Effects of Trazodone on Sleep Quality and Cognitive Function in Arteriosclerotic Cerebral Small Vessel Disease Comorbid With Chronic Insomnia
Bibliographic record
Abstract
BACKGROUND: Chronic insomnia is common in patients with arteriosclerotic cerebral small vessel disease (CSVD) and aggravates the cognitive impairment caused by CSVD. Low-dose trazodone is effective in treating insomnia, but it is unclear whether it can also improve cognitive function in CSVD patients. This study was performed to explore the effects of trazodone on sleep quality and cognitive function in CSVD comorbid with chronic insomnia. METHODS: This was a randomized, double-blind, placebo-controlled pilot study. Forty patients suffering from arteriosclerotic CSVD and insomnia were recruited from an outpatient clinic. Participants were randomized individually to receive either trazodone (study group) or a placebo (control group) for 4 weeks. The primary outcome was the cognitive score on the Montreal Cognitive Assessment scale (MoCA). Secondary outcomes included sleep parameters measured with polysomnography (PSG) and the Pittsburgh Sleep Quality Index. RESULTS: Trazodone caused significantly better improvements in concentration and recall abilities, measured with MoCA, as well as in PSG parameters such as sleep efficiency, N3 sleep ratio, and sleep continuity than the placebo, with no significant differences in the occurrence of side effects. The improvement of sleep quality was correlated with increased concentration and recall abilities. CONCLUSIONS: A low dose of trazodone seems acceptable and effective in reducing insomnia severity and improving concentration and recall abilities in this pilot study. The improvement of cognition could be achieved by alleviation of insomnia severity. Considering the high incidence of insomnia in CSVD patients, the results of this preliminary study support the use of low-dose trazodone to deal with insomnia and cognitive impairment in CSVD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 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".