Automated versus manual B-lines counting, left ventricular outflow tract velocity time integral and inferior vena cava collapsibility index in COVID-19 patients.

Background And Aims: The incorporation of artificial intelligence (AI) in point-of-care ultrasound (POCUS) has become a very useful tool to quickly assess cardiorespiratory function in coronavirus disease (COVID)-19 patients. The objective of this study was to test the agreement between manual and automated B-lines counting, left ventricular outflow tract velocity time integral (LVOT-VTI) and inferior vena cava collapsibility index (IVC-CI) in suspected or confirmed COVID-19 patients using AI integrated POCUS. In addition, we investigated the inter-observer, intra-observer variability and reliability of assessment of echocardiographic parameters using AI by a novice.