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This content will become publicly available on June 17, 2025

Title: COVID-19 and silent hypoxemia in a minimal closed-loop model of the respiratory rhythm generator
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 of the respiratory neural network (Diekman et al. in J Neurophysiol 118(4):2194–2215, 2017) 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 thenucleus tractus solitariiare 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.  more » « less
Award ID(s):
2152115 2052109
PAR ID:
10517697
Author(s) / Creator(s):
; ;
Publisher / Repository:
Springer
Date Published:
Journal Name:
Biological Cybernetics
ISSN:
1432-0770
Subject(s) / Keyword(s):
Silent hypoxemia Breathing control Central pattern generator Computational modeling COVID-19 Polycythemia Sensory feedback
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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