Relationship between clinical-epidemiological parameters and outcomes of patients with COVID-19 admitted to the intensive care unit: a report from a Brazilian hospital - D’Carmo Sodré, Maisah Meyhr; dos Santos, Uener Ribeiro; Povoas, Heitor Portella; Guzmán, Júlio Lenin; Junqueira, Caroline; Trindade, Tayana Oliveira; Gadelha, Sandra Rocha; Romano, Carla Cristina; da Conceição, Aline Oliveira; Gross, Eduardo; Silva, Aline; Rezende, Rachel Passos; et al. (Frontiers in Public Health, 2023)
Background People in low-income countries, especially those with low socio-economic conditions, are likelier to test positive for SARS-CoV-2. The unequal conditions of public health systems also increase the infection rate and make early identification and treatment of at-risk patients difficult. Here, we aimed to characterize the epidemiological profile of COVID-19 patients in intensive care and identify laboratory and clinical markers associated with death. Materials and methods We conducted an observational, descriptive, and cross-sectional study in a reference hospital for COVID-19 treatment in the Southern Region of Bahia State, in Brazil, to evaluate the epidemiological, clinical, and laboratory characteristics of COVID-19 patients admitted to the intensive care unit (ICU). Additionally, we used the area under the curve (AUC) to classify survivors and non-survivors and a multivariate logistic regression analysis to assess factors associated with death. Data was collected from the hospital databases between April 2020 and July 2021. Results The use of bladder catheters (OR 79.30; p < 0.0001) and central venous catheters (OR, 45.12; p < 0.0001) were the main factors associated with death in ICU COVID-19 patients. Additionally, the number of non-survivors increased with age (p < 0.0001) and prolonged ICU stay (p < 0.0001). Besides, SAPS3 presents a higher sensibility (77.9%) and specificity (63.1%) to discriminate between survivors and non-survivor with an AUC of 0.79 (p < 0.0001). Conclusion We suggest that multi-laboratory parameters can predict patient prognosis and guide healthcare teams toward more assertive clinical management, better resource allocation, and improved survival of COVID-19 patients admitted to the ICU.