Classifying fidelity for ECMO simulators and simulations: an overview of existing physical and computational ECMO simulators

Objectives:
High-volume ECMO centers have better clinical outcomes than low-volume centers due to higher clinical exposure. Simulation-based training
(SBT) can be an alternative for these centers to reach similar experience levels. SBT not only improves education of the individual caregiver but also
improves multidisciplinary ECMO teams. However, ECMO simulators and/or simulations (Sims) differ on realism and functions, making each of these
simulators useful for different purposes. Classifying Sims is often subjective and left to the individual user and/or creator. This scoping review aims to
present a structured and objective way to classify available Sims.

Methods:
Physical and/or computational Sims with public information in English were screened for eligibility. Overall fidelity was established by taking the
median of definition-based fidelity, derived from literature, and combining this with the median of our newly established component fidelity and
customization fidelity. Component fidelity was based on the main elements of ECMO support while customization fidelity was based on main parameters to
(re)create a unique patient, see table. Sims were subsequently classified as being low-, mid-, or high-fidelity.

Results:
Universal definitions for SBT were applied to Sims. According to our objective classification method, 10 (38%) low, 16 (62%) mid and no highfidelity
Sims exist. Most (54%) Sims are lacking customization options for patient-specific modelling.

Conclusions:
Overall fidelity of available Sims were objectively classified based on definition-based, component, and customization fidelity. No high-fidelity
Sims currently exists, urging for development of a high-fidelity simulator to improve ECMO-team training and improve patient outcomes. With our method,
future Sims can be classified more objectively allowing for users and researchers to compare accordingly.