Internal and emergency medicine
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Lung ultrasound (LUS) is an effective tool for diagnosing acute heart failure (AHF). However, several imaging protocols currently exist and how to best use LUS remains undefined. We aimed at developing a lung ultrasound-based model for AHF diagnosis using machine learning. ⋯ Accuracy in the validation cohort was excellent (AUC = 0.906). Importantly, adding the algorithm on top of a validated clinical score and classical definition of positive LUS scanning for AHF resulted in a significant improvement in diagnostic accuracy (continuous net reclassification improvement = 1.21, P < 0.001). Our simple lung ultrasound-based machine learning algorithm features an excellent performance and may constitute a validated strategy to diagnose AHF.
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High-Dependency care Units (HDUs) have been introduced worldwide as intermediate wards between Intensive Care Units (ICUs) and general wards. Performing a comparative assessment of the quality of care in HDU is challenging because there are no uniform standards and heterogeneity among centers is wide. The Fenice network promoted a prospective cohort study to assess the quality of care provided by HDUs in Italy. ⋯ The expertise of HDUs in managing complex and fragile patients is supported by both the available equipment and the characteristics of admitted patients. The limited proportion of patients transferred to ICUs supports the hypothesis of preventing of ICU admissions. The heterogeneity of HDU admissions requires further research to define meaningful patients' outcomes to be used by quality-of-care assessment programs.