Cognitive Functions During Acute Period of COVID-19 and Recovery
Bibliographic record
Abstract
Study Objective: To identify the impact from the pneumonia-complicated COVID-19 coronavirus infection over patients’ cognitive functions. Study design: Perspective study. Materials and Methods. We examined 32 patients with COVID from the study group on days 2–3, 8–10 in inpatient settings, after 2 months of hospitalisation vs 30 healthy controls. Cognitive functions were evaluated using the following neuropsychologic tests: Montreal Cognitive Assessment (MoCA), Mini Mental State Examination (MMSE), Frontal Assessment Battery (FAB), The Clock-drawing Test (CDT). Signs of anxiety and depression were screened using the Hospital Anxiety and Depression Scale (HADS). Study Results. During the acute and recovery periods, patients from the study group demonstrated statistically significant cognitive disorders as per MMSE, MoCA, FAB vs controls (p < 0.001). On days 2–3 and 8–10 in inpatient settings, MMSE was 22 [22; 29] and 22 [19.2; 23.7] points; MoCA — 26 [21; 28] and 21 [18; 23] points, FAB — 13 [10; 18] and 10 [8; 12] points; in 2 months after hospitalisation, MMSE was 29 [26.8; 30] points (р = 0.008 vs days 2–3 and 8–10), MoCA — 25 [22; 27] points (р = 0.03 vs days 8–10), FAB — 16 [14.5; 17] points (р = 0.004 and р = 0.02). The condition of cognitive functions measured during the acute period of the disease worsened even more by days 8–10 of hospitalisation and tended to normalise in 2 months. As per HADS, there were no abnormal findings; therefore, the patients were neither anxious, nor depressed, and the median was 8 points. СDT values were normal as well, both in acute period and during recovery. Conclusion. The coronavirus infection impacts the cognitive status. For cognitive dysfunctions, neuroprotectives and non-drug cognitive rehabilitation can be recommended. Cognitive dysfunctions are quite an expected independent syndrome, the course of which is not directly associated with somatic recovery. Keywords: COVID-19, cognitive disorders, coronavirus infection, pandemic.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".