Publications by authors named "Daniel Jorge Jakobson"
Article Synopsis
- The study created a machine learning model to help doctors monitor COVID-19 patients in hospitals and spot who might get worse soon.
- They used real patient data to test how well the model works, focusing on eight blood tests that change before a patient gets more severe.
- The model showed good accuracy in predicting patient status changes, and if successful in future studies, it could help doctors give better care and manage hospital resources.
Purpose: The aim of the study was to document transfusion practices in a cross section of general intensive care units (ICUs) in Israel and to determine whether current guidelines are being applied.
Materials And Methods: This prospective study was performed in 5 general ICUs in Israel over a 3-month period. Red cell transfusion data collected on consecutive patients included the trigger, units transfused per transfusion event, and indications, categorized either to treat a specified condition for which transfusions may be beneficial (acute hemorrhage, acute myocardial ischemia, or severe sepsis) or to treat a low hemoglobin concentration.