Особливості динаміки відновлення порушених когнітивних функцій у пацієнтів із хронічною ішемією мозку після перенесеного COVID-19
Bibliographic record
Abstract
Objective — to investigate the prevalence and severity of cognitive impairments in patients with chronic cerebral ischemia (CCI) following symptomatic COVID-19. Materials and methods. Sixty patients with CCI who had recovered from symptomatic COVID-19 (the main group) and forty patients with CCI without a history of symptomatic COVID-19 (the control group) were examined. The average age of patients in the main group was (62.4 ± 9.0) years, while the average age in the control group was (58.0 ± 9.4) years. Patients in the main group were examined at three time points: 4—12 weeks after symptomatic COVID-19 (first point), and 6 and 12 months post-infection (second and third points). The Montreal Cognitive Assessment (MoCA) was used to assess the presence and severity of cognitive impairments. Results. All patients in the control group exhibited intact cognitive functions. In contrast, only 8.3 % of patients with CCI had cognitive functions within normal limits 4—12 weeks after symptomatic COVID-19, while 76.7 % had mild cognitive impairments (MCI), and 15.0 % exhibited significant cognitive impairments. Cognitive functions showed significant improvement (p < 0.001) at 6 and 12 months post-COVID-19. The proportion of patients with normal cognitive functions increased to 28.6 and 60.0 %, respectively, while the proportion of patients with MCI decreased to 65.3 % (p > 0.05) and 34.3 % (p < 0.001). Conclusions. Symptomatic COVID-19 adversely affected cognitive functions in 91.7 % of patients with CCI, but most of these patients showed a trend toward improvement. One year post-COVID-19, only 40.0 % of patients with CCI still exhibited cognitive impairments. These findings suggest that cognitive functions in patients with CCI significantly recover during the first year following symptomatic COVID-19.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".