Preprint Journal Article Epublish 1 citation
PubMed: 37131753 DOI: 10.1101/2023.04.19.536507
COVID-19 and silent hypoxemia in a minimal closed-loop model of the respiratory rhythm generator.
bioRxiv
Authors: Casey O Diekman, Peter J Thomas, Christopher G Wilson
Affiliations
- Department of Mathematical Sciences, New Jersey Institute of Technology, University Heights, Newark NJ 07102.
- Department of Mathematics, Applied Mathematics and Statistics, Case Western Reserve University, 10900 Euclid Avenue, Cleveland OH 44106.
- Department of Pediatrics & Basic Sciences, Loma Linda University, Lawrence D. Longo, MD Center for Perinatal Biology, 11223 Campus St, Loma Linda CA 92350.
Abstract
Silent hypoxemia, or 'happy hypoxia', is a puzzling phenomenon in which patients who have contracted COVID-19 exhibit very low oxygen saturation (SaO 2 < 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 (Diekman et al., 2017, J. Neurophysiol) of the respiratory neural network 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.
MeSH
Infections, Central Pattern Generators, Covid-19