Cognitive Impairment and Brain Metabolic Changes in Post-Acute Sequelae of COVID-19
Bibliographic record
Abstract
PURPOSE: Neurological symptoms often prominent in post-acute sequelae of COVID-19 (PASC) necessitate deeper understanding. Our objective was to investigate brain metabolism in PASC and examine correlations with neurological symptoms during both the acute and chronic stages. METHODS: Eighty-seven adults experiencing PASC with neurocognitive symptoms were recruited in the PERSICOR prospective study and examined using brain [ 18 F]FDG PET/CT. Comprehensive clinical variables including neurocognitive symptoms were evaluated. PET images were compared voxel-wise with SPM12 software ( P < 0.05, false discovery rate corrected) and volume-of-interest basis (BrainVisa software) with those of 55 healthy controls recruited before COVID-19 pandemic. We also investigated differences in brain metabolism according to the time interval after acute COVID-19. The correlation between brain metabolism and neurocognitive symptoms was assessed. RESULTS: Frequently reported neurological symptoms included concentration difficulties (79%) and immediate/working memory impairments (66%). Significant hypometabolism was identified in regions previously identified in PASC: left fusiform gyrus (33% of patients), amygdala (23% on left, 28% on right), parahippocampal area (25% left, 24% right), and vermis (22%). The most substantial metabolism decreases were observed in the pons (5.5% decrease in the whole patient group vs controls) and right amygdala (-4.2%). Concentration and memory impairments correlated with decreased metabolism in prefrontal and mesial/inferior temporal areas, respectively ( P < 0.01 for both). A shorter interval between PET imaging and the acute phase of COVID-19 correlated with reduced glucose metabolism in the brainstem, thalamus, mesiotemporal lobe, frontobasal cortex, and olfactory bulb ( P < 10 -3 ). CONCLUSIONS: This study underscores the links between neurological symptoms and cerebral hypometabolism in specific regions in PASC. These findings illuminate the complex neuropathophysiological mechanisms of PASC and pave the way for potential therapeutic interventions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".