Increased breathlessness in post-COVID syndrome despite normal breathing patterns in a rebreathing challenge.

Severe symptoms in the absence of measurable body pathology are a frequent hallmark of post-COVID syndrome. From a Bayesian Brain perspective, such symptoms can be explained by incorrect internal models that the brain uses to interpret sensory signals. In this pre-registered study, we investigate whether induced breathlessness perception during a controlled CO2rebreathing challenge is reflected by altered respiratory measures (physiology and breathing patterns), and propose different computational mechanisms that could explain our findings in a Bayesian Brain framework. We analysed data from 40 patients with post-COVID syndrome and 40 healthy participants. Results from lung function, neurological and neurocognitive examination of all participants were within normal limits on the day of the experiment. Using a Bayesian repeated-measures ANOVA, we found that patients' breathlessness was strongly increased (BF10,baseline=8.029, BF10,rebreathing=11636, BF10,recovery=43662) compared to controls. When excluding patients who hyperventilated (N = 8, 20%) during the experiment from the analysis, differences in breathlessness remained (BF10,baseline=1.283, BF10,rebreathing=126.812, BF10,recovery=751.282). For physiology and breathing patterns, all evidence pointed towards no difference between the two groups (0.307 > BF10 < 0.704). In summary, we found intact breathing patterns and physiology but increased symptom perception in patients with post-COVID syndrome.