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To describe the clinical characteristics, laboratory results, imaging findings, and in-hospital outcomes of COVID-19 patients admitted to Brazilian hospitals. Methods: A cohort study of laboratory-confirmed COVID-19 patients who were hospitalized from March 2020 to September 2020 in 25 hospitals. Data were collected from medical records using Research Electronic Data Capture (REDCap) tools. A multivariate Poisson regression model was used to assess the risk factors for in-hospital mortality. Results: For a total of 2,054 patients (52.6% male; median age of 58 years), the in-hospital mortality was 22.0%; this rose to 47.6% for those treated in the intensive care unit (ICU). Hypertension (52.9%), diabetes (29.2%), and obesity (17.2%) were the most prevalent comorbidities. Overall, 32.5% required invasive mechanical ventilation, and 12.1% required kidney replacement therapy. Septic shock was observed in 15.0%, nosocomial infection in 13.1%, thromboembolism in 4.1%, and acute heart failure in 3.6%. Age >= 65 years, chronic kidney disease, hypertension, C-reactive protein ! 100 mg/dL, platelet count < 100 Â 10 9 /L, oxygen saturation < 90%, the need for supplemental oxygen, and invasive mechanical ventilation at admission were independently associated with a higher risk of in-hospital mortality. The overall use of antimicrobials was 87.9%. Conclusions: This study reveals the characteristics and in-hospital outcomes of hospitalized patients with confirmed COVID-19 in Brazil. Certain easily assessed parameters at hospital admission were independently associated with a higher risk of death. The high frequency of antibiotic use points to an over-use of antimicrobials in COVID-19 patients.

Objectives The majority of available scores to assess mortality risk of coronavirus disease 19 (COVID-19) patients in the emergency department have high risk of bias. Therefore, our aim was to develop and validate a score at hospital admission for predicting in-hospital mortality in COVID-19 patients, and to compare this score with other existing ones. Methods Consecutive patients (≥18 years) with confirmed COVID-19 admitted to the participating hospitals were included. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients admitted between March-July, 2020. The model was validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Results Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, and in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. Seven significant variables were included in the risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO 2 /FiO 2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859 [95% CI 0.833 to 0.885]) and Spanish (0.894 [95% CI 0.870 to 0.919]) validation cohorts, and displayed better discrimination ability than other existing scores. It is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.

RESUMOA qualidade de vida (QV) nos idosos é determinada em grande parte pelo seu estado funcional e condições de saúde. Com o objectivo de avaliar o nível de QV, os factores que a influenciam e identificar o grau de dependência dos idosos foi realizado um estudo observacional transversal do tipo exploratório-descritivo, englobando 93 idosos. Na recolha de dados utilizouse o índice de Barthel e MOS-SF 36. Na identificação dos níveis de dependência os resultados indicam-nos que 40,0% são independentes e 18,0% são dependentes mínimos, sendo 12,0% dependentes totais. No que diz respeito à QV 88,0% dos sujeitos refere uma pontuação inferior a 50,0%, em média reportam uma QV de 39±10,0%. Verificou-se que existe uma correlação positiva entre o grau de dependência e o índice de QV, sobretudo na componente física. Assim, importa promover um envelhecimento saudável procurando-se privilegiar a preservação da autonomia e capacidade funcional dos idosos. Descritores: Idosos; Dependência; Qualidade de Vida. ABSTRACTThe quality of life (QoL) in older adults is largely determined by their functional status and health conditions. With the purpose of investigate the QoL and the factors affecting it, and identify the degree of dependency of the elderly was carried out an observational cross-sectional exploratory and descriptive, involving 93 elderly. In collecting data we used the Barthel Index and MOS SF-36. In the identification of levels of dependency results indicate us that 40.0% are independent and 18.0% are dependents, minimum being 12.0% total-dependent. The results show us that, 88.0% of the subjects reported a score below 50.0% on average reported a QoL of 39±10.0%. Checking that are a positive correlation between the degree of dependence and the index of QoL, especially in the physical component. It is therefore important to promote healthy aging in an attempt to favor the preservation of autonomy and functional capacity of the elderly. Key words: Elders; Dependency; Quality of Life. RESUMENLa calidad de vida (CV) en los adultos mayores es en gran parte determinado por su estado funcional y las condiciones de salud. Con el fin de evaluar el nivel de CV y los factores que influyen en ella y determinar el grado de dependencia de los ancianos se llevó a cabo un estudio observacional transversal, exploratorio y descriptivo, que involucró a 93 personas mayores. En la recopilación de datos se utilizó el Índice de Barthel y el MOS SF-36. En la identificación de los nivele de dependiencia los resultados nos indican que 40,0% son independientes, 18,0% são dependentes mínimos y 12,0% dependientes totales. En lo que respeicta a la CV, 88,0% de los sujetos reportaron una puntuación inferior a 50,0% en promedio reportó una CV de 39±10,0%. Tomando nota de que existe una correlación positiva entre el grado de dependencia y el índice de calidad de vida, especialmente en el componente físico. Por tanto, es importante promover un envejecimiento saludable, en un intento de favorecer la preservación de la autonomía y la capacidad funcional...

Objective: To develop and validate a rapid scoring system at hospital admission for predicting in-hospital mortality in patients hospitalized with coronavirus disease 19 (COVID-19), and to compare this score with other existing ones. Design: Cohort study Setting: The Brazilian COVID-19 Registry has been conducted in 36 Brazilian hospitals in 17 cities. Logistic regression analysis was performed to develop a prediction model for in-hospital mortality, based on the 3978 patients that were admitted between March-July, 2020. The model was then validated in the 1054 patients admitted during August-September, as well as in an external cohort of 474 Spanish patients. Participants: Consecutive symptomatic patients (≥18 years old) with laboratory confirmed COVID-19 admitted to participating hospitals. Patients who were transferred between hospitals and in whom admission data from the first hospital or the last hospital were not available were excluded, as well those who were admitted for other reasons and developed COVID-19 symptoms during their stay. Main outcome measures: In-hospital mortality Results: Median (25th-75th percentile) age of the model-derivation cohort was 60 (48-72) years, 53.8% were men, in-hospital mortality was 20.3%. The validation cohorts had similar age distribution and in-hospital mortality. From 20 potential predictors, seven significant variables were included in the in-hospital mortality risk score: age, blood urea nitrogen, number of comorbidities, C-reactive protein, SpO2/FiO2 ratio, platelet count and heart rate. The model had high discriminatory value (AUROC 0.844, 95% CI 0.829 to 0.859), which was confirmed in the Brazilian (0.859) and Spanish (0.899) validation cohorts. Our ABC2-SPH score showed good calibration in both Brazilian cohorts, but, in the Spanish cohort, mortality was somewhat underestimated in patients with very high (>25%) risk. The ABC2-SPH score is implemented in a freely available online risk calculator (https://abc2sph.com/). Conclusions: We designed and validated an easy-to-use rapid scoring system based on characteristics of COVID-19 patients commonly available at hospital presentation, for early stratification for in-hospital mortality risk of patients with COVID-19.