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Research Article| Volume 118, P197-202, May 2022

Bacterial co-infection at hospital admission in patients with COVID-19

Open AccessPublished:March 04, 2022DOI:https://doi.org/10.1016/j.ijid.2022.03.003

      Highlights

      • Over 9% of patients hospitalized for COVID-19 will present a co-infection.
      • Independent risk factors for co-infection were identified.
      • When procalcitonin values are <0.2 ng/mL, co-infection is very rare.
      • High ferritin values and oxygen saturation >94% are also uncommon in co-infection.

      ABSTRACT

      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 sample 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%.

      Key words

      INTRODUCTION

      On July 23rd, 2021, more than 190 million people had been infected with SARS-CoV-2 worldwide, of whom more than 4.1 million died (

      WHO Coronavirus (COVID-19) Dashboard | WHO Coronavirus (COVID-19) Dashboard With Vaccination Data. n.d. https://covid19.who.int /(accessed July 28, 2021).

      ). Approximately 10% of patients with COVID-19 pneumonia will require hospital admission for different clinical complications, including hyperinflammatory response, thrombotic events, organizing pneumonia, or co-infections. These complications may have clinically similar presentation, such as fever, dyspnea, and/or respiratory deterioration. However, each will require a personalized therapeutic approach (
      • Garcia-Vidal C
      • Moreno-García E
      • Hernández-Meneses M
      • Puerta-Alcalde P
      • Chumbita M
      • Garcia-Pouton N
      • et al.
      Personalized therapy approach for hospitalized patients with COVID-19.
      ).
      A leading challenge for physicians treating COVID-19 is deciding when antibiotics are necessary at hospital admission. In the first pandemic wave, most patients received antibiotics at disease onset, although few reports described low incidence of bacterial co-infections (
      • Adler H
      • Ball R
      • Fisher M
      • Mortimer K
      • Vardhan MS.
      Low rate of bacterial co-infection in patients with COVID-19.
      ;
      • Garcia-Vidal C
      • Sanjuan G
      • Moreno-García E
      • Puerta-Alcalde P
      • Garcia-Pouton N
      • Chumbita M
      • et al.
      Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a retrospective cohort study.
      ;
      • Lehmann CJ
      • Pho MT
      • Pitrak D
      • Ridgway JP
      • Pettit NN.
      Community-acquired Coinfection in Coronavirus Disease 2019: A Retrospective Observational Experience.
      ). A year after the start of the pandemic, there are still unresolved questions with respect to both the usefulness of procalcitonin (PCT) in ruling out co-infection or the selection of clinical phenotypes or analytical patterns to identify patients at a higher risk of co-infection. Although some epidemiological changes have occurred through the different waves of the pandemic (
      • Garcia-Vidal C
      • Cózar-Llistó A
      • Meira F
      • Dueñas G
      • Puerta-Alcalde P
      • Cilloniz C
      • et al.
      Trends in mortality of hospitalised COVID-19 patients: A single centre observational cohort study from Spain.
      ), recent data regarding incidence and epidemiological characteristics of co-infections are lacking.
      For all of these reasons, we aimed to describe the current incidence of co-infection in hospitalized patients with COVID-19 and identify factors that may help clinicians initiate or discard empirical antibiotics correctly.

      PATIENTS AND METHODS

      Study design and patients

      This observational cohort study was performed at the Hospital Clinic of Barcelona, a 700-bed university center that provides broad and specialized medical, surgical, and intensive care for an urban population of 500,000 adults (>18 years old). We retrospectively analyzed all consecutive adults hospitalized for SARS-CoV-2 infection between 19 February 2020 and 24 February 2021 who met all of these criteria: (1) hospital admission for more than 48 hours, (2) microbiological samples collected within the first 48 hours at hospital admission, (3) serum creatinine lower than 2 mg/dL, and (4) at least 1 PCT determination within the first 48 hours of admission. Patients with a positive urine culture were excluded owing to difficulties in assessing the clinical relevance of urinary infections retrospectively. All patients had a confirmed diagnosis of COVID-19 by real-time PCR (RT-PCR) performed using nasal and oropharyngeal throat-swab and/or by fulfillment of clinical diagnostic criteria for SARS-CoV-2 during the first peak of the pandemic (March–April 2020). The suspected bacterial co-infection was defined on the basis of a positive microbiological sample, with clinical significance within the first 48 hours of admission.
      Our group previously published a work about bacterial co-infections in the first year of SARS-CoV-2 pandemic (
      • Garcia-Vidal C
      • Sanjuan G
      • Moreno-García E
      • Puerta-Alcalde P
      • Garcia-Pouton N
      • Chumbita M
      • et al.
      Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a retrospective cohort study.
      ). In the current study, we focused on those episodes in which active co-infection screening was performed. The primary outcome of this study was to determine the incidence of bacterial co-infection in this selected population of patients with COVID-19. Secondary outcomes were (i) to evaluate the yield of the different microbiological tests, (ii) to evaluate the role of PCT at different thresholds to identify patients with co-infection, and (iii) to identify independent risk factors for co-infection at hospital admission.
      The Institutional Ethics Committee of the Hospital Clinic of Barcelona approved the study, and owing to the nature of the retrospective data review, the need for informed consent from individual patients was waived (HCB/2020/0273).

      Data collection and clinical assessment

      High-quality data on demographic characteristics, clinical signs, laboratory tests, microbiological results (blood cultures, respiratory samples, and urinary antigen tests), treatments, and outcomes (intensive care unit [ICU] admission, need for mechanical ventilation, and mortality) were collected directly from electronic health records (EHRs) using an intelligent system to retrieve high-quality data from EHRs (SILDv1.0 system, [email protected]), as described elsewhere (
      • Garcia-Vidal C
      • Sanjuan G
      • Puerta-Alcalde P
      • Moreno-García E
      • Soriano A.
      Artificial intelligence to support clinical decision-making processes.
      ). All patients with positive microbiological results were reviewed by 1 of our researchers (CGV, PPA, EMG, or LLG) for clinical significance assessments.

      Definitions

      Clinical diagnostic criteria for SARS-CoV-2 included clinical symptoms (fever, respiratory tract symptoms, myalgia, diarrhea, and smell or taste aberrancies), laboratory findings (lymphopenia, as well as elevated levels of aminotransaminase, lactate dehydrogenase, inflammatory markers such as ferritin and C-reactive protein, and D-dimer), and chest x-ray or computed tomography (CT) suggestive of COVID-19 with no other etiology that would explain clinical presentation in its entirety.

      Microbiological methods

      We considered bacterial infections as significant when 1 or more of the following criteria were met: (1) positive blood culture with a noncontaminant bacteria, (2) positive cultures obtained from good-quality sputum (<10 squamous cells and >25 leukocytes per low-power field) and/or pleural fluids, and (3) positive urinary antigen test.
      In addition, Streptococcus pneumoniae urinary antigen was detected through a rapid immunochromatographic assay (NOW Assay; Binax Inc, Portland, ME). STANDARDTM F for serogroup 1 Legionella pneumophila was performed in urine samples. Blood samples were processed using either a BACTEC 9240 system (Becton–Dickinson Microbiology Systems, Franklin Lakes, NJ, USA) or BacTAlert (BioMérieux SA, Marcy L'Etoile, France) for a 5-day incubation period.

      Statistical analysis

      Categorical variables were described using the absolute number and percentage, whereas continuous variables were presented using the median and IQR. Categorical variables were compared using either a chi-square (χ²) test or Fisher exact test when appropriate, and medians with the Mann-Whitney U test. Statistical significance was defined as p<0.05. Factors associated with co-infection were evaluated by univariate and multivariate analysis, with the multivariate analysis including all significant variables (p<0.05) from the univariate analysis. Diagnostic accuracy of PCT was assessed by calculating sensitivity, specificity, negative predictive value (NPV), and positive predictive value of different PCT cut-off values. A 2-tailed p<0.05 was considered as significant. Analyses were performed with Microsoft SPSS-PC+, version 22.0 (SPSS, Chicago, IL, USA).

      RESULTS

      Description of overall population and co-infection

      During the study period, we assessed 1125 consecutive adults who met the inclusion criteria Figure 1. shows the flowchart of patients’ inclusion. Epidemiological and clinical characteristics of these patients are summarized in Table 1. Attending physicians ordered microbiological test comprising 1 or more of the following: blood cultures in 803 patients, in whom 8 (1%) were positive; pneumococcal urinary antigen tests in 780 patients, in whom 79 (10.1%) were positive; Legionella urinary antigen tests in 776 patients, all of which were negative; and cultures of good-quality sputum in 132 patients, of whom 15 (11.4%) were positive.
      Table 1Main 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 years64 (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 (%)
       Hypertension480 (42.7)442 (43.2)38 (37.3)0.247
       Diabetes mellitus198 (17.6)179 (17.5)19 (18.6)0.775
       Chronic heart disease250 (22.2)223 (21.8)27 (26.5)0.279
       Chronic lung disease281 (25)248 (24.2)33 (32.4)0.071
       Hematological malignancy71 (6.3)60 (5.9)11 (8.8)0.235
       Chronic liver disease86 (7.6)77 (7.5)9 (8.8)0.638
       Solid neoplasm162 (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/mm3)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.
      Co-infections were microbiologically documented in 102 (9.1%) patients, representing 3.2% of the whole cohort (including those patients not meeting the inclusion criteria). Co-infection epidemiology is detailed in Table 2. The most frequent microorganisms found were S. pneumoniae in 81 patients (representing 79% of patients with co-infections and causing 7.2% of co-infections in the overall cohort), Staphylococcus aureus in 7 patients (6.8%; 0.6%), and Haemophilus influenzae in 7 patients (6.8%; 0.6%).
      Table 2Epidemiology of bacterial co-infections at COVID-19 admission.
      n=102 (%)
      Respiratory co-infection diagnosed by pneumococcal urinary antigen79
      Respiratory co-infection diagnosed by sputum culture15
      Three patients had a positive polymicrobial sputum culture.
      S. pneumoniae4
      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.
      P. aeruginosa2
      S. aureus5
      K. pneumoniae1
      H. influenzae6
      Bacteremia8
      E. coli3
      S. aureus3
      P. aeruginosa1
      H. influenzae1
      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.

      Relationship between PCT levels and co-infection

      Median PCT levels were similar between patients with co-infection and those without co-infection (0.12 ng/mL; IQR 0.06–0.34 vs 0.11 ng/mL, IQR 0.06–0.22; p=0.534). Specifically, median PCT was higher in patients with bacteremia compared with those without bacteremia (0.48 ng/mL, IQR 0.27–36.7 vs 0.11 ng/mL, IQR 0.06–0.23; p=0.019). No significant differences were found in median PCT values between patients with either positive pneumococcal urinary antigen or positive sputum culture and those with negative results.
      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) Table 3. details the sensitivity, specificity, NPV, and positive predictive value of PCT cut-off values of 0.2, 0.5, 1, and 2 ng/mL for co-infection detection.
      Table 3Sensitivity, specificity, predictive negative value, and predictive positive value of different PCT cut-offs for co-infection detection.
      PCT ≥0.20 ng/mlPCT ≥0.50 ng/mlPCT ≥1 ng/mlPCT ≥2 ng/ml
      Sensitivity0.400.190.140.14
      Specificity0.710.890.950.97
      Negative predictive value0.920.920.920.92
      Positive predictive value0.120.140.210.34
      Abbreviations: PCT, procalcitonin.

      Predictors of COVID-19 co-infection

      In the univariate analysis, patients with co-infection at onset presented with (i) a higher respiratory rate (20 rpm median value vs 22; p=0.05), (ii) a lower oxygen saturation (95% vs 94%; p=0.012), iii) decreased ferritin levels (602 ng/mL median value vs 338 ng/mL; p=0.012), and iv) PCT higher than the cut-off value of 0.2 ng/mL (18.6% vs 11.3%; p=0.031). No other differences were documented compared with patients without co-infection.
      In the multivariate analysis, oxygen saturation equal or lower than 94% (OR 2.47, CI 1.57–3.86), ferritin levels lower than 338 ng/mL (OR 2.63, CI 1.69-4.07), and PCT higher than the cut-off value of 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. The goodness-of-fit of the multivariate model was assessed using the Hosmer-Lemeshow test (0.387). The discriminatory power of the score, as evaluated by the area under the receiver operating characteristic curve, was 0.677 (95% CI, 0.619–0.734), demonstrating a moderate ability to predict co-infection.

      DISCUSSION

      The results obtained from of our study show that co-infection was relatively frequent (approximately 10%) in hospitalized patients with COVID-19 during the first year of pandemic. We identify that those patients with oxygen saturation equal or lower than 94% who had lower ferritin levels and had PCT higher than the cut-off value of 0.2 ng/mL had more frequent co-infection. The PCT cut-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 population, ranging between 2% and 6% (
      • Adler H
      • Ball R
      • Fisher M
      • Mortimer K
      • Vardhan MS.
      Low rate of bacterial co-infection in patients with COVID-19.
      ;
      • Garcia-Vidal C
      • Sanjuan G
      • Moreno-García E
      • Puerta-Alcalde P
      • Garcia-Pouton N
      • Chumbita M
      • et al.
      Incidence of co-infections and superinfections in hospitalized patients with COVID-19: a retrospective cohort study.
      ;
      • Lehmann CJ
      • Pho MT
      • Pitrak D
      • Ridgway JP
      • Pettit NN.
      Community-acquired Coinfection in Coronavirus Disease 2019: A Retrospective Observational Experience.
      ). However, some important methodological differences among the studies should be noted. In contrast with these previous studies, the current study only includes patients for whom microbiological tests had been ordered to rule out this complication. Moreover, this study describes a series of patients admitted to the hospital for COVID-19 during the first full year of the pandemic. This aspect of the study differs from other studies, which included patients from only the first few months. This point may be important for different reasons. For example, we may have improved the diagnostic approaches used for co-infection detection over the months. In addition, a change in patient characteristics over time could have an impact on the risk of co-infection. Some researchers warned of a potential increase in pneumococcal colonization among adults as a result of close contact with children (
      • Almeida ST
      • Paulo AC
      • Froes F
      • de Lencastre H
      • Sá-Leão R.
      Dynamics of Pneumococcal Carriage in Adults: A New Look at an Old Paradigm.
      ). It would be logical, therefore, to believe that following at-home confinements, contact between adults and children may have been especially close, potentially increasing pneumococcal colonization in seniors.
      Our study documented that both the pneumococcal urinary antigen test and the sputum culture comprise 2 of the most important tests when it comes to ruling out co-infections in patients with COVID-19 at hospital admission. Both techniques may provide quick-time results and contribute to improved decision-making processes regarding antibiotic use among treating physicians. Although our study recorded very infrequent use of sputum culture, when performed, it was able to diagnose 11% of patients nonetheless. Currently, S. aureus and H. influenzae co-infections cannot be diagnosed by other microbiological techniques. Therefore, the incidence of such co-infections could be underestimated in most cohorts of patients with COVID-19. We recommend increasing the use of Gram staining and sputum culture in all patients with productive sputum arriving to the hospital, which could provide valuable, insightful information within a few minutes. In contrast, as has been done in bacterial pneumonia management, clinicians could consider not performing blood cultures, at least in patients with a PCT lower than 0.5 ng/ml (
      • Falguera M
      • Trujillano J
      • Caro S
      • Menéndez R
      • Carratalà J
      • Ruiz-González A
      • et al.
      A prediction rule for estimating the risk of bacteremia in patients with community-acquired pneumonia.
      ). In our view, owing to low frequency of the pathogen, it does not make sense to perform Legionella urinary antigen routinely at onset.
      The role of PCT in ruling out co-infections in patients hospitalized with COVID-19 remains a controversial topic. Some previous studies analyzing this issue included a very low number of patients and had several methodological limitations (

      Heer RS, Mandal AK, Kho J, Szawarski P, Csabi P, Grenshaw D, et al. Elevated procalcitonin concentrations in severe Covid-19 may not reflect bacterial co-infection: Https://DoiOrg/101177/00045632211022380 2021:000456322110223. https://doi.org/10.1177/00045632211022380.

      ;
      • Malinverni S
      • Nuñez M
      • Cotton F
      • Martiny D
      • Collot V
      • Konopnicki D
      • et al.
      Is procalcitonin a reliable marker of bacterial community-acquired pneumonia in adults admitted to the emergency department during SARS-CoV-2 pandemic?.
      ;
      • Pink I
      • Raupach D
      • Fuge J
      • Vonberg R-P
      • Hoeper MM
      • Welte T
      • et al.
      C-reactive protein and procalcitonin for antimicrobial stewardship in COVID-19.
      ). May et al. retrospectively analyzed the role of PCT in diagnosing co-infection in a larger cohort of 2443 patients admitted with COVID-19 (
      • May M
      • Chang M
      • Dietz D
      • Shoucri S
      • Laracy J
      • Sobieszczyk ME
      • et al.
      Limited utility of procalcitonin in identifying community-associated bacterial infections in patients presenting with coronavirus disease 2019.
      ). However, there are important differences between their study and ours. First, May et al. included patients in whom no microbiological tests had been performed to rule out bacterial infections as patients without co-infection. Second, they also included patients with positive urine cultures as patients with co-infection. In our view, it is difficult to retrospectively assess the relevance of clinical infection in patients with positive urine cultures. It is even more challenging to associate urine infections with COVID-19. Finally, the authors do not report the incidence of renal failure in the study cohort. In our experience, renal insufficiency was associated with difficult-to-assess PCT values; consequently, we excluded these patients from our work (
      • El-sayed D
      • Grotts J
      • Golgert WA
      • Sugar AM.
      Sensitivity and specificity of procalcitonin in predicting bacterial infections in patients with renal impairment.
      ;
      • Grace E
      • Turner RM.
      Use of procalcitonin in patients with various degrees of chronic kidney disease including renal replacement therapy.
      ). Despite of all these methodological differences, those authors and we similarly conclude that PCT has limited use in diagnosing bacterial co-infections. Importantly, nonetheless, PCT may play a role in ruling out this complication. Other authors have described that withholding antibiotics in patients with COVID-19 and a PCT cut-off value lower than 0.25 ng/ml may prove to be safe (
      • Williams EJ
      • Mair L
      • Silva TI de
      • Green DJ
      • House P
      • Cawthron K
      • et al.
      Evaluation of procalcitonin as a contribution to antimicrobial stewardship in SARS-CoV-2 infection: a retrospective cohort study.
      ).
      In our study, we more frequently identified bacterial co-infections among patients with oxygen saturation equal or lower than 94%, ferritin levels lower that 338 ng/mL, and PCT higher than a cut-off value of 0.2 ng/mL. The relationship between low ferritin values and bacterial co-infection may be attributable to the fact that patients with COVID-19 with high ferritin levels have hyperinflammatory syndrome more frequently as a cause of hospital admission.
      Our study does have some limitations that should be acknowledged. First, not all patients had sputum culture, urinary antigen test, and blood cultures performed at hospital admission. Therefore, underdiagnosis of some co-infections may have occurred. Second, hospital's protocol regarding patient care and COVID-19 recommends that clinicians order microbiological tests to rule out co-infection and measure PCT at hospital admission. However, our selection of patients, for whom these tests were ordered, may then also bias the frequency of co-infections. In addition, we decided to exclude urinary cultures because these are commonly difficult to evaluate in otherwise asymptomatic patients and because urinary tract co-infection is not expected in patients with pneumonia. However, this introduced another bias and could have influenced the final study result. Finally, as this study was conducted at a single center, frequency and microbiological epidemiology may vary according to different geographical contexts. The strengths of this study include the large number of cohort subjects and the clear, complete collection of clinical and microbiological data for optimal evaluation of factors related with co-infection, especially the role of PCT in ruling out this complication.
      To conclude, bacterial co-infection is a relatively common COVID-19 complication that is diagnosed in 10% of hospitalized adults. Our results suggest that avoiding the use of antibiotics in patients with COVID-19 and PCT values below 0.2, especially with high ferritin values and oxygen saturation greater than 94%, may constitute a wise approach as it relates to making decisions related to antibiotic use at admission. Clinicians should perform pneumococcal urinary antigen test, Gram staining, and sputum cultures in all patients when possible. The need for antibiotics should then be re-evaluated within the first 24 hours of these results.

      Funding

      This work has been financed by funds for research adhoc COVID-19 from citizens and organizations patronage to Hospital Clínic de Barcelona-Fundació Clínic per a la Recerca Biomèdica. This research forms part of an activity that has received funding from EIT Health. EIT Health is supported by the European Institute of Innovation and Technology (EIT), a body of the European Union that receives support from the European Union's Horizon 2020 Research and Innovation Program. PP-A [JR20/00012 and PI21/00498], NG-P [FI19/00133], and CG-V [PI21/01640] have received research grants from the Ministerio de Sanidad y Consumo, Instituto de Salud Carlos III. MSD provided financial support for medical writing assistance of this paper. The funders had neither a specific role in study design, in collection of data, in writing of the paper, nor in the decision to submit. Project PI21/01640 has been funded by Instituto de Salud Carlos III (ISCIII) and co-funded by the European Union.

      Declaration of Competing Interest

      CG-V has received honoraria for talks on behalf of Gilead Science, MSD, Novartis, Pfizer, Janssen, Lilly, as well as a grant from Gilead Science and MSD. AS has received honoraria for talks on behalf of Merck Sharp and Dohme, Pfizer, Novartis, Angellini, as well as grant support from Pfizer. PC has received honoraria for talks on behalf of Merck Sharp and Dohme, Pfizer, Gilead, and Alexion. JM has received honoraria for talks on behalf of Merck Sharp and Dohme, Pfizer, Novartis, and Angellini. PP-A has received honoraria for talks on behalf of Merck Sharp and Dohme, Lilly, ViiV Healthcare, and Gilead Science.

      Acknowledgments

      Hospital Clinic of Barcelona COVID-19 Research Group: Infectious Diseases’ Research Group: Daiana Agüero, Sabina Herrera, Rodrigo Alonso, Ana Camón, Juan Ambrosioni, Jose Luis Blanco, Josep Mallolas, Alexy Inciarte, Esteban Martínez, María Martínez, Jose María Miró, Montse Solà, Ainhoa Ugarte, Lorena de la Mora, and all the staff members.
      Medical Intensive Care Unit: Fernando Fuentes, Adrian Téllez, Sara Fernández, and all the staff members.
      Department of International Health: Daniel Camprubi, Maria Teresa de Alba, Marc Fernandez, Elisabet Ferrer, Berta Grau, Helena Marti, Maria Jesus Pinazo, Natalia Rodríguez, Montserrat Roldan, Isabel Vera, Nana Williams, Alex Almuedo-Riera, Jose Muñoz, and all the staff members.
      Department of Internal Medicine: Miquel Camafort, Julia Calvo, Aina Capdevila, Francesc Cardellach, Emmanuel Coloma, Ramon Estruch, Joaquim Fernández-Solá, Alfons López-Soto, Ferran Masanés, Jose Milisenda, Pedro Moreno, Jose Naval, David Nicolás, Omar Oberoi, Sergio Prieto-González, Olga Rodríguez-Núnez, Emili Secanella, Cristina Sierra, and all the staff members.
      Department of Microbiology: Manel Almela, Míriam Alvarez, Jordi Bosch, Josep Costa, Julià Gonzàlez, Francesc Marco, Sofia Narvaez, Cristina Pitart, Elisa Rubio, Andrea Vergara, Mª Eugenia Valls, Jordi Vila, and all the staff members.
      Department of Farmacy: Esther López, Montse Tuset, and all the staff members.
      Other acknowledgments: We would like to thank Anthony Armenta for providing medical editing assistance for the manuscript at hand.

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