Neuropsychiatric symptoms and altered sleep quality in cerebral small vessel disease
Bibliographic record
Abstract
Background: Sleep disturbance and neuropsychiatric symptoms are common clinical symptoms of cerebral small vessel disease (CSVD), but the underlying mechanism is unclear. Here, we investigated the relationship between sleep quality and neuropsychiatric performance in patients with CSVD. Methods: A total of 30 patients with CSVD and 35 healthy controls (HCs) were recruited. The 13-item Beck Depression Inventory (BDI-13), Beck Anxiety Inventory (BAI), and Symptom Check List 90 (SCL90) were used to assess depression, anxiety, and other psychological symptoms, respectively. Sleep quality was assessed using Pittsburgh Sleep Quality Index (PSQI), and cognitive function was tested using Montreal Cognitive Assessment (MoCA). Results: < 0.05). The prevalence of comorbid poor sleep quality in the patients with CSVD was approximately 46%. The patients with CSVD with poor sleep quality also had more severe neuropsychiatric symptoms. After controlling for demographic variables, sex and anxiety significantly predicted sleep quality. Conclusion: This study suggests that the prevalence of CSVD with poor sleep quality is high, and that sex and anxiety are independent risk factors for CSVD comorbid sleep quality.
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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 | 0.000 |
| 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) | 0.002 | 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".