Clinical-neurological and cognitive changes in patients with COVID-19
Bibliographic record
Abstract
Background. The coronavirus disease is the cause of various neurological and mental disorders, namely impaired memory, attention, the development of anxiety and depression. First of all, complications after the illness require improvement of the system of early diagnosis of cognitive disorders and psycho-emotional changes in patients who have suffered from COVID-19. Purpose – the study of neurological complications after suffering from the disease of COVID-19 and the identification of markers of disorders of the nervous system after the coronavirus disease to improve early diagnosis. Materials and Methods. 100 patients were involved in this study, who were divided into 2 groups: the main and control, aged from 19 to 60 years, men predominated – 60 people, women – 40 people. The main group is represented by patients with a confirmed diagnosis of COVID-19 and who received inpatient or outpatient treatment. The control group included patients who did not suffer from this disease. The participants underwent a clinical and neurological examination, which included a collection of complaints, medical history, and the presence of concomitant pathology. Assessment of cognitive changes performed on patients, namely the Montreal Cognitive Assessment Scale (MoCA); Luria’s «10 words» test, which made it possible to study memory processes; Schulte’s tables, with the help of which the switching of attention was studied. Results. According to the results of the examination of the MoCA scale, it was found that in the main group, compared to the control group, cognitive disorders were noted, both at the time of inclusion in the study and at the re-examination after 6 months. During the Luria test, no statistically significant difference was found when comparing the indicators obtained during the re-examination of patients with the indicator obtained during inclusion in the study. To study the switching of attention with the help of Schulte tables, it was established that the patients of the main group needed on average more time to search for information compared to the patients of the control group, as at the beginning of the study (151 (118; 171) s vs. 119 (112; 134) s, p < 0.001), and after 6 months (127 (107; 143) s vs. 98 (87; 103) s, p < 0.001). Conclusions. The detection of cognitive decline from the onset of the disease and its persistence after 6 months may indicate the induction of a neurodegenerative process from the onset of the disease after the transfer of COVID-19, which requires further study.
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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 | 0.001 | 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) | 0.002 | 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".