Objectives To analyse the characteristics and predictors of death in hospitalized patients with coronavirus disease 2019 (COVID-19) in Spain. Methods A retrospective observational study was performed of the first consecutive patients hospitalized with COVID-19 confirmed by real-time PCR assay in 127 Spanish centres until 17 March 2020. The follow-up censoring date was 17 April 2020. We collected demographic, clinical, laboratory, treatment and complications data. The primary endpoint was all-cause mortality. Univariable and multivariable Cox regression analyses were performed to identify factors associated with death. Results Of the 4035 patients, male subjects accounted for 2433 (61.0%) of 3987, the median age was 70 years and 2539 (73.8%) of 3439 had one or more comorbidity. The most common symptoms were a history of fever, cough, malaise and dyspnoea. During hospitalization, 1255 (31.5%) of 3979 patients developed acute respiratory distress syndrome, 736 (18.5%) of 3988 were admitted to intensive care units and 619 (15.5%) of 3992 underwent mechanical ventilation. Virus- or host-targeted medications included lopinavir/ritonavir (2820/4005, 70.4%), hydroxychloroquine (2618/3995, 65.5%), interferon beta (1153/3950, 29.2%), corticosteroids (1109/3965, 28.0%) and tocilizumab (373/3951, 9.4%). Overall, 1131 (28%) of 4035 patients died. Mortality increased with age (85.6% occurring in older than 65 years). Seventeen factors were independently associated with an increased hazard of death, the strongest among them including advanced age, liver cirrhosis, low age-adjusted oxygen saturation, higher concentrations of C-reactive protein and lower estimated glomerular filtration rate. Conclusions Our findings provide comprehensive information about characteristics and complications of severe COVID-19, and may help clinicians identify patients at a higher risk of death.

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...

Background Since December 2019, the COVID-19 pandemic has changed the concept of medicine. This work aims to analyze the use of antibiotics in patients admitted to the hospital due to SARS-CoV-2 infection. Methods This work analyzes the use and effectiveness of antibiotics in hospitalized patients with COVID-19 based on data from the SEMI-COVID-19 registry, an initiative to generate knowledge about this disease using data from electronic medical records. Our primary endpoint was all-cause in-hospital mortality according to antibiotic use. The secondary endpoint was the effect of macrolides on mortality. Results Of 13,932 patients, antibiotics were used in 12,238. The overall death rate was 20.7% and higher among those taking antibiotics (87.8%). Higher mortality was observed with use of all antibiotics (OR 1.40, 95% CI 1.21–1.62; p < .001) except macrolides, which had a higher survival rate (OR 0.70, 95% CI 0.64–0.76; p < .001). The decision to start antibiotics was influenced by presence of increased inflammatory markers and any kind of infiltrate on an x-ray. Patients receiving antibiotics required respiratory support and were transferred to intensive care units more often. Conclusions Bacterial co-infection was uncommon among COVID-19 patients, yet use of antibiotics was high. There is insufficient evidence to support widespread use of empiric antibiotics in these patients. Most may not require empiric treatment and if they do, there is promising evidence regarding azithromycin as a potential COVID-19 treatment.

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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.

Background: Since December 2019, the COVID-19 pandemic has changed the concept of medicine. This work aims to analyze the use of antibiotics in patients admitted to the hospital due to SARS-CoV-2 infection. Methods: This work analyzes the use and effectiveness of antibiotics in hospitalized patients with COVID-19 based on data from the SEMI-COVID-19 registry, an initiative to generate knowledge about this disease using data from electronic medical records. Our primary endpoint was all-cause in-hospital mortality according to antibiotic use. The secondary endpoint was the effect of macrolides on mortality. Results: Of 13,932 patients, antibiotics were used in 12,238. The overall death rate was 20.7% and higher among those taking antibiotics (87.8%). Higher mortality was observed with use of all antibiotics (OR 1.40, 95%CI 1.21-1.62; p<.001) except macrolides, which had a higher survival rate (OR 0.70, 95%CI 0.64-0.76; p<.001). The decision to start antibiotics was influenced by presence of increased inflammatory markers and any kind of infiltrate on an x-ray. Patients receiving antibiotics required respiratory support and were transferred to intensive care units more often. Conclusions: Bacterial co-infection was uncommon among COVID-19 patients, yet use of antibiotics was high. There is insufficient evidence to support widespread use of empiric antibiotics in these patients. Most may not require empiric treatment and if they do, there is promising evidence regarding azithromycin as a potential COVID-19 treatment.

Highlights Multicentric prospective observational study of 94 EEG in 62 patients with COVID-19. The most frequent EEG finding was generalized slow-wave activity (66 %). Epileptiform activity (19 %) included NCSE, seizures and interictal discharges. Mortality was increased in patients with cancer comorbidity. Mortality was increased in patients who required an EEG during the 3 rd week.

Objectives (1) To describe the incidence, clinical characteristics, treatment and outcome of Aspergillus Endocarditis (AE) in a nationwide multicentric cohort (GAMES). (2) To compare the AE cases of the GAMES cohort, with the AE cases reported in the literature since 2010. (3) To identify variables related to mortality. Methods We recruited 10 AE cases included in the GAMES cohort (January 2008‐December 2018) and 51 cases from the literature published from January 2010 to July 2019. Results 4528 patients with infectious endocarditis (IE) were included in the GAMES cohort, of them 10 (0.2%) were AE. After comparing our 10 cases with the 51 of the literature, no differences were found. Analysing the 61 AE cases together, 55.7% were male, median age 45 years. Their main underlying conditions were as follows: prosthetic valve surgery (34.4%) and solid organ transplant (SOT) (19.7%). Mainly affecting mitral (36.1%) and aortic valve (29.5%). Main isolated species were as follows: Aspergillus fumigatus (47.5%) and Aspergillus flavus (24.6%). Embolisms occurred in 54%. Patients were treated with antifungals (90.2%), heart surgery (85.2%) or both (78.7%). Overall, 52.5% died. A greater mortality was observed in immunosuppressed patients (59.4% vs. 24.1%, OR = 4.09, 95%CI = 1.26–13.19, p = .02), and lower mortality was associated with undergoing cardiac surgery plus azole therapy (28.1% vs. 65.5%, OR = 0.22, 95%CI = 0.07–0.72, p = .01). Conclusions AE accounts for 0.2% of all IE episodes of a national multicentric cohort, mainly affecting patients with previous valvular surgery or SOT recipients. Mortality remains high especially in immunosuppressed hosts and azole‐based treatment combined with surgical resection are related to a better outcome.