A proposed lung ultrasound and phenotypic algorithm for the care of COVID-19 patients with acute respiratory failure.
André Y DenaultStéphane DelisleDavid CantyAlistair RoyseColin RoyseXimena Cid SerraCaroline E GebhardÉtienne J CoutureMartin GirardYiorgos Alexandros CavayasNicolas PeschanskiStéphan LangevinPaul OuelletPublished in: Canadian journal of anaesthesia = Journal canadien d'anesthesie (2020)
Pulmonary complications are the most common clinical manifestations of coronavirus disease (COVID-19). From recent clinical observation, two phenotypes have emerged: a low elastance or L-type and a high elastance or H-type. Clinical presentation, pathophysiology, pulmonary mechanics, radiological and ultrasound findings of these two phenotypes are different. Consequently, the therapeutic approach also varies between the two. We propose a management algorithm that combines the respiratory rate and oxygenation index with bedside lung ultrasound examination and monitoring that could help determine earlier the requirement for intubation and other surveillance of COVID-19 patients with respiratory failure.
Keyphrases
- coronavirus disease
- respiratory failure
- extracorporeal membrane oxygenation
- sars cov
- mechanical ventilation
- magnetic resonance imaging
- pulmonary hypertension
- respiratory syndrome coronavirus
- machine learning
- deep learning
- healthcare
- public health
- acute respiratory distress syndrome
- palliative care
- quality improvement
- risk factors
- computed tomography
- blood flow