SARS-CoV-2 infection has a wide spectrum of presentations, from asymptomatic to pneumonia and sepsis. Risk scores have been used as triggers for protocols that combine several interventions for early management of sepsis. This study tested the accuracy of the score SIRS, qSOFA, and NEWS in predicting outcomes, including mortality and bacterial infection, in patients admitted to the emergency department (ED) during the COVID-19 pandemic. We described 2,473 cases of COVID-19 admitted to the ED of the largest referral hospital for severe COVID-19 in Brazil during the pandemic. SIRS, qSOFA and NEWS scores showed a poor performance as prognostic scores. However, NEWS score had a high sensitivity to predict in-hospital death (0.851), early bacterial infection (0.851), and ICU admission (0.868), suggesting that it may be a good screening tool for severe cases of COVID-19, despite its low specificity.

Background Capacity strain negatively impacts patient outcome, and the effects of patient surge are a continuous threat during the COVID-19 pandemic. Evaluating changes in mortality over time enables evidence-based resource planning, thus improving patient outcome. Our aim was to describe baseline risk factors associated with mortality among COVID-19 hospitalized patients and to compare mortality rates over time. Methods We conducted a retrospective cohort study in the largest referral hospital for COVID-19 patients in Sao Paulo, Brazil. We investigated risk factors associated with mortality during hospitalization. Independent variables included age group, sex, the Charlson Comorbidity Index, admission period according to the stage of the first wave of the epidemic (early, peak, and late), and intubation. Results We included 2949 consecutive COVID-19 patients. 1895 of them were admitted to the ICU, and 1473 required mechanical ventilation. Median length of stay in the ICU was 10 (IQR 5–17) days. Overall mortality rate was 35%, and the adjusted odds ratios for mortality increased with age, male sex, higher Charlson Comorbidity index, need for mechanical ventilation, and being admitted to the hospital during the wave peak of the epidemic. Being admitted to the hospital during the wave peak was associated with a 33% higher risk of mortality. Conclusions In-hospital mortality was independently affected by the epidemic period. The recognition of modifiable operational variables associated with patient outcome highlights the importance of a preparedness plan and institutional protocols that include evidence-based practices and allocation of resources.

Despite solid scientific evidence, the concepts of treatment as prevention (TASP) and Undetectable = Untransmittable (U = U) remain unfamiliar and underutilized for some healthcare providers. We conducted a self-completion survey to evaluate the knowledge of TASP/U = U in different medical specialties. Wilcoxon Rank-Sum, Chi-square and Fisher’s exact tests were used for group comparisons and a logistic regression model was used to assess factors independently associated with U = U-non-supportive attitudes. 197 physicians were included; 74% agreed/strongly agreed that people living with HIV (PLHIV) under regular treatment with undetectable viral do not transmit HIV sexually. However, only 66% agree/strongly agree that PLHIV should be informed about that. The knowledge about these concepts was poorer among gynecologists, urologists and internal medicine specialists when compared to infectious diseases specialists after adjustment for age, race/skin color, gender, and sexual orientation. Our study found that knowledge of crucial concepts of HIV prevention may be lacking for some medical specialties. This highlights the need of improvement in medical education.

Objectives We aim to compare differences in mortality risk factors between admission and follow-up incorporated models. Methods A retrospective cohort study with 524 patients with confirmed COVID-19 infection admitted to a tertiary medical center in São Paulo, Brazil, from March 13 th to April 30 th , 2020. We collected data at admission, 3 rd , 8 th and 14 th day of hospitalization. We calculated the hazard ratio (HR) and compared 28-day in-hospital mortality risk factors between admission and follow-up models using a time-dependent Cox regression model. Results Of 524 patients, 50.4% needed mechanical ventilation. The 28-day mortality rate was 32.8%. Compared to follow-up, admission models under-estimated the mortality HR for peripheral oxygen saturation<92% (1.21 versus 2.09), heart rate>100bpm (1.19 versus 2.04), respiratory rate>24ipm (1.01 versus 1.82) and mechanical ventilation (1.92 versus 12.93). Low oxygen saturation, higher oxygen support and more biomarkers including lactate dehydrogenase, c-reactive protein, neutrophil-lymphocyte ratio and urea remained associated with mortality after adjustment for clinical factors at follow-up compared to only urea and oxygen support at admission. Conclusions The inclusion of follow-up measurements changed mortality hazards of clinical signs and biomarkers. Low oxygen saturation, higher oxygen support, lactate dehydrogenase, c-reactive protein, neutrophil-lymphocyte ratio and urea could help prognose patients during follow-up.

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