Cognitive and behaviorial features of a cohort of patients in COVID-19 post-acute phase
Bibliographic record
Abstract
Background and aims: Our study aimed to assess EEG findings and their clinical and neuropsychological correlates in patients with recent COVID-19. Methods: We enrolled 55 adult patients with recent COVID-19, good recovery and objective and/or selfreported cognitive disturbances, observed at follow-up neurological evaluation (2 months after discharge). Sameday basal EEG and neuropsychological testing battery were performed. EEG were assessed for background activity, individual alpha frequency (IAF), presence/location of focal slowing, epileptiform abnormalities and seizures. Correlations with neuropsychological and clinical variables were assessed using linear/logistic regression. Results: We evaluated 55 patients (70.9% males, mean age 60.5±13.3 years);13/55 (23.6%) had needed ventilatory support (12 NIV, one intubation). Mean adjusted Montreal Cognitive Assessment (MoCA) score was 21.3±2.8. Modest EEG background-activity alteration was observed in 5/55 (9.1%) patients. Prevailing fronto-temporal focal slowwave activity (SWA) was observed in 6/55 (10.9%) patients. Brief (<5 sec) anterior theta/alpha activity sequences were recorded in 10/55 (18.2%) subjects. No epileptiform/seizure discharges were recorded. 41/55 (74.5%) patients had experienced mild neurological symptoms during acutephase COVID-19. Only confusion/disorientation was associated with EEG parameters, particularly with anterior theta/alpha activity. IAF did not correlate with acute-phase respiratory severity scores or neuropsychological findings. Presence of anterior theta-alpha activity was associated with lower executive-function scores at frontal assessment battery and symbol-digit modalities test. Executive-function impairment was not associated with background-activity alteration or SWA. Conclusion: EEG alterations after COVID-19 might be independent of acute infection severity and suggest a link with ongoing neuro-psychiatric symptoms. Further followup data is needed to confirm the reversibility and/or evolution of our findings.
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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 | 0.001 | 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".