Articles: critical-illness.
-
Multicenter Study
Evaluation of thiamine as adjunctive therapy in COVID-19 critically ill patients: a two-center propensity score matched study.
Thiamine is a precursor of the essential coenzyme thiamine pyrophosphate required for glucose metabolism; it improves the immune system function and has shown to reduce the risk of several diseases. The role of thiamine in critically ill septic patient has been addressed in multiple studies; however, it's role in COVID-19 patients is still unclear. The aim of this study was to evaluate the use of thiamine as an adjunctive therapy on mortality in COVID-19 critically ill patients. ⋯ Thiamine use as adjunctive therapy may have potential survival benefits in critically ill patients with COVID-19. Additionally, it was associated with a lower incidence of thrombosis. Further interventional studies are required to confirm these findings.
-
Background and Objectives: The aim of this study was to investigate the association between obesity and 28-day mortality, duration of invasive mechanical ventilation and length of stay at the Intensive Care Unit (ICU) and hospital in patients admitted to the ICU for SARS-CoV-2 pneumonia. Materials and Methods: This was a retrospective observational cohort study in patients admitted to the ICU for SARS-CoV-2 pneumonia, in a single Dutch center. The association between obesity (body mass index > 30 kg/m2) and 28-day mortality, duration of invasive mechanical ventilation and length of ICU and hospital stay was investigated. ⋯ Conclusion: One-third of the patients admitted to the ICU for SARS-CoV-2 pneumonia had obesity. The present study showed no relationship between obesity and 28-day mortality, duration of invasive mechanical ventilation, ICU and hospital length of stay. Further studies are needed to substantiate these findings.
-
Beijing Da Xue Xue Bao · Jun 2021
[Prediction of intensive care unit readmission for critically ill patients based on ensemble learning].
To develop machine learning models for predicting intensive care unit (ICU) readmission using ensemble learning algorithms. ⋯ The ensemble learning based ICU readmission prediction models had better performance than Logistic regression model. Such ensemble learning models have the potential to aid ICU physicians in identifying those patients with high risk of ICU readmission and thus help improve overall clinical outcomes.