Key result
Evolving ECMO prognostic models and decision support tools promise more accurate predictions and automated management.
Why the study?
Prognostic modelling techniques have rapidly evolved and may produce predictive decision support tools to improve complex clinical decisions regarding ECMO allocation and management.
Prognostic models and digital twins hold potential to improve complex clinical decisions surrounding ECMO allocation and management, though current models require external validation and better alignment with clinical workflows.
Prognostic modelling techniques have rapidly evolved over the past decade and may greatly benefit patients supported with ExtraCorporeal Membrane Oxygenation (ECMO). Epidemiological and computational physiological approaches aim to provide more accurate predictive assessments of ECMO-related risks and benefits. Implementation of these approaches may produce predictive tools that can improve complex clinical decisions surrounding ECMO allocation and management. This Review describes current applications of prognostic models and elaborates on upcoming directions for their clinical applicability in decision support tools directed at improved allocation and management of ECMO patients. The discussion of these new developments in the field will culminate in a futuristic perspective leaving ourselves and the readers wondering whether we may “ fly ECMO by wire” someday.
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Pladet et al. (2023) conducted a review in Patients supported with ExtraCorporeal Membrane Oxygenation (ECMO). Prognostic modelling and clinical decision support tools was evaluated. Prognostic modeling and clinical decision support tools for ECMO are evolving, potentially leading to more accurate predictive assessments and automated management in the future.
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