Avaliação de escores de risco para a predição de mortalidade em pacientes com covid-19 admitidos em unidades de terapia intensiva de hospitais brasileiros

• Ano de defesa: 2023
• Autor(a) principal: Matheus Carvalho Alves Nogueira
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Minas Gerais; Brasil; MEDICINA - FACULDADE DE MEDICINA; Programa de Pós-Graduação em Ciências da Saúde - Infectologia e Medicina Tropical; UFMG
• Palavras-chave em Português: mortalidade; covid-19; SARS-CoV-2; unidade de terapia intensiva; prognóstico; fatores de risco; Mortalidade; COVID-19; Unidades de Terapia Intensiva; Prognóstico; Fatores de Risco; Estudos Retrospectivos
• Link de acesso: http://hdl.handle.net/1843/64936

Introduction: The covid-19 pandemic has brought many challenges to healthcare systems around the world; among them, to predict which patients have a greater chance of serious complications. Several risk scores have already been tested for this purpose, including in the intensive care setting, but often with methodological limitations. The performance of the risk score developed and validated in Brazil, the ABC2-SPH, had never been tested before specifically in this subgroup of covid-19 patients admitted to the Intensive Care Unit (ICU). Objectives: To assess the accuracy of the ABC2-SPH score when used upon admission to the ICU to predict in-hospital mortality of covid-19 patients, and to compare its performance with that of other scores (SOFA, SAPS-3, NEWS2, 4C Mortality Score, SOARS, CURB-65, modified CHA2DS2-VASc, and a novel severity score proposed by Altschul). Methods: Retrospective cohort study. Consecutive adult patients (≥ 18 years) with laboratory-confirmed covid-19, admitted to the intensive care units (ICUs) of 25 hospitals in 17 Brazilian cities, between October 4, 2020, and March 13, 2022, were enrolled. Overall performance of the scores was evaluated using the Brier score, and the discrimination of each model was described by the Area under the Receiver Operating Characteristic Curve (AUROC), with their confidence intervals of 95%. Positive and negative predictive values derived from risk scores for the outcome of death were also calculated. ABC2SPH was used as the reference score for every comparisons, which were performed by using the Bonferroni method of correction. Results: A total of 3,037 patients were included in the final analysis, with an in-hospital mortality of 50,0%. ABC2-SPH had an area under the curve of 0.716 (95% CI 0.693 - 0.738), higher than CURB65, SOFA, NEWS2, SOARS, and modified CHA2DS2-VASc scores. There was no statistically significant difference between ABC2-SPH and SAPS-3, 4C Score, and the novel severity score proposed by Altschul. Conclusions: The evaluated scores, including some routinely used, performed poorly to moderately to predict in-hospital mortality of patients with severe COVID-19 at the time of ICU admission, with areas under the curve ranging from 0.605 to 0.716. The ABC2-SPH, however, was, in absolute numbers, the one with the largest area under the curve, being statistically significantly superior to five of the scores tested, as mentioned above. However, in order to obtain excellent accuracy, it is likely that a new score will have to be developed for this specific subgroup of patients.