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Afterload mismatch, defined as the inability of the ventricle to maintain stroke volume and ejection fraction (Figure 1), is a major issue after mitral valve repairs. Although the phenomenon is mostly transient, it has been associated with increased mortality in the early post-operative period. Yet, the physiological mechanisms underlying afterload mismatch remain unclear, making it difficult to ascertain proper medical prognosis and risk assessment.

In this thesis, we took a three-pronged approach, combining literature review, retrospective patient database analysis and computational modelling, to further our physiological and clinical understanding of afterload mismatch (Figure 2).

The observed associations in the clinical registries suggest that left-ventricular upstream components contribute to the incidence of the afterload mismatch. Combining these findings with our literature review and detailed analysis of the cardiovascular physiology, we propose a new set of clinical parameters to better characterize its onset and potentially identify patients at risk. While our computational model could capture some of the hallmarks of mitral valve regurgitation and mitral valve repair (Figure 3), the reproduction of patient-specific characteristics revealed challenging calling for further refinements on both the simulation methodology and parameter identification procedure. Most importantly the combined clinical datasets and analyses resulting from this thesis may serve as a basis for the implementation of a new prospective study on this topic.

This thesis was conducted in close collaboration with Prof. Dr. med. Francesco Maisano and Dr. Andrea Guidotti from the Department of Cardiovascular surgery at the University Hospital of Zurich