ECMO during the COVID-19 pandemic: When is it justified?
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COMMENTARY
ECMO during the COVID‑19 pandemic: When is it justified? Silver Heinsar1,2,3* , Giles J. Peek4 and John F. Fraser1,2,3
Background Abrams et al. recently introduced their view of extracorporeal membrane oxygenation (ECMO) utilisation during the COVID-19 pandemic as a burden-based approach, highlighting that surge conditions may result in decreased utilization of ECMO, as resources must be carefully managed to ensure an acceptable level of care in all patients [1]. Whilst case numbers may overwhelm some health care systems, thus making ECMO seem less attractive, we are offering an extended viewpoint where ECMO may be justified if systems are optimised to proceed without compromising the overall delivery of intensive care (Fig. 1). The objective of this commentary is to provide general guidance, to expand on previously described suggestions by Abrams et al., on ECMO use during pandemic situations, especially while treating the critically ill patients with COVID-19. Conditions allowing for judicious use of ECMO Firstly, apply the best conventional intensive care before moving to ECMO.
ECMO is a complex supportive treatment with inherent complications and significant economic implications. ECMO should only be considered when proven effective and relatively inexpensive measures such as proning, neuromuscular blockade and lung-protective ventilation have been tried without success. Omitting these steps without a valid reason prior to ECMO commencement
*Correspondence: [email protected] 1 Critical Care Research Group (CCRG), The Prince Charles Hospital, Chermside, Brisbane, QLD, Australia Full list of author information is available at the end of the article
is unjustified and a disservice to the global ECMO community. Secondly, pick the right patients for the right treatment.
The staggering contrast in outcomes of currently published ECMO reports amongst all COVID-19 patients tells a tale of different use of the same technology. The heterogeneity of COVID-19 patients with acute respiratory distress syndrome (ARDS) has been hypothesized by numerous authors, whilst no agreement on the existence and nature of possible sub-phenotypes exists [2, 3]. Furthermore, knowledge on COVID-19 atypical manifestations, such as predisposition to intrapulmonary thrombosis, right ventricular failure and the compounded immunologic insult by both COVID-19 infection and the extracorporeal circuit is yet to be fully explored. As the world is still waiting for comparative analyses of COVID19 ECMO patients, intelligent ECMO case selection using the available evidence-base is essential to facilitate each patients’ recovery potential. Considering the currently progressing global pandemic, we propose the use of advanced prediction models, which take into account regional differences, to complement expert opinions and various preliminary algorithms. Artificial intelligence (AI) and machine learning (ML) are well suited to analysing large volumes of complex, heterogenous data in order to guide the lifecritical decisions
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