Introduction
Mathematical models based on the physiology, namely, physiological
models, have a crucial role in understanding the underlying mechanisms.
When programmed as a software with a graphical user interface, these
so-called computational models, or virtual patients, could be used to
teach cardiorespiratory physiology and ventilation, determine optimal
ventilation management as well as forecast the effect of various
ventilatory support strategies (1–3). Furthermore, due to its virtual
nature, prediction over a large amount of time can be summarized in a
few minutes, making the assessment of the model more convenient than a
real time assessment. Currently, there is no validated virtual patient
specifically designed for modelling children cardiorespiratory system.
Thus, our research team developed a cardiorespiratory simulator for
children called “SimulResp” (figure 1) (2,4). SimulResp provides
cardiorespiratory parameters, such as blood gases values, while
simulating spontaneous and artificial ventilation situations for
patients of various ages and weights with several pathological
conditions. This simulator is based on physiological principles. Before
a widespread use in respiratory status forecasting, this simulator must
be validated (5). According to Summers et al. (6,7), the quality of a
physiologic model is evaluated by three specific criteria: 1)
qualitatively, which relates to the model’s ability to provide
directionally appropriate predictions; 2) quantitatively in steady
states and 3) in dynamics, which is the ability of the model to provide
accurate predictions in steady state situations as well as dynamic
transitions. The purpose of this study was to evaluate the quality of
SimulResp according to these criteria in a pediatric critical care
population.