The relative role of patient physiology and device optimisation in cardiac resynchronisation therapy: A computational modelling study
Why the study?
Does pacing lead placement optimisation or patient physiological conditions have a greater impact on CRT outcomes in a computational model?
Population
648 virtual patients generated from a multi-scale biophysical model of cardiac electromechanics personalised…
Design
Preclinical
Authors
Discussion
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Member takes
Implication
Pacing site optimization may merit priority in CRT models; leaves open translation to patient physiology and outcomes.
Structured PICO
Does pacing lead placement optimisation or patient physiological conditions have a greater impact on CRT outcomes in a computational model?
P
Population
648 virtual patients generated from a multi-scale biophysical model of cardiac electromechanics personalised to patient data from 3 patients
I
Intervention
Pacing lead placement optimisation and physiological conditions (cardiac anatomy, myocardial conductivity, stiffness, afterload, active contraction, conduction block)
O
Outcome
Change in total activation time of the ventricles (ΔTAT) and acute haemodynamic response (AHR)surrogate
Computational modelling suggests that pacing site location has the largest effect on CRT outcomes, highlighting the need for greater emphasis on therapy optimisation.
Cite This Study
Crozier et al. (2015) studied this question.