Aging-related predictive factors for oxygenation improvement and mortality in COVID-19 and acute respiratory distress syndrome (ARDS) patients exposed to prone position: A multicenter cohort study

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.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data

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.

Aging-related predictive factors for oxygenation improvement and mortality in COVID-19 and acute respiratory distress syndrome (ARDS) patients exposed to prone position: A multicenter cohort study.

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.

Prediction of intensive care admission and hospital mortality in COVID-19 patients using demographics and baseline laboratory data.

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.