INFLUENCE OF SLEEP DISTURBANCES ON COGNITIVE DECLINE IN PATIENTS WITH PARKINSON’S DISEASE
Bibliographic record
Abstract
The article summarizes the arguments and counter-arguments within the scientific discussion on the impact of sleep disorders on the development of cognitive decline in patients with Parkinson's disease. The main purpose of the study is to study the possibility of predicting the development of cognitive decline by assessing the severity of sleep disorders and their differences in the presence of cognitive impairment. Systematization of literature sources and approaches to solving the problem showed that sleep disorders develop in the early stages of Parkinson's disease and are often accompanied by cognitive impairment. Cognitive decline is manifested throughout Parkinson's disease and ranges from moderate in the early stages to dementia in the late stages. The relevance of the study of the relationship between sleep disorders and cognitive functions lies in the possibility of further improving the prediction of the development of cognitive decline in order to effectively correct it. Treatment of sleep disorders can be accompanied by improved memory and even morphological changes in the brain. Therefore, the question arises about the possibility of correcting cognitive decline by influencing sleep disorders. The methodology of the study included assessment of the overall status of patients on a unified scale of Parkinson's disease, Montreal cognitive rating scale and sleep scale in Parkinson's disease. The duration of the study was 8 months. Patients with Parkinson's disease were selected as the study. The article presents the results of a survey of patients who show that patients with Parkinson's disease and cognitive decline showed a predominance of motor disorders, sleep disorders and the overall score on the sleep scale in Parkinson's disease. In the presence of cognitive decline more pronounced disorders of motor functions in everyday life, which can lead to sleep disorders and its quality. The study empirically confirms and theoretically proves that the assessment of sleep disorders can be used to predict the risk of developing cognitive impairment in patients with Parkinson's disease. The results of this study may be useful for improving the early diagnosis and prevention of cognitive impairment in patients with Parkinson's disease, which, in turn, leads to improved quality of treatment of these patients. Such changes can directly affect the choice of therapeutic tactics and improve the quality of life of patients with Parkinson's disease. The question of the features of various sleep disorders and their prognostic value in relation to cognitive decline in patients with various forms of Parkinson's disease remains open.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".