more frequently as a cause of hospital ad- ission. Our study does have some limitations that should be acknowl- dged. First, not all patients had sputum culture, urinary antigen est, and blood cultures performed at hospital admission. There- ore, underdiagnosis of some co-infections may have occurred. Sec- nd, hospital’s protocol regarding patient care and COVID-19 rec- mmends that clinicians order microbiological tests to rule out co- nfection and measure PCT at hospital admission. However, our se- ection of patients, for whom these tests were ordered, may then lso bias the frequency of co-infections. In addition, we decided o exclude urinary cultures because these are commonly difficult o evaluate in otherwise asymptomatic patients and because uri- ary tract co-infection is not expected in patients with pneumonia. owever, this introduced another bias and could have influenced he final study result. Finally, as this study was conducted at a sin- le center, frequency and microbiological epidemiology may vary ccording to different geographical contexts. The strengths of this tudy include the large number of cohort subjects and the clear, omplete collection of clinical and microbiological data for optimal valuation of factors related with co-infection, especially the role f PCT in ruling out this complication. To conclude, bacterial co-infection is a relatively common OVID-19 complication that is diagnosed in 10% of hospitalized dults. Our results suggest that avoiding the use of antibiotics in atients with COVID-19 and PCT values below 0.2, especially with igh ferritin values and oxygen saturation greater than 94%, may onstitute a wise approach as it relates to making decisions related o antibiotic use at admission. Clinicians should perform pneumo- occal urinary antigen test, Gram staining, and sputum cultures in ll patients when possible. The need for antibiotics should then be e-evaluated within the first 24 hours of these results. unding This work has been financed by funds for research ad- oc COVID-19 from citizens and organizations patronage to Hospi- al Clínic de Barcelona-Fundació Clínic per a la Recerca Biomèdica. his research forms part of an activity that has received funding rom EIT Health. EIT Health is supported by the European Institute f Innovation and Technology (EIT), a body of the European Union hat receives support from the European Union’s Horizon 2020 Re- earch and Innovation Program. PP-A [JR20/0 0 012 and PI21/0 0498], G-P [FI19/00133], and CG-V [PI21/01640] have received research rants from the Ministerio de Sanidad y Consumo, Instituto de alud Carlos III. MSD provided financial support for medical writ- ng assistance of this paper. The funders had neither a specific role n study design, in collection of data, in writing of the paper, nor n the decision to submit. Project PI21/01640 has been funded by nstituto de Salud Carlos III (ISCIII) and co-funded by the European nion. eclaration of Competing Interest CG-V has received honoraria for talks on behalf of Gilead Sci- nce, MSD, Novartis, Pfizer, Janssen, Lilly, as well as a grant from ilead Science and MSD. AS has received honoraria for talks on be- alf of Merck Sharp and Dohme, Pfizer, Novartis, Angellini, as well s grant support from Pfizer. PC has received honoraria for talks n behalf of Merck Sharp and Dohme, Pfizer, Gilead, and Alexion. M has received honoraria for talks on behalf of Merck Sharp and ohme, Pfizer, Novartis, and Angellini. PP-A has received honoraria 201 or talks on behalf of Merck Sharp and Dohme, Lilly, ViiV Health- are, and Gilead Science. cknowledgments Hospital Clinic of Barcelona COVID-19 Research Group: nfectious Diseases’ Research Group: Daiana Agüero, Sabina Her- era, Rodrigo Alonso, Ana Camón, Juan Ambrosioni, Jose Luis lanco, Josep Mallolas, Alexy Inciarte, Esteban Martínez, María artínez, Jose María Miró, Montse Solà, Ainhoa Ugarte, Lorena de a Mora, and all the staff members. Medical Intensive Care Unit: Fernando Fuentes, Adrian Téllez, ara Fernández, and all the staff members. Department of International Health: Daniel Camprubi, Maria eresa de Alba, Marc Fernandez, Elisabet Ferrer, Berta Grau, Helena arti, Maria Jesus Pinazo, Natalia Rodríguez, Montserrat Roldan, Is- bel Vera, Nana Williams, Alex Almuedo-Riera, Jose Muñoz, and all he staff members. Department of Internal Medicine: Miquel Camafort, Julia Calvo, ina Capdevila, Francesc Cardellach, Emmanuel Coloma, Ramon Es- ruch, Joaquim Fernández-Solá, Alfons López-Soto, Ferran Masanés, ose Milisenda, Pedro Moreno, Jose Naval, David Nicolás, Omar beroi, Sergio Prieto-González, Olga Rodríguez-Núnez, Emili Se- anella, Cristina Sierra, and all the staff members. Department of Microbiology: Manel Almela, Míriam Alvarez, ordi Bosch, Josep Costa, Julià Gonzàlez, Francesc Marco, Sofia Nar- aez, Cristina Pitart, Elisa Rubio, Andrea Vergara, M ª Eugenia Valls, ordi Vila, and all the staff members. Department of Farmacy: Esther López, Montse Tuset, and all the taff members. Other acknowledgments: We would like to thank Anthony Ar- enta for providing medical editing assistance for the manuscript t hand. eferences dler H, Ball R, Fisher M, Mortimer K, Vardhan MS. Low rate of bacterial co-infection in patients with COVID-19. 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