Abstract Background: Elderly patients are more susceptible to Coronavirus Disease-2019 (COVID-19) and are more likely to develop it in severe forms, (e.g., Acute Respiratory Distress Syndrome [ARDS]). Prone positioning is a treatment strategy for severe ARDS; however, its response in the elderly population remains poorly understood. The main objective was to evaluate the predictive response and mortality of elderly patients exposed to prone positioning due to ARDS-COVID-19. Methods: This retrospective multicenter cohort study involved 223 patients aged ≥ 65 years, who received prone position sessions for severe ARDS due to COVID-19, using invasive mechanical ventilation. The PaO2/FiO2 ratio was used to assess the oxygenation response. The 20-point improvement in PaO2/FiO2 after the first prone session was considered for good response. Data were collected from electronic medical records, including demographic data, laboratory/image exams, complications, comorbidities, SAPS III and SOFA scores, use of anticoagulants and vasopressors, ventilator settings, and respiratory system mechanics. Mortality was defined as deaths that occurred until hospital discharge. Results: Most patients were male, with arterial hypertension and diabetes mellitus as the most prevalent comorbidities. The non-responders group had higher SAPS III and SOFA scores, and a higher incidence of complications. There was no difference in mortality rate. A lower SAPS III score was a predictor of oxygenation response, and the male sex was a risk predictor of mortality. Conclusion: The present study suggests the oxygenation response to prone positioning in elderly patients with severe COVID-19-ARDS correlates with the SAPS III score. Furthermore, the male sex is a risk predictor of mortality. Background Disease2019 Disease 2019 Disease-201 COVID19 COVID 19 (COVID-19 forms e.g., eg e g (e.g. ARDS. . [ARDS]) however understood ARDSCOVID19. ARDSCOVID19 ARDSCOVID 19. ARDS-COVID-19 Methods 22 6 years COVID19, 19, COVID-19 ventilation PaO2FiO2 PaOFiO PaO2 FiO2 PaO FiO PaO2/FiO 20point point 20 records data laboratoryimage laboratory image exams complications comorbidities scores vasopressors settings mechanics discharge Results nonresponders non responders rate Conclusion COVID19ARDS COVIDARDS Furthermore Disease201 201 Disease-20 COVID1 1 (COVID-1 e.g. (e.g [ARDS] ARDSCOVID1 ARDS-COVID-1 2 COVID-1 PaO2FiO Disease20 Disease-2 (COVID- e.g [ARDS ARDS-COVID- COVID- Disease2 Disease- (COVID ARDS-COVID

Abstract Introduction: Optimized allocation of medical resources to patients with COVID-19 has been a critical concern since the onset of the pandemic. Methods: In this retrospective cohort study, the authors used data from a Brazilian tertiary university hospital to explore predictors of Intensive Care Unit (ICU) admission and hospital mortality in patients admitted for COVID-19. Our primary aim was to create and validate prediction scores for use in hospitals and emergency departments to aid clinical decisions and resource allocation. Results: The study cohort included 3,022 participants, of whom 2,485 were admitted to the ICU; 1968 survived, and 1054 died in the hospital. From the complete cohort, 1,496 patients were randomly assigned to the derivation sample and 1,526 to the validation sample. The final scores included age, comorbidities, and baseline laboratory data. The areas under the receiver operating characteristic curves were very similar for the derivation and validation samples. Scores for ICU admission had a 75% accuracy in the validation sample, whereas scores for death had a 77% accuracy in the validation sample. The authors found that including baseline flu-like symptoms in the scores added no significant benefit to their accuracy. Furthermore, our scores were more accurate than the previously published NEWS-2 and 4C Mortality Scores. Discussion and conclusions: The authors developed and validated prognostic scores that use readily available clinical and laboratory information to predict ICU admission and mortality in COVID-19. These scores can become valuable tools to support clinical decisions and improve the allocation of limited health resources. Introduction COVID19 COVID 19 COVID-1 pandemic Methods (ICU COVID19. 19. Results 3022 3 022 3,02 participants 2485 2 485 2,48 196 survived 105 1496 1 496 1,49 1526 526 1,52 age comorbidities samples 75 77 flulike flu like Furthermore NEWS2 NEWS NEWS- C conclusions COVID1 COVID- 302 02 3,0 248 48 2,4 10 149 49 1,4 152 52 1,5 7 30 0 3, 24 4 2, 14 1, 15 5