Med Intensiva (Engl Ed)
December 2024
Introduction: From a safety perspective, the pandemic imposed atypical work dynamics that led to noticeable gaps in clinical safety across all levels of health care.
Objectives: To verify that Real-Time Random Safety Analyses (AASTRE) are feasible and useful in a high-pressure care setting.
Design: Prospective study (January-September 2022).
: Bacterial/fungal coinfections (COIs) are associated with antibiotic overuse, poor outcomes such as prolonged ICU stay, and increased mortality. Our aim was to develop machine learning-based predictive models to identify respiratory bacterial or fungal coinfections upon ICU admission. : We conducted a secondary analysis of two prospective multicenter cohort studies with confirmed influenza A (H1N1)pdm09 and COVID-19.
View Article and Find Full Text PDFPatient safety is a priority for all healthcare systems. Despite this, too many patients still suffer harm as a consequence of healthcare. Furthermore, it has a significant impact on family members, professionals and healthcare institutions, resulting in considerable economic costs.
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