- #1
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- TL;DR
- Brain imaging Before and After COVID-19 shows loss of brain grey matter after COVID-19
Significant Loss of Brain Grey Matter after COVID-19
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SUMMARY
The discussion highlights significant loss of grey matter in specific brain regions due to COVID-19, particularly in the left parahippocampal gyrus, left lateral orbitofrontal cortex, and left insula. Additional effects were observed across the cortical surface, including the anterior cingulate cortex, supramarginal gyrus, and temporal pole. Concerns were raised regarding the study's methodology, particularly the potential for false positives due to the analysis of approximately 2,000 brain imaging features, which may lead to p-hacking. The statistically significant differences reported may not be biologically meaningful, raising questions about their clinical relevance.
PREREQUISITES- Understanding of neuroanatomy, specifically brain regions such as the parahippocampal gyrus and orbitofrontal cortex.
- Familiarity with brain imaging techniques and their statistical analysis.
- Knowledge of p-hacking and its implications in scientific research.
- Awareness of the clinical significance of neuroimaging findings.
- Research the implications of grey matter loss in the left parahippocampal gyrus on cognitive function.
- Explore methodologies for correcting for multiple comparisons in neuroimaging studies.
- Investigate the relationship between brain structure changes and clinical symptoms in COVID-19 patients.
- Learn about advanced neuroimaging techniques and their applications in understanding brain health post-COVID-19.
This discussion is beneficial for neuroscientists, clinical researchers, and healthcare professionals interested in the neurological impacts of COVID-19 and the interpretation of neuroimaging data.
- #2
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After a quickly browsing the paper, I'm somewhat skeptical of the results of the study. The study did comparisons of ~2,000 features from their brain imaging between the two groups, which gives plenty of opportunities to find false positives (potentially an example of p-hacking). Furthermore, the statistically significant differences the paper finds seem quite small compared to normal variation. For example, here are some of the most significant longitudinal group comparison results from Fig 1 of the paper:
https://www.medrxiv.org/content/10.1101/2021.06.11.21258690v1.full.pdf
While these results may be statistically significant differences (at least, assuming they corrected for multiple comparison correction correctly), it's not clear whether these observed differences would be biologically meaningful (i.e. whether the differences are large enough to cause clinically relevant symptoms).
https://www.medrxiv.org/content/10.1101/2021.06.11.21258690v1.full.pdf
While these results may be statistically significant differences (at least, assuming they corrected for multiple comparison correction correctly), it's not clear whether these observed differences would be biologically meaningful (i.e. whether the differences are large enough to cause clinically relevant symptoms).
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