Analysis of the correlation between sleep spindles and cognitive impairment in patients with ischemic stroke
Bibliographic record
Abstract
Sleep spindle (SS) are characteristic electroencephalographic hallmarks of nonrapid eye movement sleep (NREM), typically defined as oscillatory activity in the sigma frequency range (11-16 Hz) lasting 0.5-3.0 s. Research indicates that SS are involved in memory consolidation, promote memory and learning, and are significantly associated with physiological aging and cognitive decline. To explore the changes in the number, amplitude, and duration of SS in patients with acute ischemic stroke, to analyze the impact of SS on cognitive function in stroke patients, and to understand whether SS can serve as biomarkers for assessing cognitive function in stroke patients. This retrospective study included a total of 314 patients who underwent polysomnography (PSG) at the Affiliated Hospital of Yangzhou University from March 2022 to February 2024 were selected and divided into a stroke group (229 patients) and a control group (85 patients). Baseline data, questionnaire scores, PSG parameters, and SS parameters were collected. Differences between the two groups were compared. Multiple linear regression analyse was conducted to evaluate the influencing factors of Montreal Cognitive Assessment (MoCA) score in patients with ischemic stroke. Compared with the control group, the stroke group had lower MoCA score, fewer SS in nonrapid-eye-movement sleep stage 2 (NREM2) and nonrapid-eye-movement sleep stage 3 (NREM3), lower SS indices, a shorter average duration of SS in N2 sleep, and a lower maximum amplitude of SS in the N3 stage. The multiple linear regression models showed that the MoCA score of stroke patients was significantly correlated with age, sleep efficiency and N2 sleep spindle (N2-SS) index. In stroke patients, there is a reduction in the number, a shorter duration, and a decrease in amplitude of SS. The decrease of spindle activity is one of the potential factors affecting the cognitive level of stroke patients. The change of N2-SS can be related to the degree of cognitive impairment in ischemic stroke patients. SS is expected to be a new objective physiological indicator to evaluate the cognitive function after stroke. However, this study represents an initial exploration of associations rather than causal relationships. Future research should focus on longitudinal designs to clarify whether interventions targeting SS activity could improve cognitive outcomes.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".