Medicina intensiva
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Intensive care is an ideal environment for the use of Big Data Analysis (BDA) and Machine Learning (ML), due to the huge amount of information processed and stored in electronic format in relation to such care. These tools can improve our clinical research capabilities and clinical decision making in the future. The present study reviews the foundations of BDA and ML, and explores possible applications in our field from a clinical viewpoint. We also suggest potential strategies to optimize these new technologies and describe a new kind of hybrid healthcare-data science professional with a linking role between clinicians and data.
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Multicenter Study
Prone positioning before extracorporeal membrane oxygenation for severe acute respiratory distress syndrome: A retrospective multicenter study.
To evaluate the clinical outcomes of patients with severe acute respiratory distress syndrome (ARDS) subjected to prone positioning before extracorporeal membrane oxygenation (ECMO). ⋯ Prone positioning before ECMO was not associated to increased mortality and tended to exert a protective effect.
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Observational Study
Rotational thromboelastometry (ROTEM) profile in a cohort of asystole donors.
Hypoperfusion plays a central role in shock states, and has been proposed as a coagulopathy trigger. The study of the rotational thromboelastometry (ROTEM) profile during cardiac arrest could offer new insights to the role of hypoperfusion in coagulation during shock states. ⋯ The ROTEM assays revealed severe alterations of the clot formation parameters and a high incidence of hyperfibrinolysis.