Frontal-striatal glucose metabolism and fatigue in patients with multiple sclerosis, long COVID, and COVID-19 recovered controls, 2024, Rudroff+

Frontal-striatal glucose metabolism and fatigue in patients with multiple sclerosis, long COVID, and COVID-19 recovered controls
Rudroff, Thorsten

This study compared brain glucose metabolism using FDG-PET in the caudate nucleus, putamen, globus pallidus, thalamus, and dorsolateral prefrontal cortex (DLPFC) among patients with Long COVID, patients with fatigue, people with multiple sclerosis (PwMS) patients with fatigue, and COVID recovered controls.

PwMS exhibited greater hypometabolism compared to long COVID patients with fatigue and the COVID recovered control group in all studied brain areas except the globus pallidus (effect size range 0.7–1.5). The results showed no significant differences in glucose metabolism between patients with Long COVID and the COVID recovered control group in these regions.

These findings suggest that long COVID fatigue may involve non-CNS systems, neurotransmitter imbalances, or psychological factors not captured by FDG-PET, while MS-related fatigue is associated with more severe frontal-striatal circuit dysfunction due to demyelination and neurodegeneration.

Symmetrical standardized uptake values (SUVs) between hemispheres in all groups imply that fatigue in these conditions may be related to global or network-level alterations rather than hemisphere-specific changes.

Future studies should employ fine-grained analysis methods, explore other brain regions, and control for confounding factors to better understand the pathophysiology of fatigue in MS and long COVID. Longitudinal studies tracking brain glucose metabolism in patients with Long COVID could provide insights into the evolution of metabolic patterns as the condition progresses.

Link | PDF (Experimental Brain Research)

 

I can't access this currently.

 

Unfortunately they determined whether patients were or were not experiencing PCS using the Chalder scale:

The group characteristics and SUV data:

 

WTF?

This is so bizarre. Wasting an entire study by making such a terrible choice. There is literally no point looking at the study because of this. I guess academics do this because quality doesn't matter, getting published is the goal in itself. Still how is anyone OK with working on something only for it to be worthless? I don't get it. There are such huge problems with judgment in this profession, it's so damn poor.