Percorrer por autor "Cabral, Susana Isabel de Lousa"
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- The impact of different types of respiratory failure on death in the ICU, in a Portuguese population with COVID-19Publication . Cabral, Susana Isabel de Lousa; Pinto, Iola Maria Silvério; Bento, LuísAbstract Background: The COVID-19 pandemic, caused by SARS-CoV-2, was one of the major challenges of the 21st century. It rapidly spread worldwide, ranging from mild to critical forms. Early identification of high-risk patients was essential to optimize treatment and resources. Arterial blood gas (ABG) analysis provided information on oxygenation, ventilation, and acid-base balance, for early disease severity assessment at intensive care unit (ICU) admission. Purpose: To assess the predictive value of ABG parameters (PaO2, PaCO2, pH, and lactate) for adverse clinical outcomes (ICU death, need for invasive mechanical ventilation (IMV), and extracorporeal membrane oxygenation (ECMO)) and their association with the duration of ICU stay and invasive supports. Methods: Observational and retrospective study including 794 COVID-19 patients admitted to the ICU of Unidade Local de Saúde de São José between October 2020 and January 2022. ABG parameters from admission day, along with demographic and clinical variables, were analyzed using parametric and non-parametric tests. Generalized linear models (GLM) with a negative binomial distribution identified factors influencing the duration of ICU stay and invasive supports. Results: Non-survivors had lower pH and PaO2 and higher lactate levels, indicating more severe respiratory and metabolic impairment. IMV and ECMO needs were associated with lower pH and higher PaCO2. Patients with comorbidities had higher ICU mortality, and significant difference was found across pandemic waves. The GLMs showed that maximum PaCO2, being male, not having chronic lung disease and being unvaccinated prolonged ICU stay and support duration, while maximum lactate and non-obese were associated with shorter durations. Conclusion: Early ABG assessment demonstrated the utility of these parameters as a predictive tool for risk stratification in critically ill COVID-19 patients, supporting their integration into prognostic models and personalized approaches to ICU management.