Demyelination and Cognitive Performance in Long COVID Patients with Insomnia and/or Depression
Bibliographic record
Abstract
Insomnia and depression are severe sequelae of COVID-19 and often occur simultaneously. Our study examined associations of insomnia and/or depression with cognitive impairments, white matter changes, and serum biomarkers. In total, 76 long COVID patients and 22 healthy controls were examined using neuropsychiatric (ISI, HADS, and HDRS) and cognitive (MoCA, Stroop, WMT, and TMT) tests, with their blood biomarkers (anti-SARS-CoV-2, BDNF, anti-S100, anti-MBP, and anti-PLP) investigated, and underwent MRI using macromolecular proton fraction (MPF) mapping to quantify myelination. The Insomnia (n = 14), Depression (n = 12), InsDep (comorbid insomnia-depression, n = 13), and PostCovid (long COVID without depression and insomnia, n = 32) groups were identified based on psychiatric/neurological diagnoses and neuropsychiatric assessment. Cognitive performance was most affected in the Insomnia group in the MoCA and CW Stroop tests. The Depression group underperformed in the TMT and W Stroop task; the InsDep group underperformed in the WMT. The Insomnia group showed the greatest demyelination, affecting commissural (CC and tapetum), projection (CR, IC, CST, cerebral peduncles, CP, and ML), and some association pathways (SLF, SFOF), as well as most juxtacortical regions, the thalamus, and the midbrain; these changes correlated with insomnia severity. The Depression and InsDep groups showed smaller but significant overall demyelination correlated with depression severity. The Depression group exhibited the highest MPF decrease in the globus pallidus, putamen, and external capsule, while the InsDep group demonstrated the highest demyelination of the association pathways IFOF, UF, and cingulum. The anti-PLP levels were the highest in the Insomnia group and correlated with both the persistence of insomnia/depression symptoms and demyelination. Demyelination in long COVID is associated with high levels of myelin-specific autoantibodies, but symptoms of insomnia and/or depression are associated with demyelination of a different set of brain structures.
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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 | 0.001 | 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".