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Development of an app-based bedside clinical decision-making tool for mechanical cardiocirculatory support in patients with cardiogenic shock: the MCS-Aid app
BACKGROUND: Patients presenting with cardiogenic shock remain at high risk of morbidity and mortality. Several mechanical cardiocirculatory support (MCS) devices have been developed and their use is rapidly increase in clinical practice. However, there is significant heterogeneity in patient selecti...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9779758/ http://dx.doi.org/10.1093/ehjdh/ztac076.2791 |
Sumario: | BACKGROUND: Patients presenting with cardiogenic shock remain at high risk of morbidity and mortality. Several mechanical cardiocirculatory support (MCS) devices have been developed and their use is rapidly increase in clinical practice. However, there is significant heterogeneity in patient selection, timing of implantation, and post-implantation management across centers and operators. PURPOSE: We sought to develop and smartphone app-based clinical decision-making tool to help bedside selection and post-implantation management of MCS devices in patients presenting with cardiogenic shock or cardiac arrest. METHODS: The MCS-Aid app will consistent of 3 major sections: (i) initial device selection based on clinical presentation (patients with cardiogenic shock or cardiac arrest post-ROSC); (ii) guide for escalation or addition of MCS based on the individual hemodynamic scenario; (iii) guide for weaning after implantation of MCS device. The app will have an interactive interface that will allow the user to select the most appropriate next step in management based on the clinical information being entered. A calculator to derive key hemodynamic parameters (e.g. cardiac power output or pulmonary artery pulsatility index) will be incorporated in the App to inform clinical decision-making when appropriate. An example of an algorithm that will be part of the MCS-Aid app is illustrated in the figure. CONCLUSIONS: The MCS-Aid app is an user-friendly bedside clinical decision tool that could help fellows-in-training, early-career interventionalist and interventional cardiologist to select the appropriate MCS device according to the individual clinical and hemodynamic scenario. FUNDING ACKNOWLEDGEMENT: Type of funding sources: Private company. Main funding source(s): Abiomed |
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