for the ConPlas-19 Study Group* *Complete list of the ConPlas-19 study group provided in the Supplement.

Background The clinical presentation of COVID-19 in patients admitted to hospital is heterogeneous. We aimed to determine whether clinical phenotypes of patients with COVID-19 can be derived from clinical data, to assess the reproducibility of these phenotypes and correlation with prognosis, and to derive and validate a simplified probabilistic model for phenotype assignment. Phenotype identification was not primarily intended as a predictive tool for mortality. MethodsIn this study, we used data from two cohorts: the COVID-19@Spain cohort, a retrospective cohort including 4035 consecutive adult patients admitted to 127 hospitals in Spain with COVID-19 between Feb 2 and March 17, 2020, and the COVID-19@HULP cohort, including 2226 consecutive adult patients admitted to a teaching hospital in Madrid between Feb 25 and April 19, 2020. The COVID-19@Spain cohort was divided into a derivation cohort, comprising 2667 randomly selected patients, and an internal validation cohort, comprising the remaining 1368 patients. The COVID-19@HULP cohort was used as an external validation cohort. A probabilistic model for phenotype assignment was derived in the derivation cohort using multinomial logistic regression and validated in the internal validation cohort. The model was also applied to the external validation cohort. 30-day mortality and other prognostic variables were assessed in the derived phenotypes and in the phenotypes assigned by the probabilistic model. Findings Three distinct phenotypes were derived in the derivation cohort (n=2667)-phenotype A (516 [19%] patients), phenotype B (1955 [73%]) and phenotype C (196 [7%])-and reproduced in the internal validation cohort (n=1368)phenotype A (233 [17%] patients), phenotype B (1019 [74%]), and phenotype C (116 [8%]). Patients with phenotype A were younger, were less frequently male, had mild viral symptoms, and had normal inflammatory parameters. Patients with phenotype B included more patients with obesity, lymphocytopenia, and moderately elevated inflammatory parameters. Patients with phenotype C included older patients with more comorbidities and even higher inflammatory parameters than phenotype B. We developed a simplified probabilistic model (validated in the internal validation cohort) for phenotype assignment, including 16 variables. In the derivation cohort, 30-day mortality rates were 2•5% (95% CI 1•4-4•3) for patients with phenotype A, 30•5% (28•5-32•6) for patients with phenotype B, and 60•7% (53•7-67•2) for patients with phenotype C (log-rank test p<0•0001). The predicted phenotypes in the internal validation cohort and external validation cohort showed similar mortality rates to the assigned phenotypes (internal validation cohort: 5•3% [95% CI 3•4-8•1] for phenotype A, 31•3% [28•5-34•2] for phenotype B, and 59•5% [48•8-69•3] for phenotype C; external validation cohort: 3•7% [2•0-6•4] for phenotype A, 23•7% [21•8-25•7] for phenotype B, and 51•4% [41•9-60•7] for phenotype C).Interpretation Patients admitted to hospital with COVID-19 can be classified into three...

Bacterial infections may complicate the course of COVID-19 patients. The rate and predictors of bacterial infections were examined in patients consecutively admitted with COVID-19 at one tertiary hospital in Madrid between March 1st and April 30th, 2020. Among 1594 hospitalized patients with COVID-19, 135 (8.5%) experienced bacterial infectious events, distributed as follows: urinary tract infections (32.6%), bacteremia (31.9%), pneumonia (31.8%), intra-abdominal infections (6.7%) and skin and soft tissue infections (6.7%). Independent predictors of bacterial infections were older age, neurological disease, prior immunosuppression and ICU admission (p < 0.05). Patients with bacterial infections who more frequently received steroids and tocilizumab, progressed to lower Sap02/FiO2 ratios, and experienced more severe ARDS (p < 0.001). The mortality rate was significantly higher in patients with bacterial infections as compared to the rest (25% vs 6.7%, respectively; p < 0.001). In multivariate analyses, older age, prior neurological or kidney disease, immunosuppression and ARDS severity were associated with an increased mortality (p < 0.05) while bacterial infections were not. Conversely, the use of steroids or steroids plus tocilizumab did not confer a higher risk of bacterial infections and improved survival rates. Bacterial infections occurred in 8.5% of patients hospitalized with COVID-19 during the first wave of the pandemic. They were not independently associated with increased mortality rates. Baseline COVID-19 severity rather than the incidence of bacterial infections seems to contribute to mortality. When indicated, the use of steroids or steroids plus tocilizumab might improve survival in this population.

Introduction SARS-CoV-2 pneumonia is often associated with hyper-inflammation. The cytokine-storm-like is one of the targets of current therapies for coronavirus disease 2019 (COVID-19). High Interleukin-6 (IL6) blood levels have been identified in severe COVID-19 disease, but there are still uncertainties regarding the actual role of anti-IL6 antagonists in COVID-19 management. Our hypothesis was that the use of sarilumab plus corticosteroids at an early stage of the hyper-inflammatory syndrome would be beneficial and prevent progression to acute respiratory distress syndrome (ARDS). Methods We randomly assigned (in a 1:1 ratio) COVID-19 pneumonia hospitalized patients under standard oxygen therapy and laboratory evidence of hyper-inflammation to receive sarilumab plus usual care (experimental group) or usual care alone (control group). Corticosteroids were given to all patients at a 1 mg/kg/day of methylprednisolone for at least 3 days. The primary outcome was the proportion of patients progressing to severe respiratory failure (defined as a score in the Brescia-COVID19 scale ≥ 3) up to day 15. Results A total of 201 patients underwent randomization: 99 patients in the sarilumab group and 102 patients in the control group. The rate of patients progressing to severe respiratory failure (Brescia-COVID scale score ≥ 3) up to day 15 was 16.16% in the Sarilumab group versus 15.69% in the control group (RR 1.03; 95% CI 0.48–2.20). No relevant safety issues were identified. Conclusions In hospitalized patients with Covid-19 pneumonia, who were under standard oxygen therapy and who presented analytical inflammatory parameters, an early therapeutic intervention with sarilumab plus standard of care (including corticosteroids) was not shown to be more effective than current standard of care alone. The study was registered at EudraCT with number: 2020-002037-15. Supplementary Information The online version contains supplementary material available at 10.1007/s40121-021-00543-2.