This is an updated version of a closed-loop respiratory control model incorporating a central pattern generator (CPG), the Butera-Rinzel-Smith (BRS) model, together with lung mechanics, oxygen handling, and chemosensory components (see accession number 229640). We explored model parameters consistent with the silent hypoxemia phenomenon observed in some COVID-19 patients.
Experimental motivation: Silent hypoxemia, or "happy hypoxia", is a puzzling phenomenon in which patients who have contracted COVID-19 exhibit very low oxygen saturation (SaO2<80%) but do not experience discomfort in breathing. The mechanism by which this blunted response to hypoxia occurs is unknown. We have previously shown that a computational model of the respiratory neural network (Diekman et al., 2017, J. Neurophysiol) can be used to test hypotheses focused on changes in chemosensory inputs to the central pattern generator (CPG). We hypothesize that altered chemosensory function at the level of the carotid bodies and/or the nucleus tractus solitarii are responsible for the blunted response to hypoxia. Here, we use our model to explore this hypothesis by altering the properties of the gain function representing oxygen sensing inputs to the CPG. We then vary other parameters in the model and show that oxygen carrying capacity is the most salient factor for producing silent hypoxemia. We call for clinicians to measure hematocrit as a clinical index of altered physiology in response to COVID-19 infection.
Model Type: Neuron or other electrically excitable cell
Region(s) or Organism(s): Brainstem
Cell Type(s): Brainstem neuron
Receptors:
Genes:
Transmitters:
Model Concept(s): COVID-19; Pacemaking mechanism; Respiratory control
Simulation Environment: MATLAB
Implementer(s): Diekman, Casey O. [casey.o.diekman at njit.edu]; Thomas, Peter J; Wilson, Charles G
References:
Diekman CO, Thomas PJ, Wilson CG. (2024). COVID-19 and silent hypoxemia in a minimal closed-loop model of the respiratory rhythm generator. Biological cybernetics. [PubMed]