Cognitive impairment in COVID-19 patients complicated by depression after the acute phase
Bibliographic record
Abstract
BACKGROUND: Damage of the central nervous system in COVID-19 patients includes cognitive impairment, depression, and fatigue. Clinical features of cognitive impairment after the acute phase of COVID-19 and the contribution of various factors to the development of memory deficit have not been fully studied. AIM: This study assesses the clinical features of cognitive impairment in COVID-19 patients complicated by depression after the acute phase and analyzes how health and demographic factors contribute to the development of cognitive impairment. MATERIALS AND METHODS: The observational cross-sectional study includes 33 patients aged 18–80 (mean age: 53.5; women: 60.6%) who meet the eligibility criteria. All subjects had a clinical semi-structured interview, a general clinical examination, MoCA, HDRS-17, and MFI-20 neuropsychological tests. RESULTS: The average MoCA-total score was 23.8±2.2. Cognitive impairments primarily affected memory (average MoCA memory score: 10.5±2.0), executive functions (average MoCA executive functioning score: 9.5±1.1), and attention (average MoCA attention score: 14.8±1.9). There is a strong negative correlation of HDRS-17 and MoCA-total values ( r=−0.72; p0.05), executive functioning index ( r=−0.82; p0.05), and memory index ( r=−0.85; p0.05). Age (β=−0.028; p=0.03), number of cardiovascular risk factors (β=−0.53; p=0.001), severity of COVID-19 in the acute phase (β=−0.97; p=0.001) and depression (β=−0.065; p=0.02) are the main contributors to cognitive impairment. CONCLUSION: Multi-domain cognitive impairment with predominant deterioration of executive functions, memory and attention was detected in patients who had COVID-19 complicated by depression after the acute phase. The key factors of, or main contributors to, cognitive impairment were identified, which can help select the best targeted therapy for this category of patients.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".