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.

OBJECTIVETo analyze the causes of delay in hospital discharge of patients admitted to internal medicine wards.METHODSWe reviewed 395 medical records of consecutive patients admitted to internal medicine wards of two public teaching hospitals: Hospital das Clínicas of the Universidade Federal de Minas Gerais and Hospital Odilon Behrens. The Appropriateness Evaluation Protocol was used to define the moment at which notes in the medical records indicated hospital stay was no longer appropriate and patients could be discharged. The interval between this estimated time and actual discharge was defined as the total number of days of delay in hospital discharge. An instrument was used to systematically categorize reasons for delay in hospital discharge and frequencies were analyzed.RESULTSDelays in discharge occurred in 60.0% of 207 hospital admissions in the Hospital das Clínicas and in 58.0% of 188 hospital admissions in the Hospital Odilon Behrens. Mean delay per patient was 4.5 days in the former and 4.1 days in the latter, corresponding to 23.0% and 28.0% of occupancy rates in each hospital, respectively. The main reasons for delay in the two hospitals were, respectively, waiting for complementary tests (30.6% versus 34.7%) or for results of performed tests to be released (22.4% versus 11.9%) and medical-related accountability (36.2% versus 26.1%) which comprised delays in discussing the clinical case and in clinical decision making and difficulties in providing specialized consultation (20.4% versus 9.1%).CONCLUSIONSBoth hospitals showed a high percentage of delay in hospital discharge. The delays were mainly related to processes that could be improved by interventions by care teams and managers. The impact on mean length of stay and hospital occupancy rates was significant and troubling in a scenario of relative shortage of beds and long waiting lists for hospital admission.

Background and Purpose-It has been suggested that Chagas disease (CD) and particularly CD cardiomyopathy are independent risk factors for cerebrovascular events. Strong evidence is scarce, cardioembolic and inflammatory mechanisms have been proposed, and most studies lack representative and well-matched controls. We sought to investigate CD, defined by positive serology, as an independent risk factor for stroke, by comparing patients admitted with ischemic stroke with representative control patients with a very similar cardiovascular risk factor profile. Methods-We performed a case-control study with 101 consecutive stroke patients and 100 consecutive acute coronary syndrome patients admitted to an emergency hospital. CD was investigated in all patients and was confirmed when both immunofluorescence and hemagglutination tests were positive. Clinical, laboratory, and ECG findings were analyzed.

We investigated the validity of the abbreviated mental test (AMT) as a guide to the diagnosis of delirium in 100 patients aged more than 65 yr. Patients were assessed using the AMT on the day before and on the third day after operation. Fifteen patients were delirious on the third postoperative day; 10 of 43 patients undergoing orthopaedic surgery and five of 57 patients undergoing non-orthopaedic surgery. Delirium developed in four of 16 patients with a preoperative AMT score less than 8 and in 11 of 84 patients with a preoperative AMT score of 8 or more. Patients who developed delirium had a greater decline in AMT score (mean 2.7 (SD 0.9)) than patients who did not develop delirium (0.7 (1.0)) (P < 0.001). The sensitivity and specificity of a decline in AMT score of 2 or more points after surgery for diagnosis of postoperative delirium were 93% and 84%, respectively.