Open AccessAutomated versus manual B-lines counting, left ventricular outflow tract velocity time integral and inferior vena cava collapsibility index in COVID-19 patients
Author(s) -
Srinath Damodaran,
Anuja V Kulkarni,
Vikneswaran Gunaseelan,
Vimal Raj,
Muralidhar Kanchi
Publication year - 2022
Publication title -
indian journal of anaesthesia/indian journal of anaesthesia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.645
H-Index - 30
eISSN - 0976-2817
pISSN - 0019-5049
DOI - 10.4103/ija.ija_1008_21
Subject(s) - medicine , ventricular outflow tract , intraclass correlation , inferior vena cava , ultrasound , nuclear medicine , covid-19 , cardiology , radiology , disease , clinical psychology , infectious disease (medical specialty) , psychometrics
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.